Lecture Notes in Artificial Intelligence 11439

Subseries of Lecture Notes in Computer Science

Series Editors

Randy GoebelUniversity of Alberta, Edmonton, Canada

Yuzuru TanakaHokkaido University, Sapporo, Japan

Wolfgang WahlsterDFKI and Saarland University, Saarbrücken, Germany

Founding Editor

Jörg SiekmannDFKI and Saarland University, Saarbrücken, Germany

More information about this series at http://www.springer.com/series/1244

Qiang Yang • Zhi-Hua Zhou •

Zhiguo Gong • Min-Ling Zhang •

Sheng-Jun Huang (Eds.)

Advances inKnowledge Discoveryand Data Mining23rd Pacific-Asia Conference, PAKDD 2019Macau, China, April 14–17, 2019Proceedings, Part I

123

EditorsQiang YangHong Kong University of Scienceand TechnologyHong Kong, China

Zhi-Hua ZhouNanjing UniversityNanjing, China

Zhiguo GongUniversity of MacauTaipa, Macau, China

Min-Ling ZhangSoutheast UniversityNanjing, China

Sheng-Jun HuangNanjing University of Aeronauticsand AstronauticsNanjing, China

ISSN 0302-9743 ISSN 1611-3349 (electronic)Lecture Notes in Artificial IntelligenceISBN 978-3-030-16147-7 ISBN 978-3-030-16148-4 (eBook)https://doi.org/10.1007/978-3-030-16148-4

Library of Congress Control Number: 2019934768

LNCS Sublibrary: SL7 – Artificial Intelligence

© Springer Nature Switzerland AG 2019This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of thematerial is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,broadcasting, reproduction on microfilms or in any other physical way, and transmission or informationstorage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology nowknown or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoes not imply, even in the absence of a specific statement, that such names are exempt from the relevantprotective laws and regulations and therefore free for general use.The publisher, the authors and the editors are safe to assume that the advice and information in this book arebelieved to be true and accurate at the date of publication. Neither the publisher nor the authors or the editorsgive a warranty, expressed or implied, with respect to the material contained herein or for any errors oromissions that may have been made. The publisher remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.

This Springer imprint is published by the registered company Springer Nature Switzerland AGThe registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

PC Chairs’ Preface

It is our great pleasure to introduce the proceedings of the 23rd Pacific-Asia Conferenceon Knowledge Discovery and Data Mining (PAKDD 2019). The conference providesan international forum for researchers and industry practitioners to share their newideas, original research results, and practical development experiences from allKDD-related areas, including data mining, data warehousing, machine learning, arti-ficial intelligence, databases, statistics, knowledge engineering, visualization,decision-making systems, and the emerging applications.

We received 567 submissions to PAKDD 2019 from 46 countries and regions allover the world, noticeably with submissions from North America, South America,Europe, and Africa. The large number of submissions and high diversity of submissiondemographics witness the significant influence and reputation of PAKDD. A rigorousdouble-blind reviewing procedure was ensured via the joint efforts of the entireProgram Committee consisting of 55 Senior Program Committee (SPC) members and379 Program Committee (PC) members.

The PC Co-Chairs performed an initial screening of all the submissions, amongwhich 25 submissions were desk rejected due to the violation of submission guidelines.For submissions entering the double-blind review process, each one received at leastthree quality reviews from PC members or in a few cases from external reviewers (with78.5% of them receiving four or more reviews). Furthermore, each valid submissionreceived one meta-review from the assigned SPC member who also led the discussionwith the PC members. The PC Co-Chairs then considered the recommendations andmeta-reviews from SPC members, and looked into each submission as well as itsreviews and PC discussions to make the final decision. For borderline papers, addi-tional reviews were further requested and thorough discussions were conducted beforefinal decisions.

As a result, 137 out of 567 submissions were accepted, yielding an acceptance rateof 24.1%. We aim to be strict with the acceptance rate, and all the accepted papers arepresented in a total of 20 technical sessions. Each paper was allocated 15 minutes fororal presentation and 2 minutes for Q/A. The conference program also featured threekeynote speeches from distinguished data mining researchers, five cutting-edgeworkshops, six comprehensive tutorials, and one dedicated data mining contest session.

We wish to sincerely thank all SPC members, PC members and externel reviewersfor their invaluable efforts in ensuring a timely, fair, and highly effective paper reviewand selection procedure. We hope that readers of the proceedings will find that thePAKDD 2019 technical program was both interesting and rewarding.

February 2019 Zhiguo GongMin-Ling Zhang

General Chairs’ Preface

On behalf of the Organizing Committee, it is our great pleasure to welcome you toMacau, China for the 23rd Pacific-Asia Conference on Knowledge Discovery and DataMining (PAKDD 2019). Since its first edition in 1997, PAKDD has well established asone of the leading international conferences in the areas of data mining and knowledgediscovery. This year, after its four previous editions in Beijing (1999), Hong Kong(2001), Nanjing (2007), and Shenzhen (2011), PAKDD was held in China for the fifthtime in the fascinating city of Macau, during April 14–17, 2019.

First of all, we are very grateful to the many authors who submitted their work to thePAKDD 2019 main conference, satellite workshops, and data mining contest. We weredelighted to feature three outstanding keynote speakers: Dr. Jennifer Neville fromPurdue University, Professor Hui Xiong from Baidu Inc., and Professor JosepDomingo-Ferrer from Universitat Rovira i Virgili. The conference program was furtherenriched with six high-quality tutorials, five workshops on cutting-edge topics, and onedata mining contest on AutoML for lifelong machine learning.

We would like to express our gratitude to the contributions of the SPC members,PC members, and external reviewers, led by the PC Co-Chairs, Zhiguo Gong andMin-Ling Zhang. We are also very thankful to the other Organizing Committeemembers: Workshop Co-Chairs, Hady W. Lauw and Leong Hou U, TutorialCo-Chairs, Bob Durrant and Yang Yu, Contest Co-Chairs, Hugo Jair Escalante andWei-Wei Tu, Publicity Co-Chairs, Yi Cai, Xiangnan Kong, Gang Li, and Yasuo Tabei,Proceedings Chair, Sheng-Jun Huang, and Local Arrangements Chair, Andrew Jiang.We wish to extend our special thanks to Honorary Co-Chairs, Hiroshi Motoda andLionel M. Ni, for their enlightening support and advice throughout the conferenceorganization.

We appreciate the hosting organization University of Macau, and our sponsorsMacao Convention & Exhibition Association, Intel, Baidu, for their institutional andfinancial support of PAKDD 2019. We also appreciate the Fourth Paradigm Inc.,ChaLearn, Microsoft, and Amazon for sponsoring the PAKDD 2019 data miningcontest. We feel indebted to the PAKDD Steering Committee for its continuingguidance and sponsorship of the paper award and student travel awards.

Last but not least, our sincere thanks go to all the participants and volunteers ofPAKDD 2019—there would be no conference without you. We hope you enjoyPAKDD 2019 and your time in Macau, China.

