Search results
Results From The WOW.Com Content Network
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] [3] Recommender systems are particularly useful when an individual needs to ...
Collaborative filtering (CF) is a technique used by recommender systems. [1] Collaborative filtering has two senses, a narrow one and a more general one. [2]In the newer, narrower sense, collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating).
Recommender systems. Matrix factorization is a class of collaborative filtering algorithms used in recommender systems. Matrix factorization algorithms work by decomposing the user-item interaction matrix into the product of two lower dimensionality rectangular matrices. [1] This family of methods became widely known during the Netflix prize ...
Netflix Prize. ACM Conference on Recommender Systems. v. t. e. Cold start is a potential problem in computer-based information systems which involves a degree of automated data modelling. Specifically, it concerns the issue that the system cannot draw any inferences for users or items about which it has not yet gathered sufficient information.
The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e. without the users being identified except by numbers assigned for the contest. The competition was held by Netflix, a video streaming ...
Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.
Slope One. Slope One is a family of algorithms used for collaborative filtering, introduced in a 2005 paper by Daniel Lemire and Anna Maclachlan. [1] Arguably, it is the simplest form of non-trivial item-based collaborative filtering based on ratings. Their simplicity makes it especially easy to implement them efficiently while their accuracy ...
Knowledge-based recommender systems are often conversational, i.e., user requirements and preferences are elicited within the scope of a feedback loop. A major reason for the conversational nature of knowledge-based recommender systems is the complexity of the item domain where it is often impossible to articulate all user preferences at once.