PNS: Personalized Multi-Source News Delivery

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PNS: Personalized Multi-Source News Delivery Georgios Paliouras(1), Mouzakidis Alexandros(1), Christos Ntoutsis(2), Angelos Alexopoulos(3), Christos Skourlas(2) (1) Institute of Informatics and Telecommunications, NCSR "Demokritos", Greece {paliourg, alexm}@iit.demokritos.gr (2) Dept. of informatics ,Technological Institute of Athens, Greece (3) Dept. of Informatics and Telecommunications, University of Athens, Greece

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PNS: Personalized Multi-Source News Delivery. Georgios Paliouras(1), Mouzakidis Alexandros (1), Christos Ntoutsis(2), Angelos Alexopoulos(3), Christos Skourlas(2) (1) Institute of Informatics and Telecommunications, NCSR "Demokritos", Greece {paliourg, alexm }@iit.demokritos.gr - PowerPoint PPT Presentation

Transcript of PNS: Personalized Multi-Source News Delivery

Page 1: PNS: Personalized  Multi-Source News Delivery

PNS: Personalized Multi-Source News Delivery

Georgios Paliouras(1), Mouzakidis Alexandros(1), Christos Ntoutsis(2), Angelos Alexopoulos(3), Christos Skourlas(2)

(1) Institute of Informatics and Telecommunications, NCSR "Demokritos", Greece {paliourg, alexm}@iit.demokritos.gr

(2) Dept. of informatics ,Technological Institute of Athens, Greece

(3) Dept. of Informatics and Telecommunications, University of Athens, Greece

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Outline

Content aggregationNews source aggregation Information extractionUrl extractionNews content extraction PersonalizationSingle user modelingUser communities, stereotypes and feature groups Summary and future work

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The PNS approach

News source aggregation Data collection (spiders and extraction) User modeling Presentation Filtering

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Architecture

Web Web

Users

Content Database

1 2 3

Web browser

News Sources Personalization Server

http Request – Response

http Request

– Response

News Content Presenter

News Content Scanner

News ContentSelector

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News Content Scanner

Html and RSS Feed parsing Extraction of urls that contain articles News content extraction from URLs

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News Content Scanner

Architecture of News Content Scanner

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Personalization Server (PServer)

A general purpose personalization web server

constructs and maintains models for individual users stereotypes user communities feature groups.

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PServer

Independent of particular applications

Able to adapt to application parameters.

Covers a wide range of services and functionality.

Easily expandable.

Easy to set up and use by ongoing projects

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PServer

Personalization functionality as a web service:– Centrally installed and maintained.– Completely separated from applications.– Possible for many applications to use concurrently.– Easily accessible through HTTP.

Towards an adaptable model.– central concepts: application features, users.– Feature semantics not part of PServer.– Features organization in a tree-like manner facilitates querying.

lang.english lang.greek page10.top_frame.banner8

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PServer

Application communicates with PServer through HTTP requests. PServer response body is formatted in XML.

– Especially developed XSLs allow any browser to suitably display the PServer response.

Three distinct modes of operation: personal, stereotype.community

Application requests provide full control for inserting, updating, deleting and querying data:

Each request type can take up many forms, representing a set of possible actual requests.

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Pserver: Application Usage

user

Application designer

Personalization meta-service

designer

Content database

User models

Knowledge base

User interface

Content management

User model management

Inference engine

Web usage mining

Application layer

Personalization layer

Knowledge editor

Thin-client layer

Personalization interface Personalization

parameters

External databases

External databasesExternal

databases

Data import

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News Content Selector

Structures the content that must be presented based on the request

Personalize the content

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News Content Presenter

Registration of new users. Identification of registered users. Presentation of the daily news that exist in the Content

Index Database according to the user’s preferences (personal e-paper).

Presentation of the daily news according to the preferences of users that belong to the same stereotype.

Presentation of the daily news according to the preferences of users that belong to the same user community.

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News Content Presenter

Presentation of the daily news that belong to the same news itemset as the currently viewed item.

Personalized presentation of the news of previous days. Text-based search and presentation of news titles using

keywords. Ability to retrieve news highlight in specific dates from the

database.

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News Content Presenter

PNS User interface

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Summary

Easy to install 100% configurable A wide range of RDBMS can be used 100% Platform Independent PNS now contains 12 news source and 10

categories Static wrapper maintenance

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Future work

More sources will be added in the future A new module for dynamic wrapper

maintenance have to be build Content based personalization will be

supported Pserver will be published online as open

source software

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Thank you for your concentration

User Modeling 2007

11th International Conference on User Modeling (UM 2007)

Corfu , Greece , 25-29 June, 2007

Organized by

the National Center for Scientific Research "Demokritos",

in collaboration with

the Ionian University and User Modeling Inc.

http://www.iit.demokritos.gr/um2007/