February 2019 Qiang YangZhi-Hua Zhou

Organization

Organizing Committee

Honorary Co-chairs

Hiroshi Motoda Osaka University, JapanLionel M. Ni University of Macau, SAR China

General Co-chairs

Qiang Yang Hong Kong University of Science and Technology,SAR China

Zhi-Hua Zhou Nanjing University, China

Program Committee Co-chairs

Zhiguo Gong University of Macau, ChinaMin-Ling Zhang Southeast University, China

Workshop Co-chairs

Hady W. Lauw Singapore Management University, SingaporeLeong Hou U University of Macau, China

Tutorial Co-chairs

Bob Durrant University of Waikato, New ZealandYang Yu Nanjing University, China

Contest Co-chairs

Hugo Jair Escalante INAOE, MexicoWei-Wei Tu The Fourth Paradigm Inc., China

Publicity Co-chairs

Yi Cai South China University of Technology, ChinaXiangnan Kong Worcester Polytechnic Institute, USAGang Li Deakin University, AustraliaYasuo Tabei RIKEN, Japan

Proceedings Chair

Sheng-Jun Huang Nanjing University of Aeronautics and Astronautics,China

Local Arrangements Chair

Andrew Jiang Macao Convention & Exhibition Association, China

Steering Committee

Co-chairs

Ee-Peng Lim Singapore Management University, SingaporeTakashi Washio Institute of Scientific and Industrial Research,

Osaka University, Japan

Treasurer

Longbing Cao Advanced Analytics Institute, Universityof Technology, Sydney, Australia

Members

Dinh Phung Monash University, Australia (Member since 2018)Geoff Webb Monash University, Australia (Member since 2018)Jae-Gil Lee Korea Advanced Institute of Science & Technology,

Korea (Member since 2018)Longbing Cao Advanced Analytics Institute,

University of Technology, Sydney, Australia(Member since 2013, Treasurer since 2018)

Jian Pei School of Computing Science,Simon Fraser University (Member since 2013)

Vincent S. Tseng National Cheng Kung University,Taiwan (Member since 2014)

Gill Dobbie University of Auckland,New Zealand (Member since 2016)

Kyuseok Shim Seoul National University, Korea (Member since 2017)

Life Members

P. Krishna Reddy International Institute of Information Technology,Hyderabad (IIIT-H), India (Member since 2010,Life Member since 2018)

Joshua Z. Huang Shenzhen University, China (Member since 2011,Life Member since 2018)

Ee-Peng Lim Singapore Management University, Singapore(Member since 2006, Life Member since 2014,Co-chair 2015–2017, Chair 2018–2020)

Hiroshi Motoda AFOSR/AOARD and Osaka University, Japan(Member since 1997, Co-chair 2001–2003,Chair 2004–2006, Life Member since 2006)

x Organization

Rao Kotagiri University of Melbourne, Australia (Member since1997, Co-chair 2006–2008, Chair 2009–2011,Life Member since 2007, Co-sign since 2006)

Huan Liu Arizona State University, USA (Member since 1998,Treasurer 1998–2000, Life Member since 2012)

Ning Zhong Maebashi Institute of Technology,Japan (Member since 1999, Life Membersince 2008)

Masaru Kitsuregawa Tokyo University, Japan (Member since 2000,Life Member since 2008)

David Cheung University of Hong Kong, SAR China (Member since2001, Treasurer 2005–2006, Chair 2006–2008,Life Member since 2009)

Graham Williams Australian National University, Australia(Member since 2001, Treasurer 2006–2017, Co-signsince 2006, Co-chair 2009–2011, Chair 2012–2014,Life Member since 2009)

Ming-Syan Chen National Taiwan University, Taiwan (Member since2002, Life Member since 2010)

Kyu-Young Whang Korea Advanced Institute of Science & Technology,Korea (Member since 2003, Life Membersince 2011)

Chengqi Zhang University of Technology Sydney, Australia(Member since 2004, Life Member since 2012)

Tu Bao Ho Japan Advanced Institute of Science and Technology,Japan (Member since 2005, Co-chair 2012–2014,Chair 2015–2017, Life Member since 2013)

Zhi-Hua Zhou Nanjing University, China (Member since 2007,Life Member since 2015)

Jaideep Srivastava University of Minnesota, USA (Member since 2006,Life Member since 2015)

Takashi Washio Institute of Scientific and Industrial Research, OsakaUniversity (Member since 2008, Life Member since2016, Co-chair 2018–2020)

Thanaruk Theeramunkong Thammasat University, Thailand (Member since 2009,Life Member since 2017)

Past Members

Hongjun Lu Hong Kong University of Science and Technology,SAR China (Member 1997–2005)

Arbee L. P. Chen National Chengchi University,Taiwan (Member 2002–2009)

Takao Terano Tokyo Institute of Technology,Japan (Member 2000–2009)

Organization xi

Tru Hoang Cao Ho Chi Minh City University of Technology,Vietnam (Member 2015–2017)

Myra Spiliopoulou Information Systems, Otto-von-Guericke-UniversityMagdeburg (Member 2013–2019)

Senior Program Committee

James Bailey University of Melbourne, AustraliaAlbert Bifet Telecom ParisTech, FranceLongbin Cao University of Technology Sydney, AustraliaTru Cao Ho Chi Minh City University of Technology, VietnamPeter Christen Australian National University, AustraliaPeng Cui Tsinghua University, ChinaGuozhu Dong Wright State University, USABenjamin C. M. Fung McGill University, CanadaBart Goethals University of Antwerp, BelgiumGeoff Holmes University of Waikato, New ZealandQinghua Hu Tianjin University, ChinaXia Hu Texas A&M University, USASheng-Jun Huang Nanjing University of Aeronautics and Astronautics,

ChinaShuiwang Ji Texas A&M University, USAKamalakar Karlapalem IIIT Hyderabad, IndiaGeorge Karypis University of Minnesota, USALatifur Khan University of Texas at Dallas, USAByung S. Lee University of Vermont, USAJae-Gil Lee KAIST, KoreaGang Li Deakin University, AustraliaJiuyong Li University of South Australia, AustraliaMing Li Nanjing University, ChinaYu-Feng Li Nanjing University, ChinaShou-De Lin National Taiwan University, TaiwanQi Liu University of Science and Technology of China, ChinaWeiwei Liu University of New South Wales, AustraliaNikos Mamoulis University of Ioannina, GreeceWee Keong Ng Nanyang Technological University, SingaporeSinno Pan Nanyang Technological University, SingaporeJian Pei Simon Fraser University, CanadaWen-Chih Peng National Chiao Tung University, TaiwanRajeev Raman University of Leicester, UKChandan K. Reddy Virginia Tech, USAKrishna P. Reddy IIIT Hyderabad, IndiaKyuseok Shim Seoul National University, KoreaMyra Spiliopoulou Otto-von-Guericke-University Magdeburg, GermanyMasashi Sugiyama RIKEN/The University of Tokyo, JapanJiliang Tang Michigan State University, USA

xii Organization

Kai Ming Ting Federation University, AustraliaHanghang Tong Arizona State University, USAVincent S. Tseng National Chiao Tung University, TaiwanFei Wang Cornell University, USAJianyong Wang Tsinghua University, ChinaJie Wang University of Science and Technology of China, ChinaWei Wang University of California at Los Angeles, USATakashi Washio Osaka University, JapanJia Wu Macquarie University, AustraliaXindong Wu Mininglamp Software Systems, ChinaXintao Wu University of Arkansas, USAXing Xie Microsoft Research Asia, ChinaJeffrey Xu Yu Chinese University of Hong Kong, SAR ChinaOsmar R. Zaiane University of Alberta, CanadaZhao Zhang Soochow University, ChinaFeida Zhu Singapore Management University, SingaporeFuzhen Zhuang Institute of Computing Technology, CAS, China

