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Personalized Multi-Source News Delivery System for Enhanced User Engagement

The PNS (Personalized Multi-Source News Delivery) system offers a comprehensive solution for aggregating and personalizing news content. By utilizing advanced content and source aggregation techniques, the platform employs user modeling and community detection to deliver tailored news experiences. Users can enjoy a personalized selection of news articles based on their preferences and habits. The system operates independently of applications and integrates seamlessly with various services, ensuring an adaptable and user-friendly interface. Future enhancements will further expand its capabilities, including the introduction of additional data sources.

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Personalized Multi-Source News Delivery System for Enhanced User Engagement

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  1. 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

  2. Outline • Content aggregation News source aggregation • Information extraction Url extraction News content extraction • Personalization Single user modeling User communities, stereotypes and feature groups • Summary and future work

  3. The PNS approach • News source aggregation • Data collection (spiders and extraction) • User modeling • Presentation Filtering

  4. Users Webbrowser Content Server Content Database 1 2 3 Web Web Architecture News Content Scanner http Request – Response News Content Presenter News Content Selector http Request – Response News Sources Personalization Server

  5. News Content Scanner • Html and RSS Feed parsing • Extraction of urls that contain articles • News content extraction from URLs

  6. News Content Scanner Architecture of News Content Scanner

  7. Personalization Server (PServer) A general purpose personalization web server constructs and maintains models for • individual users • stereotypes • user communities • feature groups.

  8. 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

  9. 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

  10. 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.

  11. External databases External databases Personalization parameters Content database User models Knowledge base External databases Thin-client layer Pserver: Application Usage Personalization layer Data import Inference engine Web usage mining Knowledge editor Personalization meta-service designer User model management Personalization interface Content management Application layer Application designer User interface user

  12. News Content Selector • Structures the content that must be presented based on the request • Personalize the content

  13. 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.

  14. 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.

  15. News Content Presenter PNS User interface

  16. 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

  17. 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

  18. 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/

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