GeniUS: Generic User Modeling Libraryfor the Social Semantic WebJIST2011, December 2011, Hangzhou, China                  ...
What we do: Science and Engineering for the        Personal Webdomains: news social mediacultural heritage public datae-le...
Motivation                                      • Sparsity problem             Product                     • do not have e...
Research Challenges of GeniUS Various applications in different domains   Product        Movie           Hotel            ...
What is GeniUS?• GeniUSis a topic and user modeling software library that   • produces semantically meaningful profiles to...
GeniUS: Generic Topic and User Modeling Library    for the Social Semantic Web                                            ...
Item                                                                                                       Fetcher   GeniU...
Weighting   GeniUS modules: Weighting Function and                                              Function   RDF Serializati...
Filter      GeniUS modules: Configuration and Filter                                      Modeling                        ...
GeniUS: Generic Topic and User Modeling Libraryfor the Social Semantic WebSemantic Web                GeniUS              ...
Analysis of Domain-specific User Profile Construction• Dataset   • 72 Twitter users (CS researchers) observed over a perio...
Analysis of Domain-specific User Profile Constructionaverage number of entities: 1097.1                                   ...
Analysis of Domain-specific User Profile Construction                  domain: location      the more specific the domain ...
Evaluation of Domain-specific User Profile Construction• Task: Recommending domain-specific tweets• Domains:   • three dom...
Evaluation results    the domain-specific user modeling strategies   improve the performance of recommendations           ...
Evaluation results The sub-domain-specific user modeling strategyalso improve the performance of recommendation.          ...
Wrap up• GeniUS: Generic topic and User modeling library for the Social Semantic Web   • exploits traces (e.g. tweets) tha...
Thank You!                     q.gao@tudelft.nl                     Twitter: @qigaoshQiGao                     http://wis....
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GeniUS: Generic User Modeling Library for the Social Semantic Web

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  • Redundant;
  • Spars
  • Research challenges for GeniUSUser profiles with
  • Item fetcher , enrichment
  • Weighting function/RDF representationTime-sensitive, emphasize the temporal factor in news recommendations.
  • Modeling configuration: specify the implementation of the different modules. Filtering function
  • more details on the dataset
  • Our hypothesis is that
  • The user modeling quality varies only slightly between the different domains
  • GeniUS: Generic User Modeling Library for the Social Semantic Web

    1. 1. GeniUS: Generic User Modeling Libraryfor the Social Semantic WebJIST2011, December 2011, Hangzhou, China QiGao, Fabian Abel, Geert-Jan Houben {q.gao, f.abel, g.j.p.m.houben}@tudelft.nl Web Information Systems Delft University of Technology Delft University of Technology
    2. 2. What we do: Science and Engineering for the Personal Webdomains: news social mediacultural heritage public datae-learning Personalized Personalized Adaptive Systems Recommendations Search Analysis and User Modeling Semantic Enrichment, Linkage and Alignment user/usage data Social Web GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 2
    3. 3. Motivation • Sparsity problem Product • do not have enough useful Recommender information for a (new) user ? ? • Possible solution: gatheringuser data from other sources • But not all data may be relevant for User Modeling the given application context. • how to filter out user data that does not fit the target application context?I’m a new user.Recommend me some product GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 3
    4. 4. Research Challenges of GeniUS Various applications in different domains Product Movie Hotel Productrecommender recommender recommender recommender Profile ? customized user profile construction Analysis and interested in: User Modeling Product Movie location Semantic Enrichment How can we build a flexible and extensible user modeling functionality that adapts to the demands of a given application context? GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 4
    5. 5. What is GeniUS?• GeniUSis a topic and user modeling software library that • produces semantically meaningful profiles to enhance the interoperability of profiles between applications; • provides functionality for aggregating relevant information about a user from the Social Web; • generates domain-specific user profiles according to the information needs of different applications; • is flexible and extensible to serve different applications. GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 5