Program Committee

Saurav Acharya University of Vermont, USASwati Agarwal BITS Pilani Goa, IndiaDavid Albrecht Monash University, AustraliaDavid Anastasiu San Jose State University, USALuiza Antonie University of Guelph, CanadaXiang Ao Institute of Computing Technology, CAS, ChinaSunil Aryal Deakin University, AustraliaElena Baralis Politecnico di Torino, ItalyJean Paul Barddal Pontifícia Universidade Católica do Paraná, BrazilArnab Basu Indian Institute of Management Bangalore, IndiaGustavo Batista Universidade de São Paulo, BrazilBettina Berendt KU Leuven, BelgiumRaj K. Bhatnagar University of Cincinnati, USAArnab Bhattacharya Indian Institute of Technology, Kanpur, IndiaKevin Bouchard Université du Quebec a Chicoutimi, CanadaKrisztian Buza Eotvos Lorand University, HungaryLei Cai Washington State University, USARui Camacho Universidade do Porto, PortugalK. Selcuk Candan Arizona State University, USATanmoy Chakraborty Indraprastha Institute of Information Technology Delhi,

IndiaShama Chakravarthy University of Texas at Arlington, USAKeith Chan Hong Kong Polytechnic University, SAR ChinaChia Hui Chang National Central University, TaiwanBo Chen Monash University, AustraliaChun-Hao Chen Tamkang University, Taiwan

Organization xiii

Lei Chen Nanjing University of Posts and Telecommunications,China

Meng Chang Chen Academia Sinica, TaiwanRui Chen Samsung Research America, USAShu-Ching Chen Florida International University, USASongcan Chen Nanjing University of Aeronautics and Astronautics,

ChinaYi-Ping Phoebe Chen La Trobe University, AustraliaYi-Shin Chen National Tsing Hua University, TaiwanZhiyuan Chen University of Maryland Baltimore County, USAJiefeng Cheng Tencent Cloud Security Lab, ChinaYiu-ming Cheung Hong Kong Baptist University, SAR ChinaSilvia Chiusano Politecnico di Torino, ItalyJaegul Choo Korea University, KoreaKun-Ta Chuang National Cheng Kung University, TaiwanBruno Cremilleux Université de Caen Normandie, FranceChaoran Cui Shandong University of Finance and Economics, ChinaLin Cui Nanjing University of Aeronautics and Astronautics,

ChinaBoris Cule University of Antwerp, BelgiumBing Tian Dai Singapore Management University, SingaporeDao-Qing Dai Sun Yat-Sen University, ChinaWang-Zhou Dai Nanjing University, ChinaXuan-Hong Dang IBM T.J. Watson Research Center, USAJeremiah Deng University of Otago, New ZealandZhaohong Deng Jiangnan University, ChinaLipika Dey Tata Consultancy Services, IndiaBolin Ding Data Analytics and Intelligence Lab, Alibaba Group,

ChinaSteven H. H. Ding McGill University, CanadaTrong Dinh Thac Do University of Technology Sydney, AustraliaGillian Dobbie University of Auckland, New ZealandXiangjun Dong Qilu University of Technology, ChinaDejing Dou University of Oregon, USABo Du Wuhan University, ChinaBoxin Du Arizona State University, USALei Duan Sichuan University, ChinaSarah Erfani University of Melbourne, AustraliaVladimir Estivill-Castro Griffith University, AustraliaXuhui Fan University of Technology Sydney, AustraliaRizal Fathony University of Illinois at Chicago, USAPhilippe Fournier-Viger Harbin Institute of Technology (Shenzhen), ChinaYanjie Fu Missouri University of Science and Technology, USADragan Gamberger Rudjer Boskovic Institute, CroatiaNiloy Ganguly Indian Institute of Technology Kharagpur, IndiaJunbin Gao University of Sydney, Australia

xiv Organization

Wei Gao Nanjing University, ChinaXiaoying Gao Victoria University of Wellington, New ZealandAngelo Genovese Università degli Studi di Milano, ItalyArnaud Giacometti University Francois Rabelais of Tours, FranceHeitor M. Gomes Telecom ParisTech, FranceChen Gong Nanjing University of Science and Technology, ChinaMaciej Grzenda Warsaw University of Technology, PolandLei Gu Nanjing University of Posts and Telecommunications,

ChinaYong Guan Iowa State University, USAHimanshu Gupta IBM Research, IndiaSunil Gupta Deakin University, AustraliaMichael Hahsler Southern Methodist University, USAYahong Han Tianjin University, ChinaSatoshi Hara Osaka University, JapanChoochart Haruechaiyasak National Electronics and Computer Technology Center,

ThailandJingrui He Arizona State University, USAShoji Hirano Shimane University, JapanTuan-Anh Hoang Leibniz University of Hanover, GermanyJaakko Hollmén Aalto University, FinlandTzung-Pei Hong National University of Kaohsiung, TaiwanChenping Hou National University of Defense Technology, ChinaMichael E. Houle National Institute of Informatics, JapanHsun-Ping Hsieh National Cheng Kung University, TaiwanEn-Liang Hu Yunnan Normal University, ChinaJuhua Hu University of Washington Tacoma, USALiang Hu University of Technology Sydney, AustraliaWenbin Hu Wuhan University, ChinaChao Huang University of Notre Dame, USADavid Tse Jung Huang University of Auckland, New ZealandJen-Wei Huang National Cheng Kung University, TaiwanNam Huynh Japan Advanced Institute of Science and Technology,

JapanAkihiro Inokuchi Kwansei Gakuin University, JapanDivyesh Jadav IBM Research, USASanjay Jain National University of Singapore, SingaporeSzymon Jaroszewicz Polish Academy of Sciences, PolandSonglei Jian University of Technology Sydney, AustraliaMeng Jiang University of Notre Dame, USABo Jin Dalian University of Technology, ChinaToshihiro Kamishima National Institute of Advanced Industrial Science

and Technology, JapanWei Kang University of South Australia, AustraliaMurat Kantarcioglu University of Texas at Dallas, USAHung-Yu Kao National Cheng Kung University, Taiwan

Organization xv

Shanika Karunasekera University of Melbourne, AustraliaMakoto P. Kato Kyoto University, JapanChulyun Kim Sookmyung Women University, KoreaJungeun Kim Korea Advanced Institute of Science and Technology,

KoreaKyoung-Sook Kim Artificial Intelligence Research Center, JapanYun Sing Koh University of Auckland, New ZealandXiangnan Kong Worcester Polytechnic Institute, USAIrena Koprinska University of Sydney, AustraliaRavi Kothari Ashoka University, IndiaP. Radha Krishna National Institute of Technology, Warangal, IndiaRaghu Krishnapuram Indian Institute of Science Bangalore, IndiaMarzena Kryszkiewicz Warsaw University of Technology, PolandChao Lan University of Wyoming, USAHady Lauw Singapore Management University, SingaporeThuc Duy Le University of South Australia, AustraliaIckjai J. Lee James Cook University, AustraliaJongwuk Lee Sungkyunkwan University, KoreaKi Yong Lee Sookmyung Women’s University, KoreaKi-Hoon Lee Kwangwoon University, KoreaSael Lee Seoul National University, KoreaSangkeun Lee Korea University, KoreaSunhwan Lee IBM Research, USAVincent C. S. Lee Monash University, AustraliaWang-Chien Lee Pennsylvania State University, USAYue-Shi Lee Ming Chuan University, TaiwanZhang Lei Anhui University, ChinaCarson K. Leung University of Manitoba, CanadaBohan Li Nanjing University of Aeronautics and Astronautics,

