Searching for authors named "Manos Papagelis" – sorted by Relevance.
5 documents found, showing 1 through 5.
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Qualitative Analysis of Userbased and Item-based Prediction Algorithms for Recommendation Systems, CIA 2004
- …Abstract. Recommendation agents employ prediction algorithms to provide users with items that match their interests. In this paper, we describe and evaluate several prediction algorithms, some of which are novel in that they combine user-based and item-based similarity measures derived from either e…
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Recommendation Based Discovery of Dynamic Virtual Communities
- …Introduction Recommendation systems have been a popular topic of research ever since the ubiquity of the web made it clear that people of hugely varying backgrounds would be able to access and query the same underlying data. Content-based [1] and collaborative filtering [1], [2] algorithms are usua…
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Global Grid Forum 5
- …Abstract. Collaborative Filtering (CF), the prevalent recommendation approach, has been successfully used to identify users that can be characterized as “similar ” according to their logged history of prior transactions. However, the applicability of CF is limited due to the sparsity problem, which …
- Cited by 3 (1 self) – Add To MetaCart
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Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms
- …Abstract. Most recommendation systems employ variations of Collaborative Filtering (CF) for formulating suggestions of items relevant to users ’ interests. However, CF requires expensive computations that grow polynomially with the number of users and items in the database. Methods proposed for hand…
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CONFIOUS: Managing the Electronic Submission and Reviewing Process of Scientific Conferences
- …Abstract. Most scientific communities have recently established policies and mechanisms to put into practice electronic conference management, mainly by exploiting the Internet as the communication and cooperation infrastructure. Their foremost objective is to reduce the operational and communicatio…
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Showing 1 through 5.
