Typical recommender systems adopt a static view of the recommendation process and treat it as a prediction problem. We argue that it is more appropriate to view the problem of generating recommendations as a sequential optimization problem and, consequently, that Markov decision processes (MDPs) provide a more appropriate model for recommender systems. MDPs introduce two benefits: they take into account the long-term effects of each recommendation and the expected value of each recommendation. To succeed in practice, an MDP-based recommender system must employ a strong initial model, must be solvable quickly, and should not consume too much memory. In this paper, we describe our particular MDP model, its initialization using a predictive model, the solution and update algorithm, and its actual performance on a commercial site. We also describe the particular predictive model we used which outperforms previous models. Our system is one of a small number of commercially deployed recommender systems. As far as we know, it is the first to report experimental analysis conducted on a real commercial site. These results validate the commercial value of recommender systems, and in particular, of our MDP-based approach<\/p>\n","protected":false},"excerpt":{"rendered":"
Typical recommender systems adopt a static view of the recommendation process and treat it as a prediction problem. We argue that it is more appropriate to view the problem of generating recommendations as a sequential optimization problem and, consequently, that Markov decision processes (MDPs) provide a more appropriate model for recommender systems. MDPs introduce two […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193718],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-322340","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002)","msr_affiliation":"","msr_published_date":"2002-08-06","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"UAI-P-2002-PG-453-460","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"Proceedings of Twentieth Conference on Uncertainty in Artificial Intelligence, Banff, Canada, UAI Press","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"459801","msr_publicationurl":"https:\/\/arxiv.org\/abs\/1301.0600","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"an-mdp-based-recommender-systemv2","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/11\/An-MDP-Based-Recommender-Systemv2.pdf","id":459801,"label_id":0},{"type":"file","title":"an-mdp-based-recommender-system","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/11\/An-MDP-Based-Recommender-System.pdf","id":459798,"label_id":0},{"type":"url","title":"https:\/\/arxiv.org\/abs\/1301.0600","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":0,"url":"https:\/\/arxiv.org\/abs\/1301.0600"},{"id":459801,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2018\/01An-MDP-Based-Recommender-Systemv2.pdf"},{"id":459798,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2018\/01An-MDP-Based-Recommender-System.pdf"}],"msr-author-ordering":[{"type":"text","value":"Guy Shani","user_id":0,"rest_url":false},{"type":"text","value":"Ronen I. 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