ChinaJianmin Li Tsinghua University, ChinaJianxin Li Deakin University, AustraliaJundong Li Arizona State University, USANan Li Alibaba, ChinaPeipei Li Hefei University of Technology, ChinaQian Li University of Technology Sydney, AustraliaRong-Hua Li Beijing Institute of Technology, ChinaShao-Yuan Li Nanjing University, ChinaSheng Li University of Georgia, USAWenyuan Li University of California, Los Angeles, USAWu-Jun Li Nanjing University, ChinaXiaoli Li Institute for Infocomm Research, A*STAR, SingaporeXue Li University of Queensland, AustraliaYidong Li Beijing Jiaotong University, ChinaZhixu Li Soochow University, China

xvi Organization

Defu Lian University of Electronic Science and Technologyof China, China

Sungsu Lim Chungnam National University, KoreaChunbin Lin Amazon AWS, USAHsuan-Tien Lin National Taiwan University, TaiwanJerry Chun-Wei Lin Western Norway University of Applied Sciences,

NorwayAnqi Liu California Institute of Technology, USABin Liu IBM Research, USAJiajun Liu Renmin University of China, ChinaJiamou Liu University of Auckland, New ZealandJie Liu Nankai University, ChinaLin Liu University of South Australia, AustraliaLiping Liu Tufts University, USAShaowu Liu University of Technology Sydney, AustraliaZheng Liu Nanjing University of Posts and Telecommunications,

ChinaWenpeng Lu Qilu University of Technology, ChinaJun Luo Machine Intelligence Lab, Lenovo Group Limited,

ChinaWei Luo Deakin University, AustraliaHuifang Ma Northwest Normal University, ChinaMarco Maggini University of Siena, ItalyGiuseppe Manco ICAR-CNR, ItalySilviu Maniu Universite Paris-Sud, FranceNaresh Manwani International Institute of Information Technology,

Hyderabad, IndiaFlorent Masseglia Inria, FranceTomoko Matsui Institute of Statistical Mathematics, JapanMichael Mayo The University of Waikato, New ZealandStephen McCloskey The University of Sydney, AustraliaErnestina Menasalvas Universidad Politécnica de Madrid, SpainXiangfu Meng Liaoning Technical University, ChinaXiaofeng Meng Renmin University of China, ChinaJun-Ki Min Korea University of Technology and Education, KoreaNguyen Le Minh Japan Advanced Institute of Science and Technology,

JapanLeandro Minku The University of Birmingham, UKPabitra Mitra Indian Institute of Technology Kharagpur, IndiaAnirban Mondal Ashoka University, IndiaTaesup Moon Sungkyunkwan University, KoreaYang-Sae Moon Kangwon National University, KoreaYasuhiko Morimoto Hiroshima University, JapanAnimesh Mukherjee Indian Institute of Technology Kharagpur, IndiaMiyuki Nakano Advanced Institute of Industrial Technology, JapanMirco Nanni ISTI-CNR, Italy

Organization xvii

Richi Nayak Queensland University of Technology, AustraliaRaymond Ng University of British Columbia, CanadaWilfred Ng Hong Kong University of Science and Technology,

SAR ChinaCam-Tu Nguyen Nanjing University, ChinaHao Canh Nguyen Kyoto University, JapanNgoc-Thanh Nguyen Wroclaw University of Science and Technology,

PolandQuoc Viet Hung Nguyen Griffith University, AustraliaArun Reddy Nelakurthi Arizona State University, USAThanh Nguyen Deakin University, AustraliaThin Nguyen Deakin University, AustraliaAthanasios Nikolakopoulos University of Minnesota, USATadashi Nomoto National Institute of Japanese Literature, JapanEirini Ntoutsi Leibniz University of Hanover, GermanyKouzou Ohara Aoyama Gakuin University, JapanKok-Leong Ong La Trobe University, AustraliaShirui Pan University of Technology Sydney, AustraliaYuangang Pan University of Technology Sydney, AustraliaGuansong Pang University of Adelaide, AustraliaDhaval Patel IBM T.J. Watson Research Center, USAFrancois Petitjean Monash University, AustraliaHai Nhat Phan New Jersey Institute of Technology, USAXuan-Hieu Phan University of Engineering and Technology, VNUHN,

VietnamVincenzo Piuri Università degli Studi di Milano, ItalyVikram Pudi International Institute of Information Technology,

Hyderabad, IndiaChao Qian University of Science and Technology of China, ChinaQi Qian Alibaba Group, ChinaTang Qiang Luxembourg Institute of Science and Technology,

LuxembourgBiao Qin Renmin University of China, ChinaJie Qin Eidgenössische Technische Hochschule Zürich,

SwitzerlandTho Quan Ho Chi Minh City University of Technology, VietnamUday Kiran Rage University of Tokyo, JapanChedy Raissi Inria, FranceVaibhav Rajan National University of Singapore, SingaporeSantu Rana Deakin University, AustraliaThilina N. Ranbaduge Australian National University, AustraliaPatricia Riddle University of Auckland, New ZealandHiroshi Sakamoto Kyushu Institute of Technology, JapanYücel Saygin Sabanci University, TurkeyMohit Sharma Walmart Labs, USAHong Shen Adelaide University, Australia

xviii Organization

Wei Shen Nankai University, ChinaXiaobo Shen Nanjing University of Science and Technology, ChinaVictor S. Sheng University of Central Arkansas, USAChuan Shi Beijing University of Posts and Telecommunications,

ChinaMotoki Shiga Gifu University, JapanHiroaki Shiokawa University of Tsukuba, JapanMoumita Sinha Adobe, USAAndrzej Skowron University of Warsaw, PolandYang Song University of New South Wales, AustraliaArnaud Soulet University of Tours, FranceSrinath Srinivasa International Institute of Information Technology,

Bangalore, IndiaFabio Stella University of Milan-Bicocca, ItalyPaul Suganthan University of Wisconsin-Madison, USAMahito Sugiyama National Institute of Informatics, JapanGuangzhong Sun University of Science and Technology of China, ChinaYuqing Sun Shandong University, ChinaIchigaku Takigawa Hokkaido University, JapanMingkui Tan South China University of Technology, ChinaMing Tang Institute of Automation, CAS, ChinaQiang Tang Luxembourg Institute of Science and Technology,

LuxembourgDavid Taniar Monash University, AustraliaXiaohui (Daniel) Tao University of Southern Queensland, AustraliaVahid Taslimitehrani PhysioSigns Inc., USAMaguelonne Teisseire Irstea, FranceKhoat Than Hanoi University of Science and Technology, VietnamLini Thomas International Institute of Information Technology,

Hyderabad, IndiaHiroyuki Toda NTT Corporation, JapanSon Tran New Mexico State University, USAAllan Tucker Brunel University London, UKJeffrey Ullman Stanford University, USADinusha Vatsalan Data61, CSIRO, AustraliaRanga Vatsavai North Carolina State University, USAJoao Vinagre LIAAD—INESC TEC, PortugalBay Vo Ho Chi Minh City University of Technology, VietnamKitsana Waiyamai Kasetsart University, ThailandCan Wang Griffith University, AustraliaChih-Yu Wang Academia Sinica, TaiwanHongtao Wang North China Electric Power University, ChinaJason T. L. Wang New Jersey Institute of Technology, USALizhen Wang Yunnan University, ChinaPeng Wang Southeast University, ChinaQing Wang Australian National University, Australia

Organization xix

Shoujin Wang Macquarie University, AustraliaSibo Wang Chinese University of Hong Kong, SAR ChinaSuhang Wang Pennsylvania State University, USAWei Wang University of New South Wales, AustraliaWei Wang Nanjing University, ChinaWeiqing Wang Monash University, AustraliaWendy Hui Wang Stevens Institute of Technology, USAWenya Wang Nanyang Technological University, SingaporeXiao Wang Beijing University of Posts and Telecommunications,

