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Title:
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PARAMETER ESTIMATION BASED ON EM ALGORITHM FOR ANTI-FOLKSONOMICAL ITEM RECOMMENDATION SYSTEM IN SOCIAL BOOKMARKING |
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Author(s):
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Akira Sasaki , Takamichi Miyata , Yoshinori Sakai , Yasuhiro Inazumi , Aki Kobayashi |
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ISBN:
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978-972-8924-97-3 |
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Editors:
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Hans Weghorn and Pedro Isaías |
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Year:
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2009 |
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Edition:
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V I, 2 |
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Keywords:
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Social Bookmarking, Anti-folksonomy, Collaborative Filtering |
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Type:
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Full Paper |
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First Page:
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43 |
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Last Page:
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50 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Collaborative filtering (CF) is a technique widely used in recommendation systems. However, if we have only a sparse
data matrix that consists of users preferences, CF performance seriously degrades. We developed a CF-based
recommendation system using social bookmarking data to solve the problems data sparsity causes[1]. However, we
applied our method only to small data set, and we decided the parameters heuristically. In this study, we developed a
parameter estimation method by using an EM-algorithm and evaluated our system using a huge dataset obtained from
actual social bookmarking services. |
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