Read e-book online Advances in Neural Information Processing Systems 2 PDF

By David S. Touretzky (Editor)

ISBN-10: 1558601007

ISBN-13: 9781558601000

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In: Proceedings of Knowledge-Based Electronic Markets. Papers from the AAAI Workshop, AAAI Technical Report WS-00-04, pp. 78–83. Menlo Park (2000) 51. : Clustering methods for collaborative filtering. In: Proceedings of AAAI Workshop on Recommendation Systems. AAAI Press (1998) 52. : A music retrieval system based on user driven similarity and its evaluation. In: Proceedings of 6th International Conference on Music Information Retrieval, pp. 272–279. London (2005) 53. : Efficient Bayesian hierarchical user modeling for recommendation system.

For a given set of labeled data points Train − Set = {(x1 , y1 ), (x2 , y2 ), . . , (xn , yn )}, with yi ∈ {−1, 1} and a set of test data points Test−Set = {xn+1 , xn+2 , . . , xn+k }, where xi ∈ Rd , transduction seeks among the feasible corresponding labels ∗ , y∗ , . . , y∗ the one yn+1 n+2 n+k that has the minimum number of errors. Also, transduction would be useful among other ways of inference in which there are either a small amount of labeled data points available or the cost for annotating data points is prohibitive.

In [46], the authors used latent semantic indexing to create a collaborative view of a collection of user profiles represented as term vectors. This technique results in performance improvement in comparison with the pure content-based approach. , the age or gender of users or the genre of movies) in a single rule-based classifier. Single unifying models were also presented in [31], where the authors utilized a unified probabilistic method for combining collaborative and content-based recommendations.

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Advances in Neural Information Processing Systems 2 by David S. Touretzky (Editor)


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