ChinaXiaoyang Wang Zhejiang Gongshang University, ChinaXin Wang University of Calgary, CanadaXiting Wang Microsoft Research Asia, ChinaYang Wang Dalian University of Technology, ChinaYue Wang AcuSys, USAZhengyang Wang Texas A&M University, USAZhichao Wang University of Technology Sydney, AustraliaLijie Wen Tsinghua University, ChinaJorg Wicker University of Auckland, New ZealandKishan Wimalawarne Kyoto University, JapanRaymond Chi-Wing Wong Hong Kong University of Science and Technology,

SAR ChinaBrendon J. Woodford University of Otago, New ZealandFangzhao Wu Microsoft Research Asia, ChinaHuifeng Wu Hangzhou Dianzi University, ChinaLe Wu Hefei University of Technology, ChinaLiang Wu Arizona State University, USALin Wu University of Queensland, AustraliaOu Wu Tianjin University, ChinaQingyao Wu South China University of Technology, ChinaShu Wu Institute of Automation, CAS, ChinaYongkai Wu University of Arkansas, USAYuni Xia Indiana University—Purdue University Indianapolis

(IUPUI), USACongfu Xu Zhejiang University, ChinaGuandong Xu University of Technology Sydney, AustraliaJingwei Xu Nanjing University, ChinaLinli Xu University of Science and Technology China, ChinaMiao Xu RIKEN, JapanTong Xu University of Science and Technology of China, ChinaBing Xue Victoria University of Wellington, New ZealandHui Xue Southeast University, ChinaShan Xue University of Technology Sydney, AustraliaPranjul Yadav Criteo, FranceTakehisa Yairi University of Tokyo, JapanTakehiro Yamamoto Kyoto University, Japan

xx Organization

Chun-Pai Yang National Taiwan University, TaiwanDe-Nian Yang Academia Sinica, TaiwanGuolei Yang Facebook, USAJingyuan Yang George Mason University, USALiu Yang Tianjin University, ChinaMing Yang Nanjing Normal University, ChinaShiyu Yang East China Normal University, ChinaYiyang Yang Guangdong University of Technology, ChinaLina Yao University of New South Wales, AustraliaYuan Yao Nanjing University, ChinaZijun Yao IBM Research, USAMi-Yen Yeh Academia Sinica, Taiwanfeng Yi Institute of Information Engineering, CAS, ChinaHongzhi Yin University of Queensland, AustraliaJianhua Yin Shandong University, ChinaMinghao Yin Northeast Normal University, ChinaTetsuya Yoshida Nara Women’s University, JapanGuoxian Yu Southwest University, ChinaKui Yu Hefei University of Technology, ChinaYang Yu Nanjing University, ChinaLong Yuan University of New South Wales, AustraliaShuhan Yuan University of Arkansas, USAXiaodong Yue Shanghai University, ChinaReza Zafarani Syracuse University, USANayyar Zaidi Monash University, AustraliaYifeng Zeng Teesside University, UKDe-Chuan Zhan Nanjing University, ChinaDaoqiang Zhang Nanjing University of Aeronautics and Astronautics,

ChinaDu Zhang California State University, Sacramento, USAHaijun Zhang Harbin Institute of Technology (Shenzhen), ChinaJing Zhang Nanjing University of Science and Technology, ChinaLu Zhang University of Arkansas, USAMengjie Zhang Victoria University of Wellington, New ZealandQuangui Zhang Liaoning Technical University, ChinaSi Zhang Arizona State University, USAWei Emma Zhang Macquarie University, AustraliaWei Zhang East China Normal University, ChinaWenjie Zhang University of New South Wales, AustraliaXiangliang Zhang King Abdullah University of Science and Technology,

Saudi ArabiaXiuzhen Zhang RMIT University, AustraliaYudong Zhang University of Leicester, UKZheng Zhang University of Queensland, AustraliaZili Zhang Southwest University, ChinaMingbo Zhao Donghua University, China

Organization xxi

Peixiang Zhao Florida State University, USAPengpeng Zhao Soochow University, ChinaYanchang Zhao CSIRO, AustraliaZhongying Zhao Shandong University of Science and Technology,

ChinaZhou Zhao Zhejiang University, ChinaHuiyu Zhou University of Leicester, UKShuigeng Zhou Fudan University, ChinaXiangmin Zhou RMIT University, AustraliaYao Zhou Arizona State University, USAChengzhang Zhu University of Technology Sydney, AustraliaHuafei Zhu Nanyang Technological University, SingaporePengfei Zhu Tianjin University, ChinaTianqing Zhu University of Technology Sydney, AustraliaXingquan Zhu Florida Atlantic University, USAYe Zhu Deakin University, AustraliaYuanyuan Zhu Wuhan University, ChinaArthur Zimek University of Southern Denmark, DenmarkAlbrecht Zimmermann Université de Caen Normandie, France

External Reviewers

Ji FengXuan HuoBin-Bin JiaZhi-Yu ShenYanping SunXuan Wu

Zheng-Fan WuYafu XiaoYang YangMeimei YangHan-Jia YePeng Zhao

xxii Organization

Sponsoring Organizations

University of Macau

Macao Convention & Exhibition Association

Intel

Baidu Inc.

Organization xxiii

Contents – Part I

Classification and Supervised Learning

Multitask Learning for Sparse Failure Prediction . . . . . . . . . . . . . . . . . . . . . 3Simon Luo, Victor W. Chu, Zhidong Li, Yang Wang, Jianlong Zhou,Fang Chen, and Raymond K. Wong

Cost Sensitive Learning in the Presence of Symmetric Label Noise . . . . . . . . 15Sandhya Tripathi and Nandyala Hemachandra

Semantic Explanations in Ensemble Learning . . . . . . . . . . . . . . . . . . . . . . . 29Md. Zahidul Islam, Jixue Liu, Lin Liu, Jiuyong Li, and Wei Kang

Latent Gaussian-Multinomial Generative Model for Annotated Data . . . . . . . 42Shuoran Jiang, Yarui Chen, Zhifei Qin, Jucheng Yang, Tingting Zhao,and Chuanlei Zhang

Investigating Neighborhood Generation Methods for Explanationsof Obscure Image Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Riccardo Guidotti, Anna Monreale, and Leonardo Cariaggi

On Calibration of Nested Dichotomies. . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Tim Leathart, Eibe Frank, Bernhard Pfahringer, and Geoffrey Holmes

Ensembles of Nested Dichotomies with Multiple Subset Evaluation. . . . . . . . 81Tim Leathart, Eibe Frank, Bernhard Pfahringer, and Geoffrey Holmes

Text and Opinion Mining

Topic-Level Bursty Study for Bursty Topic Detection in Microblogs . . . . . . . 97Yakun Wang, Zhongbao Zhang, Sen Su, and Muhammad Azam Zia

Adaptively Transfer Category-Classifier for Handwritten ChineseCharacter Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

Yongchun Zhu, Fuzhen Zhuang, Jingyuan Yang, Xi Yang, and Qing He

Syntax-Aware Representation for Aspect Term Extraction . . . . . . . . . . . . . . 123Jingyuan Zhang, Guangluan Xu, Xinyi Wang, Xian Sun,and Tinglei Huang

Short Text Similarity Measurement Based on Coupled Semantic Relationand Strong Classification Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

Huifang Ma, Wen Liu, Zhixin Li, and Xianghong Lin

A Novel Hybrid Sequential Model for Review-Based Rating Prediction . . . . . 148Yuanquan Lu, Wei Zhang, Pan Lu, and Jianyong Wang

Integrating Topic Model and Heterogeneous Information Networkfor Aspect Mining with Rating Bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

Yugang Ji, Chuan Shi, Fuzhen Zhuang, and Philip S. Yu

Dependency-Aware Attention Model for Emotion Analysisfor Online News . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172

