Improving Tag-Based Recommendation by Topic Diversification

Author:

Wartena Christian,Wibbels Martin

Publisher

Springer Berlin Heidelberg

Reference20 articles.

1. Tso-Sutter, K.H.L., Balby Marinho, L., Schmidt-Thieme, L.: Tag-aware recommender systems by fusion of collaborative filtering algorithms. In: Wainwright, R.L., Haddad, H. (eds.) SAC, pp. 1995–1999. ACM, New York (2008)

2. Lecture Notes in Computer Science;H. Liang,2009

3. Said, A., Wetzker, R., Umbrath, W., Hennig, L.: A hybrid plsa approach for warmer cold start in folksonomy recommendation. In: Proceedings of the RecSys 2009 Workshop on Recommender Systems & The Social Web (2009)

4. Bogers, T., van den Bosch, A.: Collaborative and Content-based Filtering for Item Recommendation on Social Bookmarking Websites. In: Proceedings of the ACM RecSys 2009 Workshop on Recommender Systems & the Social Web, New-York, NY, USA, pp. 9–16 (2009)

5. Firan, C.S., Nejdl, W., Paiu, R.: The benefit of using tag-based profiles. In: Almeida, V.A.F., Baeza-Yates, R.A. (eds.) LA-WEB, pp. 32–41. IEEE Computer Society, Los Alamitos (2007)

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1. KnowGen: A Knowledge Generation Approach for Tag Recommendation Using Ontology and Honey Bee Algorithm;Artificial Intelligence Systems and the Internet of Things in the Digital Era;2021

2. Tag-Based Recommendation;Social Information Access;2018

3. A Survey on Recommendation Methods Beyond Accuracy;IEICE Transactions on Information and Systems;2017

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