One-and-only item recommendation with fuzzy logic techniques

act 11 Recommender systems anticipate users’ needs by suggesting items that are likely to interest them. Most existing systems 12 employ collaborative filtering (CF) techniques, searching for regularities in the way users have rated items. While in general 13 a successful approach, CF cannot cope well with so-called one-and-only items, that is: items of which there is only one 14 single instance (like an event), and which as such cannot be repetitively ‘‘sold’’. Typically such items are evaluated only 15 after they have ceased being available, thereby thwarting the classical CF strategy. In this paper, we develop a conceptual 16 framework for recommending one-and-only items. It uses fuzzy logic, which allows to reflect the graded/uncertain infor17 mation in the domain, and to extend the CF paradigm, overcoming limitations of existing techniques. A possible applica18 tion in the context of trade exhibition recommendation for e-government is discussed to illustrate the propos...

• Type: Journal
• Year: 2007
• Where: ISCI
• Authors: Chris Cornelis, Jie Lu, Xuetao Guo, Guanquang Zhang
• Keywords: ISCI 2007, Most Existing Systems, Recommender Systems, So-called One-and-only Items