Xue Zhao, Ying Zhang, and Xiaojie Yuan

Multi-task Learning for Target-Dependent Sentiment Classification . . . . . . . . 185Divam Gupta, Kushagra Singh, Soumen Chakrabarti,and Tanmoy Chakraborty

SC-NER: A Sequence-to-Sequence Model with Sentence Classificationfor Named Entity Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198

Yu Wang, Yun Li, Ziye Zhu, Bin Xia, and Zheng Liu

BAB-QA: A New Neural Model for Emotion Detectionin Multi-party Dialogue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210

Zilong Wang, Zhaohong Wan, and Xiaojun Wan

Unsupervised User Behavior Representation for Fraud Review Detectionwith Cold-Start Problem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

Qian Li, Qiang Wu, Chengzhang Zhu, Jian Zhang, and Wentao Zhao

Gated Convolutional Encoder-Decoder for Semi-supervisedAffect Prediction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

Kushal Chawla, Sopan Khosla, and Niyati Chhaya

Complaint Classification Using Hybrid-Attention GRU Neural Network. . . . . 251Shuyang Wang, Bin Wu, Bai Wang, and Xuesong Tong

Spatio-Temporal and Stream Data Mining

FGST: Fine-Grained Spatial-Temporal Based Regression for StationlessBike Traffic Prediction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265

Hao Chen, Senzhang Wang, Zengde Deng, Xiaoming Zhang,and Zhoujun Li

Customer Segmentation Based on Transactional Data UsingStream Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280

Matthias Carnein and Heike Trautmann

Spatio-Temporal Event Detection from Multiple Data Sources . . . . . . . . . . . 293Aman Ahuja, Ashish Baghudana, Wei Lu, Edward A. Fox,and Chandan K. Reddy

xxvi Contents – Part I

Discovering All-Chain Set in Streaming Time Series . . . . . . . . . . . . . . . . . . 306Shaopeng Wang, Ye Yuan, and Hua Li

Hawkes Process with Stochastic Triggering Kernel . . . . . . . . . . . . . . . . . . . 319Feng Zhou, Yixuan Zhang, Zhidong Li, Xuhui Fan, Yang Wang,Arcot Sowmya, and Fang Chen

Concept Drift Based Multi-dimensional Data Streams Sampling Method . . . . 331Ling Lin, Xiaolong Qi, Zhirui Zhu, and Yang Gao

Spatial-Temporal Multi-Task Learning for Within-Field CottonYield Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343

Long H. Nguyen, Jiazhen Zhu, Zhe Lin, Hanxiang Du, Zhou Yang,Wenxuan Guo, and Fang Jin

Factor and Tensor Analysis

Online Data Fusion Using Incremental Tensor Learning. . . . . . . . . . . . . . . . 357Nguyen Lu Dang Khoa, Hongda Tian, Yang Wang, and Fang Chen

Co-clustering from Tensor Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 370Rafika Boutalbi, Lazhar Labiod, and Mohamed Nadif

A Data-Aware Latent Factor Model for Web Service QoS Prediction . . . . . . 384Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang,and Xindong Wu

Keyword Extraction with Character-Level Convolutional NeuralTensor Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400

Zhe-Li Lin and Chuan-Ju Wang

Neural Variational Matrix Factorization with Side Informationfor Collaborative Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414

Teng Xiao and Hong Shen

Variational Deep Collaborative Matrix Factorizationfor Social Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426

Teng Xiao, Hui Tian, and Hong Shen

Healthcare, Bioinformatics and Related Topics

Time-Dependent Survival Neural Network for Remaining UsefulLife Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441

Jianfei Zhang, Shengrui Wang, Lifei Chen, Gongde Guo, Rongbo Chen,and Alain Vanasse

Contents – Part I xxvii

ACNet: Aggregated Channels Network for Automated Mitosis Detection . . . . 453Kaili Cheng, Jiarui Sun, Xuesong Chen, Yanbo Ma, Mengjie Bai,and Yong Zhao

Attention-Based Hierarchical Recurrent Neural Networkfor Phenotype Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465

Nan Xu, Yanyan Shen, and Yanmin Zhu

Identifying Mobility of Drug Addicts with Multilevel Spatial-TemporalConvolutional Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477

Canghong Jin, Haoqiang Liang, Dongkai Chen, Zhiwei Lin,and Minghui Wu

MC-eLDA: Towards Pathogenesis Analysis in Traditional ChineseMedicine by Multi-Content Embedding LDA . . . . . . . . . . . . . . . . . . . . . . . 489

Ying Zhang, Wendi Ji, Haofen Wang, Xiaoling Wang, and Jin Chen

Enhancing the Healthcare Retrieval with a Self-adaptive SaturatedDensity Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501

Yang Song, Wenxin Hu, Liang He, and Liang Dou

CytoFA: Automated Gating of Mass Cytometry Data via Robust SkewFactor Analzyers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514

Sharon X. Lee

Clustering and Anomaly Detection

Consensus Graph Learning for Incomplete Multi-view Clustering . . . . . . . . . 529Wei Zhou, Hao Wang, and Yan Yang

Beyond Outliers and on to Micro-clusters: Vision-GuidedAnomaly Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541

Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi,Huawei Shen, and Xueqi Cheng

Clustering of Mixed-Type Data Considering Concept Hierarchies . . . . . . . . . 555Sahar Behzadi, Nikola S. Müller, Claudia Plant, and Christian Böhm

DMNAED: A Novel Framework Based on Dynamic Memory Networkfor Abnormal Event Detection in Enterprise Networks . . . . . . . . . . . . . . . . . 574

Xueshuang Ren and Liming Wang

NeoLOD: A Novel Generalized Coupled Local Outlier Detection ModelEmbedded Non-IID Similarity Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . 587

Fan Meng, Yang Gao, Jing Huo, Xiaolong Qi, and Shichao Yi

xxviii Contents – Part I

Dynamic Anomaly Detection Using Vector Autoregressive Model . . . . . . . . 600Yuemeng Li, Aidong Lu, Xintao Wu, and Shuhan Yuan

A Convergent Differentially Private k-Means Clustering Algorithm . . . . . . . . 612Zhigang Lu and Hong Shen

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625

Contents – Part I xxix

Contents – Part II

Deep Learning Models and Applications

Semi-interactive Attention Network for Answer Understandingin Reverse-QA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Qing Yin, Guan Luo, Xiaodong Zhu, Qinghua Hu, and Ou Wu

Neural Network Based Popularity Prediction by Linking Online Contentwith Knowledge Bases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Wayne Xin Zhao, Hongjian Dou, Yuanpei Zhao, Daxiang Dong,and Ji-Rong Wen

Passenger Demand Forecasting with Multi-Task Convolutional RecurrentNeural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Lei Bai, Lina Yao, Salil S. Kanhere, Zheng Yang, Jing Chu,and Xianzhi Wang

Accurate Identification of Electrical Equipment from Power Load Profiles . . . 43Ziyi Wang, Chun Li, and Lin Shang

Similarity-Aware Deep Attentive Model for Clickbait Detection . . . . . . . . . . 56Manqing Dong, Lina Yao, Xianzhi Wang, Boualem Benatallah,and Chaoran Huang

Topic Attentional Neural Network for AbstractiveDocument Summarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Hao Liu, Hai-Tao Zheng, and Wei Wang

Parameter Transfer Unit for Deep Neural Networks . . . . . . . . . . . . . . . . . . . 82Yinghua Zhang, Yu Zhang, and Qiang Yang

EFCNN: A Restricted Convolutional Neural Network for Expert Finding. . . . 96Yifeng Zhao, Jie Tang, and Zhengxiao Du

