Improving minhashing: De Bruijn sequences and primitive roots for counting trailing zeroes Mark Manasse Frank McSherry Kunal Talwar Microsoft Research.
WSCD 2009. INTRODUCTION Query suggestion has often been described as the process of making a user query resemble more closely the documents it is expected.
1 Theory of LSH Distance Measures LS Families of Hash Functions S-Curves.
1 Near Duplicate Detection Slides adapted from –Information Retrieval and Web Search, Stanford University, Christopher Manning and Prabhakar Raghavan –CS345A,
Finding Similar Items. Set Similarity Problem: Find similar sets. Motivation: Many things can be modeled/represented as sets Applications: –Face Recognition.
PMSB 2006, Tuusula (Finland) A. Bertoni, G.Valentini, DSI - Univ. Milano 1 Alberto Bertoni, Giorgio Valentini {bertoni,valentini}@dsi.unimi.it
Query Specific Fusion for Image Retrieval
DATA MINING LECTURE 6
Finding Similar Items
Flexible Querying of Lifelong Learner Metadata Alex Poulovassilis, Peter T. Wood
DATA MINING LECTURE 6 Sketching, Min-Hashing, Locality Sensitive Hashing.
Maximizing Product Adoption in Social Networks Smriti Bhagat, Amit Goyal, Laks Lakshmanan (Paper appeared in WSDM 2012)
