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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/12454

Title: Recommender Systems. Case iKnow: Composition of the required building blocks for the development of recommender systems
Authors: Plessers, Ben
Advisors: SCHREURS, Joanna
Issue Date: 2010
Publisher: UHasselt Diepenbeek
Abstract: In a period of time where knowledge management is a very important issue and the problem of information overload is growing, there is a need for systems that can help to obtain information, knowledge and data. The information and knowledge necessary for decision-making needs to be available and accessible in an easy way for the right person, at the time the information or knowledge is needed. This is where recommender systems come in. Recommender systems are software systems that supply users with information in order to help them make decisions or to solve problems, without users have to search for it themselves. A case study executed in cooperation with iKnow, in combination with a literature review, results in a description of a proposition for a recommender system. The recommender system described in this paper is based on the Semantic Web and Linked Data. It uses the SPARQL query language to query RDF files.
Notes: Master of Management
URI: http://hdl.handle.net/1942/12454
Category: T2
Type: Theses and Dissertations
Appears in Collections: Master theses

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