CRESA: A Deep Learning Approach to Competing Risks, Recurrent EventSurvival Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

Garima Gupta, Vishal Sunder, Ranjitha Prasad, and Gautam Shroff

Long-Term Traffic Time Prediction Using Deep Learning with Integrationof Weather Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

Chih-Hsin Chou, Yu Huang, Chian-Yun Huang, and Vincent S. Tseng

Arrhythmias Classification by Integrating Stacked Bidirectional LSTMand Two-Dimensional CNN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

Fan Liu, Xingshe Zhou, Jinli Cao, Zhu Wang, Hua Wang,and Yanchun Zhang

An Efficient and Resource-Aware Hashtag Recommendation Using DeepNeural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

David Kao, Kuan-Ting Lai, and Ming-Syan Chen

Dynamic Student Classiffication on Memory Networksfor Knowledge Tracing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163

Sein Minn, Michel C. Desmarais, Feida Zhu, Jing Xiao,and Jianzong Wang

Targeted Knowledge Transfer for Learning Traffic Signal Plans . . . . . . . . . . 175Nan Xu, Guanjie Zheng, Kai Xu, Yanmin Zhu, and Zhenhui Li

Sequential Pattern Mining

Efficiently Finding High Utility-Frequent Itemsets Using Cutoffand Suffix Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191

R. Uday Kiran, T. Yashwanth Reddy, Philippe Fournier-Viger,Masashi Toyoda, P. Krishna Reddy, and Masaru Kitsuregawa

How Much Can A Retailer Sell? Sales Forecasting on Tmall . . . . . . . . . . . . 204Chaochao Chen, Ziqi Liu, Jun Zhou, Xiaolong Li, Yuan Qi, Yujing Jiao,and Xingyu Zhong

Hierarchical LSTM: Modeling Temporal Dynamics and Taxonomyin Location-Based Mobile Check-Ins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217

Chun-Hao Liu, Da-Cheng Juan, Xuan-An Tseng, Wei Wei,Yu-Ting Chen, Jia-Yu Pan, and Shih-Chieh Chang

Recovering DTW Distance Between Noise Superposed NHPP . . . . . . . . . . . 229Yongzhe Chang, Zhidong Li, Bang Zhang, Ling Luo, Arcot Sowmya,Yang Wang, and Fang Chen

ATNet: Answering Cloze-Style Questions via Intra-attentionand Inter-attention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242

Chengzhen Fu, Yuntao Li, and Yan Zhang

Parallel Mining of Top-k High Utility Itemsets in Spark In-MemoryComputing Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253

Chun-Han Lin, Cheng-Wei Wu, JianTao Huang, and Vincent S. Tseng

xxxii Contents – Part II

Weakly Supervised Learning

Robust Semi-supervised Multi-label Learning by TripleLow-Rank Regularization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269

Lijuan Sun, Songhe Feng, Gengyu Lyu, and Congyan Lang

Multi-class Semi-supervised Logistic I-RELIEF Feature SelectionBased on Nearest Neighbor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281

Baige Tang and Li Zhang

Effort-Aware Tri-Training for Semi-supervised Just-in-TimeDefect Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293

Wenzhou Zhang, Weiwei Li, and Xiuyi Jia

One Shot Learning with Margin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305Xianchao Zhang, Jinlong Nie, Linlin Zong, Hong Yu, and Wenxin Liang

DeepReview: Automatic Code Review Using DeepMulti-instance Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318

Heng-Yi Li, Shu-Ting Shi, Ferdian Thung, Xuan Huo, Bowen Xu,Ming Li, and David Lo

Multi-label Active Learning with Error Correcting Output Codes . . . . . . . . . 331Ningzhao Sun, Jincheng Shan, and Chenping Hou

Dynamically Weighted Multi-View Semi-Supervised Learningfor CAPTCHA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343

Congqing He, Li Peng, Yuquan Le, and Jiawei He

Recommender System

A Novel Top-N Recommendation Approach Based on ConditionalVariational Auto-Encoder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357

Bo Pang, Min Yang, and Chongjun Wang

Jaccard Coefficient-Based Bi-clustering and Fusion Recommender Systemfor Solving Data Sparsity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369

Jiangfei Cheng and Li Zhang

A Novel KNN Approach for Session-Based Recommendation . . . . . . . . . . . 381Huifeng Guo, Ruiming Tang, Yunming Ye, Feng Liu, and Yuzhou Zhang

A Contextual Bandit Approach to Personalized Online Recommendationvia Sparse Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 394

Chenyu Zhang, Hao Wang, Shangdong Yang, and Yang Gao

Heterogeneous Item Recommendation for the Air Travel Industry . . . . . . . . . 407Zhicheng He, Jie Liu, Guanghui Xu, and Yalou Huang

Contents – Part II xxxiii

A Minimax Game for Generative and Discriminative Sample Modelsfor Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 420

Zongwei Wang, Min Gao, Xinyi Wang, Junliang Yu, Junhao Wen,and Qingyu Xiong

RNE: A Scalable Network Embedding for Billion-Scale Recommendation . . . 432Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao,Jun Zhou, Xiaolong Li, and Yuan Qi

Social Network and Graph Mining

Graph Compression with Stars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449Faming Li, Zhaonian Zou, Jianzhong Li, and Yingshu Li

Neighbor-Based Link Prediction with Edge Uncertainty . . . . . . . . . . . . . . . . 462Chi Zhang and Osmar R. Zaïane

Inferring Social Bridges that Diffuse Information Across Communities . . . . . 475Pei Zhang, Ke-Jia Chen, and Tong Wu

Learning Pretopological Spaces to Extract Ego-Centered Communities. . . . . . 488Gaëtan Caillaut, Guillaume Cleuziou, and Nicolas Dugué

EigenPulse: Detecting Surges in Large Streaming Graphswith Row Augmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501

Jiabao Zhang, Shenghua Liu, Wenjian Yu, Wenjie Feng,and Xueqi Cheng

TPLP: Two-Phase Selection Link Prediction for Vertex in Graph Streams . . . 514Yang Xiao, Hong Huang, Feng Zhao, and Hai Jin

Robust Temporal Graph Clustering for Group Record Linkage . . . . . . . . . . . 526Charini Nanayakkara, Peter Christen, and Thilina Ranbaduge

Data Pre-processing and Feature Selection

Learning Diversified Features for Object Detection via Multi-regionOcclusion Example Generating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541

Junsheng Liang, Zhiqiang Li, and Hongchen Guo

HATDC: A Holistic Approach for Time Series Data Repairing . . . . . . . . . . . 553Xiaojie Liu, Guangxuan Song, and Xiaoling Wang

Double Weighted Low-Rank Representationand Its Efficient Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565

Jianwei Zheng, Kechen Lou, Ping Yang, Wanjun Chen,and Wanliang Wang

xxxiv Contents – Part II

Exploring Dual-Triangular Structure for Efficient R-Initiated Tall-SkinnyQR on GPGPU. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 578

Nai-Yun Cheng and Ming-Syan Chen

Efficient Autotuning of Hyperparameters in Approximate NearestNeighbor Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 590

Elias Jääsaari, Ville Hyvönen, and Teemu Roos

An Accelerator of Feature Selection Applying a General FuzzyRough Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603

Peng Ni, Suyun Zhao, Hong Chen, and Cuiping Li

Text Feature Extraction and Selection Based on Attention Mechanism. . . . . . 615Longxuan Ma and Lei Zhang

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629

Contents – Part II xxxv

Contents – Part III

Representation Learning and Embedding

AAANE: Attention-Based Adversarial Autoencoder for Multi-scaleNetwork Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Lei Sang, Min Xu, Shengsheng Qian, and Xindong Wu

