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| − | Recommendation is the subject of recommender systems, which "form or work from a specific type of information filtering system technique that attempts to recommend information items (movies, TV program/show/episode, video on demand, | + | Recommendation is the subject of recommender systems, which "form or work from a specific type of information filtering system technique that attempts to recommend information items (movies, TV program/show/episode, video on demand, [http://ontologydesignpatterns.org/wiki/Community:Music music], books, news, images, web pages, scientific literature such as research papers etc.) that are likely to be of interest to the user. |
Typically, a recommender system compares a [http://ontologydesignpatterns.org/wiki/Community:Personalization user profile] to some reference characteristics, and seeks to predict the 'rating' that a user would give to an item they had not yet considered. These characteristics may be from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach)." (see [http://en.wikipedia.org/wiki/Recommender_system Recommender System @ Wikipedia]). | Typically, a recommender system compares a [http://ontologydesignpatterns.org/wiki/Community:Personalization user profile] to some reference characteristics, and seeks to predict the 'rating' that a user would give to an item they had not yet considered. These characteristics may be from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach)." (see [http://en.wikipedia.org/wiki/Recommender_system Recommender System @ Wikipedia]). | ||
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| Name: | Recommendation |
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| Description: | Recommendation is the subject of recommender systems (see Recommender system @ Wikipedia) |
| Content OPs addressing this domain |
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| No CPs address this domain |
| Exemplary ontologies addressing this domain |
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| No exemplary ontologies address this domain |
| Modeling issues related to this domain |
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| none |
Recommendation is the subject of recommender systems, which "form or work from a specific type of information filtering system technique that attempts to recommend information items (movies, TV program/show/episode, video on demand, music, books, news, images, web pages, scientific literature such as research papers etc.) that are likely to be of interest to the user.
Typically, a recommender system compares a user profile to some reference characteristics, and seeks to predict the 'rating' that a user would give to an item they had not yet considered. These characteristics may be from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach)." (see Recommender System @ Wikipedia).
'Ontology Design Patterns'