Extracting, Mining and Predicting Users' Interests from Social Networks-Reference-Cited by-同舟云学术

Extracting, Mining and Predicting Users' Interests from Social Networks

Published:2019-07-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Zarrinkalam Fattane¹,Fani Hossein²,Bagheri Ebrahim¹

Affiliation:

1. Ryerson University, Toronto, ON, Canada

2. University of New Brunswick, Fredericton, NB, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3331184.3331383

Reference31 articles.

1. Fabian Abel Qi Gao Geert-Jan Houben and Ke Tao. 2011. Analyzing User Modeling on Twitter for Personalized News Recommendations. In UMAP. 1--12. Fabian Abel Qi Gao Geert-Jan Houben and Ke Tao. 2011. Analyzing User Modeling on Twitter for Personalized News Recommendations. In UMAP. 1--12.

2. Fabian Abel Qi Gao Geert-Jan Houben and Ke Tao. 2011. Semantic Enrichment of Twitter Posts for User Profile Construction on the Social Web. In ESWC. 375--389. Fabian Abel Qi Gao Geert-Jan Houben and Ke Tao. 2011. Semantic Enrichment of Twitter Posts for User Profile Construction on the Social Web. In ESWC. 375--389.

3. Latent factor models with additive and hierarchically-smoothed user preferences

4. Negar Arabzadeh Hossein Fani Fattane Zarrinkalam Ahmed Navivala and Ebrahim Bagheri. 2018. Causal Dependencies for Future Interest Prediction on Twitter. In CIKM. 1511--1514. 10.1145/3269206.3269312 Negar Arabzadeh Hossein Fani Fattane Zarrinkalam Ahmed Navivala and Ebrahim Bagheri. 2018. Causal Dependencies for Future Interest Prediction on Twitter. In CIKM. 1511--1514. 10.1145/3269206.3269312

5. A new temporal and social PMF-based method to predict users' interests in micro-blogging

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