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Data Sparsity: A Key Disadvantage of User-Based Collaborative Filtering?

B. Hu, Z. Li, и W. Chao. APWeb, том 7235 из Lecture Notes in Computer Science, стр. 602-609. Springer, (2012)

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A context approach to measuring similarity between questions in the community-based QA services.J. Wang, Z. Li, и B. Hu. FSKD, стр. 2408-2411. IEEE, (2010)When Sparsity Meets Noise in Collaborative Filtering.B. Hu, Z. Li, и W. Chao. APWeb, том 7235 из Lecture Notes in Computer Science, стр. 594-601. Springer, (2012)Content Semantic Similarity Boosted Collaborative Filtering.B. Hu, и Y. Zhou. CIS (2), стр. 7-11. IEEE Computer Society, (2008)978-0-7695-3508-1.Application of Item Response Theory to Collaborative Filtering.B. Hu, Y. Zhou, J. Wang, L. Li, и L. Shen. ISNN (1), том 5551 из Lecture Notes in Computer Science, стр. 766-773. Springer, (2009)Data Sparsity: A Key Disadvantage of User-Based Collaborative Filtering?B. Hu, Z. Li, и W. Chao. APWeb, том 7235 из Lecture Notes in Computer Science, стр. 602-609. Springer, (2012)User's Latent Interest-Based Collaborative Filtering.B. Hu, Z. Li, и J. Wang. ECIR, том 5993 из Lecture Notes in Computer Science, стр. 619-622. Springer, (2010)