Back نظام التوصية Arabic Sistema de recomanació Catalan سیستمی پێشنیارکەر CKB Doporučovací systém Czech Empfehlungsdienst German Sistema de recomendación Spanish سامانه توصیهگر Persian Suosittelujärjestelmä Finnish Système de recommandation French מערכות המלצה HE
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| Recommender systems |
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| Concepts |
| Methods and challenges |
| Implementations |
| Research |
A recommender system, or a recommendation system (sometimes replacing "system" with terms such as "platform", "engine", or "algorithm"), is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user.[1][2] Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.[1][3]
Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read.[1] Recommender systems are used in a variety of areas, with commonly recognised examples taking the form of playlist generators for video and music services, product recommenders for online stores, or content recommenders for social media platforms and open web content recommenders.[4][5] These systems can operate using a single type of input, like music, or multiple inputs within and across platforms like news, books and search queries. There are also popular recommender systems for specific topics like restaurants and online dating. Recommender systems have also been developed to explore research articles and experts,[6] collaborators,[7] and financial services.[8]
- ^ a b c Cite error: The named reference
handbookwas invoked but never defined (see the help page). - ^ Lev Grossman (May 27, 2010). "How Computers Know What We Want — Before We Do". TIME. Archived from the original on May 30, 2010. Retrieved June 1, 2015.
- ^ Cite error: The named reference
ResnickVarianwas invoked but never defined (see the help page). - ^ Gupta, Pankaj; Goel, Ashish; Lin, Jimmy; Sharma, Aneesh; Wang, Dong; Zadeh, Reza (2013). "WTF: the who to follow service at Twitter". Proceedings of the 22nd International Conference on World Wide Web. Association for Computing Machinery. pp. 505–514. doi:10.1145/2488388.2488433. ISBN 9781450320351.
- ^ Baran, Remigiusz; Dziech, Andrzej; Zeja, Andrzej (June 1, 2018). "A capable multimedia content discovery platform based on visual content analysis and intelligent data enrichment". Multimedia Tools and Applications. 77 (11): 14077–14091. doi:10.1007/s11042-017-5014-1. ISSN 1573-7721. S2CID 36511631.
- ^ H. Chen, A. G. Ororbia II, C. L. Giles ExpertSeer: a Keyphrase Based Expert Recommender for Digital Libraries, in arXiv preprint 2015
- ^ Chen, Hung-Hsuan; Gou, Liang; Zhang, Xiaolong; Giles, Clyde Lee (2011). "CollabSeer: a search engine for collaboration discovery" (PDF). Proceedings of the 11th Annual International ACM/IEEE Joint Conference on Digital Libraries. Association for Computing Machinery. pp. 231–240. doi:10.1145/1998076.1998121. ISBN 9781450307444.
- ^ Felfernig, Alexander; Isak, Klaus; Szabo, Kalman; Zachar, Peter (2007). "The VITA Financial Services Sales Support Environment" (PDF). In William Cheetham (ed.). Proceedings of the 19th National Conference on Innovative Applications of Artificial Intelligence, vol. 2. pp. 1692–1699. ISBN 9781577353232. ACM Copy.
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