Temporal Recommendations for Discovering Author Interests

作者: Rishabh Malhotra , Anu Taneja , Anuja Arora

DOI: 10.1109/IC3.2019.8844932

关键词:

摘要: With the advancements in technology, a rich amount of research content is available on web that creates situation dilemma for researchers to choose most appropriate and trending topic further has wide scope future too. The prediction authors' interests always been challenging task as might change with time. This demands need an efficient temporal recommender system takes into account drifting users study addresses this major challenge analyses based similar their own long-term short-term interests. proposed model extends latent Dirichlet allocation (LDA) capture aspects utilizes semantic analysis (LSA) method along word-net feature incorporate understanding topics implemented real NIPS dataset collection 2000 conference papers. empirical validates achieves accuracy about 62% predictions due fusion

参考文章(17)
D Li, H., Yan, J., Weihong, H., Zhaoyun, Mining User Interest in Microblogs with a User-Topic Model China Communications. ,vol. 11, pp. 131- 144 ,(2014) , 10.1109/CC.2014.6911095
Bo Jiang, Ying Sha, Modeling Temporal Dynamics of User Interests in Online Social Networks international conference on conceptual structures. ,vol. 51, pp. 503- 512 ,(2015) , 10.1016/J.PROCS.2015.05.275
Lei Li, Li Zheng, Fan Yang, Tao Li, Modeling and broadening temporal user interest in personalized news recommendation Expert Systems With Applications. ,vol. 41, pp. 3168- 3177 ,(2014) , 10.1016/J.ESWA.2013.11.020
David M. Blei, John D. Lafferty, Dynamic topic models Proceedings of the 23rd international conference on Machine learning - ICML '06. pp. 113- 120 ,(2006) , 10.1145/1143844.1143859
Stuart Rose, Dave Engel, Nick Cramer, Wendy Cowley, Automatic Keyword Extraction from Individual Documents Text Mining. pp. 1- 20 ,(2010) , 10.1002/9780470689646.CH1
Mark Steyvers, Michal Rosen-Zvi, Thomas Griffiths, Padhraic Smyth, The author-topic model for authors and documents uncertainty in artificial intelligence. pp. 487- 494 ,(2004) , 10.5555/1036843.1036902
Scott Deerwester, Susan T. Dumais, George W. Furnas, Thomas K. Landauer, Richard Harshman, Indexing by Latent Semantic Analysis Journal of the Association for Information Science and Technology. ,vol. 41, pp. 391- 407 ,(1990) , 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9
Geoffrey Hinton, Laurens van der Maaten, Visualizing Data using t-SNE Journal of Machine Learning Research. ,vol. 9, pp. 2579- 2605 ,(2008)
Young-Seob Jeong, Sang-Hun Lee, Gahgene Gweon, Discovery of research interests of authors over time using a topic model international conference on big data and smart computing. pp. 24- 31 ,(2016) , 10.1109/BIGCOMP.2016.7425797