    6. 6. GeniUS: Generic Topic and User Modeling Library for the Social Semantic Web Semantic Web semantic data Filter enriched user data items user profiles RDF Item items Enrichmen Weighting Serializatio Fetcher t Function interested in: n product locationSocial Web Modeling RDF Configuration Repository GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 6
    7. 7. Item Fetcher GeniUS modules: Item Fetcher and Semantic Enrichment Enrichmen t raw content a <sioc:Post> ; sioc:has_topicdbpedia:Apple_Inc; Twitter SpotLight, dcterms:created … ; sioc:has_topicdbpedia:GarageBand; API Zemanta, sioc:has_creator …; sioc:has_topicdbpedia:Ipad; OpenCalais sioc:content … .Social Web Awesome, love the new Awesome, love the new Garageband for iPad #apple GaragebandiPad#apple Garageband for iPad #apple dbpedia:GarageBand dbpedia:Ipad dbpedia:Apple_Inc GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 7
    8. 8. Weighting GeniUS modules: Weighting Function and Function RDF Serialization RDF Serializatio n weight(dbpedia:Garag eBand) weight(dbpedi a:Jazz) weight(dbpedia:Secon TF d_Life) RDF TF-IDF SerializationTime-sensitive the weighted interests vocabulary GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 8
    9. 9. Filter GeniUS modules: Configuration and Filter Modeling Configuration(Jazz, 0.5889) (Second_Life, 0.4101)(Second_Life, 0.3114) SELECT DISTINCT ?t WHERE { Filter ? <rdf:type><dbpedia-owl:Software> } (GarageBand,(GarageBand, 0.2158) 0.1638) enriched items items Twitter SpotLight TF API Modeling Configuration GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 9
    10. 10. GeniUS: Generic Topic and User Modeling Libraryfor the Social Semantic WebSemantic Web GeniUS User Profile Applications interested in: product location … Social Web How do user profiles generated by GeniUS support different types of applications? GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 10
    11. 11. Analysis of Domain-specific User Profile Construction• Dataset • 72 Twitter users (CS researchers) observed over a period of 6 months (>40,000 tweets) • a variety of topics mentioned in the tweets• Research questions • 1. What are the characteristics of (complete) Twitter-based profiles generated with GeniUS ? • 2. Can domain-specific profiles be derived from Twitter activities ? • 3. What are the characteristics of such domain-specific profiles? GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 11
    12. 12. Analysis of Domain-specific User Profile Constructionaverage number of entities: 1097.1 average number of types: 35.0 a potential to generate domain-specific profiles by categorizing entities according to their types GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 12
    13. 13. Analysis of Domain-specific User Profile Construction domain: location the more specific the domain generic domain: entertainment the smaller the profiles (all domains) × domain: product Are the domain-specific user profiles beneficial for supporting different recommendation applications? GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 13
    14. 14. Evaluation of Domain-specific User Profile Construction• Task: Recommending domain-specific tweets• Domains: • three domains: location, entertainment, product • three sub-domains of product: book, software, music• Recommender algorithm: cosine similarity between profile and candidate item• Ground truth: relevant (re-)tweets of users• Candidate items: all the tweets posted during evaluation period Recommendations = ? P(u)= ? user profile time 1 month GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 14
    15. 15. Evaluation results the domain-specific user modeling strategies improve the performance of recommendations three different domains GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 15
    16. 16. Evaluation results The sub-domain-specific user modeling strategyalso improve the performance of recommendation. three sub-domains of product The user modeling quality varies only slightly between the different domains GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 16
    17. 17. Wrap up• GeniUS: Generic topic and User modeling library for the Social Semantic Web • exploits traces (e.g. tweets) that people leave on the Social Web • enriches the semantics of these traces • constructs semantic user profiles  profile construction can be customized and is adapted to a given application context• Analysis: • Twitter-based user profiles contain a great variety of topics • GeniUS succeeds in generating profiles for different applications and domains• Evaluation: • domain-specific user modeling strategies (powered by the semantic filtering of GeniUS) allow clearly for the best performance • the more GeniUS adapts to the given domain (and application context) the better the performance GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 17
    18. 18. Thank You! q.gao@tudelft.nl Twitter: @qigaoshQiGao http://wis.ewi.tudelft.nl/tweetum/ http://wis.ewi.tudelft.nl/genius/ GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 18
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