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WeeVis
WeeVis is an online tool for the development and execution of recommender applications on the basis of an adapted Wikipedia syntax (see 〔S. Reiterer, A. Felfernig, P. Blazek, G. Leitner, F. Reinfrank, G. Ninaus: WeeVis. In: Knowledge-based Configuration: From Research to Business Cases, Elsevier/Morgan Kaufmann, pp. 297-307 (2014).〕). The major advantage of WeeVis is that developing recommender applications becomes possible without computer science knowledge. Users only need some experience in the development of Wiki pages and also knowledge about the underlying product domain (e.g., computers and bicycles).
== Application Areas ==
There are three basic types of recommender technologies.〔D. Jannach, M. Zanker, A. Felfernig, G. Friedrich: Recommender Systems. An Introduction. Cambridge (2011).〕 Collaborative approaches determine recommendations, for example, on the basis of the similarity between different users; content-based approaches rely on the content similarity between different items. In contrast, knowledge-based recommenders exploit explicit knowledge about the underlying product assortment.〔R. Burke: Knowledge-based Recommender Systems. Encyclopedia of Library and Information Systems, pp. 180-200 (2000).〕 An example thereof are product attributes of computers (e.g., processor, memory, and harddisk). In addition, information about user preferences and the dependencies between preferences of product properties are needed (the latter is often defined in terms of constraints).
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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