inria-00327070, version 1
Collaborative Filtering inspired from Language Modeling
Geoffray Bonnin
a, 1Armelle Brun a, 1Anne Boyer a, 1
Proceedings of the First International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2008), Workshop on Recommender Systems and Personalized Retrieval (RSPR) (2008)
Résumé : Recommender systems filter resources for a given user by predicting the most pertinent item given a specific context. This paper describes a new approach of generating suitable recommendations based on the active user's navigation stream. The underlying hypothesis is that the items order in the stream results from the intrinsic logic of the user's behavior. We show similarities between natural language and Internet navigation and put forward navigation specificities. We then design a new model that integrates advantages of statistical language models such as n-grams and triggers to compute recommendations. The resulting Sequence Based Recommender has been tested on Internet navigation artificial corpora.
- a – LORIA
- 1 : KIWI (LORIA)
- INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)
- Domaine : Informatique/Informatique et langage
Informatique/Recherche d'informationInformatique/Web
- inria-00327070, version 1
- http://hal.inria.fr/inria-00327070
- oai:hal.inria.fr:inria-00327070
- Contributeur : Geoffray Bonnin
- Soumis le : Mardi 7 Octobre 2008, 11:57:02
- Dernière modification le : Jeudi 7 Juillet 2011, 13:00:59
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