Research on Network Literature Recommendation Technology Based on Literature Tag

Tian Ran Fu; Guo Hui Song

doi:10.4028/www.scientific.net/AMM.687-691.2059

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691Research on Network Literature Recommendation...

Research on Network Literature Recommendation Technology Based on Literature Tag

Abstract:

With the development of network literature website, the number of network literature increase dramatically. Readers will hardly know which literature to select from the great mass of network literature that steadily accumulates. Some network literature website use collaborative filter method to recommend potential interested literature to user. However, the collaborative filter algorithm has many defects, such as cold start and sparsity. To solve these problems, we propose a new method which based on literature tag. This method is helpful to overcome collaborative filter algorithm’s shortcoming.

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Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

2059-2062

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.2059

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Online since:

November 2014

Authors:

Tian Ran Fu*, Guo Hui Song

Keywords:

Literature Recommendation, Literature Tag, Recommender System

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* - Corresponding Author

References

[1] Billsus D, Pazzani M J. Learning Collaborative Information Filters[C]/ICML. 1998, 98: 46-54.

Google Scholar

[2] Fisher D, Hildrum K, Hong J, et al. SWAMI (poster session): a framework for collaborative filtering algorithm development and evaluation[C]/Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval. ACM, 2000: 366-368.

DOI: 10.1145/345508.345658

Google Scholar

[3] Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions[J]. Knowledge and Data Engineering, IEEE Transactions on, 2005, 17(6): 734-749.

DOI: 10.1109/tkde.2005.99

Google Scholar

[4] Lang K. Newsweeder: Learning to filter netnews[C]/In Proceedings of the Twelfth International Conference on Machine Learning. (1995).

DOI: 10.1016/b978-1-55860-377-6.50048-7

Google Scholar

[5] Kobsa A. Privacy-enhanced personalization[J]. Communications of the ACM, 2007, 50(8): 24-33.

Google Scholar

[6] Herlocker J L, Konstan J A, Terveen L G, et al. Evaluating collaborative filtering recommender systems[J]. ACM Transactions on Information Systems (TOIS), 2004, 22(1): 5-53.

DOI: 10.1145/963770.963772

Google Scholar

[7] Sarwar B, Karypis G, Konstan J, et al. Analysis of recommendation algorithms for e-commerce[C]/Proceedings of the 2nd ACM conference on Electronic commerce. ACM, 2000: 158-167.

DOI: 10.1145/352871.352887

Google Scholar