NEAR: Normalized Network Embedding with Autoencoderfor Top-K Item Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Dedong Li, Aimin Zhou, and Chuan Shi

Ranking Network Embedding via Adversarial Learning . . . . . . . . . . . . . . . . 27Quanyu Dai, Qiang Li, Liang Zhang, and Dan Wang

Selective Training: A Strategy for Fast Backpropagationon Sentence Embeddings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Jan Neerbek, Peter Dolog, and Ira Assent

Extracting Keyphrases from Research Papers Using Word Embeddings . . . . . 54Wei Fan, Huan Liu, Suge Wang, Yuxiang Zhang, and Yaocheng Chang

Sequential Embedding Induced Text Clustering, a Non-parametricBayesian Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Tiehang Duan, Qi Lou, Sargur N. Srihari, and Xiaohui Xie

SSNE: Status Signed Network Embedding . . . . . . . . . . . . . . . . . . . . . . . . . 81Chunyu Lu, Pengfei Jiao, Hongtao Liu, Yaping Wang, Hongyan Xu,and Wenjun Wang

On the Network Embedding in Sparse Signed Networks . . . . . . . . . . . . . . . 94Ayan Kumar Bhowmick, Koushik Meneni, and Bivas Mitra

MSNE: A Novel Markov Chain Sampling Strategyfor Network Embedding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Ran Wang, Yang Song, and Xin-yu Dai

Auto-encoder Based Co-training Multi-view Representation Learning . . . . . . 119Run-kun Lu, Jian-wei Liu, Yuan-fang Wang, Hao-jie Xie, and Xin Zuo

Robust Semi-supervised Representation Learningfor Graph-Structured Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

Lan-Zhe Guo, Tao Han, and Yu-Feng Li

Characterizing the SOM Feature Detectors Under VariousInput Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144

Macario O. Cordel II and Arnulfo P. Azcarraga

PCANE: Preserving Context Attributes for Network Embedding . . . . . . . . . . 156Danhao Zhu, Xin-yu Dai, Kaijia Yang, Jiajun Chen, and Yong He

A Novel Framework for Node/Edge Attributed Graph Embedding. . . . . . . . . 169Guolei Sun and Xiangliang Zhang

Mining Unstructured and Semi-structured Data

Context-Aware Dual-Attention Network for Natural Language Inference . . . . 185Kun Zhang, Guangyi Lv, Enhong Chen, Le Wu, Qi Liu,and C. L. Philip Chen

Best from Top k Versus Top 1: Improving Distant Supervision RelationExtraction with Deep Reinforcement Learning . . . . . . . . . . . . . . . . . . . . . . 199

Yaocheng Gui, Qian Liu, Tingming Lu, and Zhiqiang Gao

Towards One Reusable Model for Various Software Defect Mining Tasks . . . 212Heng-Yi Li, Ming Li, and Zhi-Hua Zhou

User Preference-Aware Review Generation. . . . . . . . . . . . . . . . . . . . . . . . . 225Wei Wang, Hai-Tao Zheng, and Hao Liu

Mining Cluster Patterns in XML Corpora via Latent Topic Modelsof Content and Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

Gianni Costa and Riccardo Ortale

A Large-Scale Repository of Deterministic Regular Expression Patternsand Its Applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

Haiming Chen, Yeting Li, Chunmei Dong, Xinyu Chu, Xiaoying Mou,and Weidong Min

Determining the Impact of Missing Values on Blockingin Record Linkage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262

Imrul Chowdhury Anindya, Murat Kantarcioglu, and Bradley Malin

Behavioral Data Mining

Bridging the Gap Between Research and Production with CODE . . . . . . . . . 277Yiping Jin, Dittaya Wanvarie, and Phu T. V. Le

Distance2Pre: Personalized Spatial Preference for NextPoint-of-Interest Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289

Qiang Cui, Yuyuan Tang, Shu Wu, and Liang Wang

xxxviii Contents – Part III

Using Multi-objective Optimization to Solve the Long Tail Problemin Recommender System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302

Jiaona Pang, Jun Guo, and Wei Zhang

Event2Vec: Learning Event Representations Using Spatial-TemporalInformation for Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314

Yan Wang and Jie Tang

Maximizing Gain over Flexible Attributes in Peer to Peer Marketplaces. . . . . 327Abolfazl Asudeh, Azade Nazi, Nick Koudas, and Gautam Das

An Attentive Spatio-Temporal Neural Model for Successive Pointof Interest Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346

Khoa D. Doan, Guolei Yang, and Chandan K. Reddy

Mentor Pattern Identification from Product Usage Logs . . . . . . . . . . . . . . . . 359Ankur Garg, Aman Kharb, Yash H. Malviya, J. P. Sagar,Atanu R. Sinha, Iftikhar Ahamath Burhanuddin, and Sunav Choudhary

Visual Data Mining

AggregationNet: Identifying Multiple Changes Based on ConvolutionalNeural Network in Bitemporal Optical Remote Sensing Images . . . . . . . . . . 375

Qiankun Ye, Xiankai Lu, Hong Huo, Lihong Wan, Yiyou Guo,and Tao Fang

Detecting Micro-expression Intensity Changes from VideosBased on Hybrid Deep CNN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387

Selvarajah Thuseethan, Sutharshan Rajasegarar, and John Yearwood

A Multi-scale Recalibrated Approach for 3D Human Pose Estimation . . . . . . 400Ziwei Xie, Hailun Xia, and Chunyan Feng

Gossiping the Videos: An Embedding-Based Generative AdversarialFramework for Time-Sync Comments Generation . . . . . . . . . . . . . . . . . . . . 412

Guangyi Lv, Tong Xu, Qi Liu, Enhong Chen, Weidong He, Mingxiao An,and Zhongming Chen

Self-paced Robust Deep Face Recognition with Label Noise . . . . . . . . . . . . 425Pengfei Zhu, Wenya Ma, and Qinghua Hu

Multi-Constraints-Based Enhanced Class-Specific Dictionary Learningfor Image Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436

Ze Tian and Ming Yang

Discovering Senile Dementia from Brain MRI Using Ra-DenseNet . . . . . . . . 449Xiaobo Zhang, Yan Yang, Tianrui Li, Hao Wang, and Ziqing He

Contents – Part III xxxix

Knowledge Graph and Interpretable Data Mining

Granger Causality for Heterogeneous Processes . . . . . . . . . . . . . . . . . . . . . 463Sahar Behzadi, Kateřina Hlaváčková-Schindler, and Claudia Plant

Knowledge Graph Embedding with Order Information of Triplets . . . . . . . . . 476Jun Yuan, Neng Gao, Ji Xiang, Chenyang Tu, and Jingquan Ge

Knowledge Graph Rule Mining via Transfer Learning . . . . . . . . . . . . . . . . . 489Pouya Ghiasnezhad Omran, Zhe Wang, and Kewen Wang

Knowledge Base Completion by Inference from Both Relationaland Literal Facts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501

Zhichun Wang and Yong Huang

EMT: A Tail-Oriented Method for Specific Domain KnowledgeGraph Completion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514

Yi Zhang, Zhijuan Du, and Xiaofeng Meng

An Interpretable Neural Model with Interactive Stepwise Influence . . . . . . . . 528Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, and Xia Hu

Multivariate Time Series Early Classification with Interpretability UsingDeep Learning and Attention Mechanism. . . . . . . . . . . . . . . . . . . . . . . . . . 541

En-Yu Hsu, Chien-Liang Liu, and Vincent S. Tseng

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555

xl Contents – Part III