Entity disambiguation in tweets leveraging user social profiles

Proceedings of the 2013 IEEE 14th International Conference on Information Reuse and Integration, IEEE IRI 2013

Volumn , Issue , 2013, Pages 120-128

  Yerva, Surender Reddy ^a   Catasta, Michele ^a   Demartini, Gianluca ^a   Aberer, Karl ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION USE; SEMANTICS;

DOMAIN SPECIFIC; ENTITY DISAMBIGUATION; NETWORK ACTIVITIES; NETWORK USERS; PERVASIVE WEBS; SEMANTIC FEATURES; SOCIAL PROFILES; USER-GENERATED CONTENT;

SOCIAL NETWORKING (ONLINE);

EID: 84891090962     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IRI.2013.6642462     Document Type: Conference Paper

References (30)

1. Fabian Abel, Qi Gao, Geert-Jan Houben, and Ke Tao. Analyzing usermodeling on twitter for personalized news recommendations. UMAP,2011.
2. Fabian Abel, Eelco Herder, and Daniel Krause. Extraction of professionalinterests from social web profiles. In UMAP, 2011.
3. E. Amigo, J. Artiles, J. Gonzalo, D. Spina, B. Liu, and A. Corujo.WePS3 Evaluation Campaign: Overview of the On-line ReputationManagement Task. In WePS, 2010.
4. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. Latent dirichletallocation. Journal of Machine Learning Research, 2003.
5. David G. Brizan and Abdullah U. Tansel. A Survey of Entity Resolutionand Record Linkage Methodologies. IIMA, 2006.
6. Chia-Hui Chang, Mohammed Kayed, Moheb Ramzy Girgis, and KhaledShaalan. A survey of web information extraction systems, 2006.
7. Qi Gao, Fabian Abel, Geert-Jan Houben, and Yong Yu. A comparativestudy of users microblogging behavior on sina weibo and twitter. InUMAP, 2012.
8. John Hannon, Mike Bennett, and Barry Smyth. Recommending twitterusers to follow using content and collaborative filtering approaches. InRecSys, 2010.
9. John Hannon, Kevin McCarthy, Michael P. OMahony, and BarrySmyth. A multi-faceted user model for twitter. In UMAP, 2012.
10. David Heckerman. Learning in graphical models, chapter A tutorial onlearning with Bayesian networks. MIT Press, 1999.
11. Liangjie Hong and Brian D. Davison. Empirical study of topic modelingin twitter. In SOMA, 2010.
12. Jeon-Hyung Kang, Jun Ma, and Yan Liu. Transfer topic modeling withease and scalability. CoRR, 2013.
13. David D. Lewis. Naive (Bayes) at Forty: The Independence Assumptionin Information Retrieval. In ECML, 1998.
14. Chenliang Li, Jianshu Weng, Qi He, Yuxia Yao, Anwitaman Datta,Aixin Sun, and Bu-Sung Lee. Twiner: named entity recognition intargeted twitter stream. In SIGIR, 2012.
15. Sian Lindley, Cathy Marshall, Richard Banks, Abigail Sellen, and TimRegan. Rethinking the web as a personal archive. In WWW, 2013.
16. Bing Liu and Lei Zhang. A survey of opinion mining and sentimentanalysis. Mining Text Data, 2012.
17. David Nadeau and Satoshi Sekine. A survey of named entity recognitionand classification. Linguisticae Investigationes, 2007.
18. Niels Ott, Ramon Ziai, Michael Hahn, and Detmar Meurers. Comet: Integratingdifferent levels of linguistic modeling for meaning assessment.In (SemEval), 2013.
19. Aditya Pal and Scott Counts. Identifying topical authorities in microblogs.In WSDM, 2011.
20. Daniel Ramage, Susan Dumais, and Dan Liebling. Characterizingmicroblogs with topic models. In AAAI, 2010.
21. Daniel Ramage, David Hall, Ramesh Nallapati, and Christopher D.Manning. Labeled LDA: a supervised topic model for credit attributionin multi-labeled corpora. EMNLP, 2009.
22. Alan Ritter, Sam Clark, Mausam, and Oren Etzioni. Named entityrecognition in tweets: an experimental study. In EMNLP, 2011.
23. Harish Srinivasan, John Chen, and Rohini Srihari. Cross documentperson name disambiguation using entity profiles, 2009.
24. Stanford topic modeling toolbox. http://nlp.stanford.edu/software/tmt/ tmt-0.4/.
25. Jianshu Weng, Ee-Peng Lim, Jing Jiang, and Qi He. Twitterrank: findingtopic-sensitive influential twitterers. In WSDM, 2010.
26. Meng-Sung Wu and Jen-Tzung Chien. A new topic-bridged model fortransfer learning. In ICASSP, 2010.
27. L. Yang, M. Moshtaghi, B. Han, S. Karunasekera, R. Kotagiri, T. Baldwin,and A. Harwood. Mining micro-blogs: Opportunities and challenges.Social Networks: Computational Aspects and Mining.
28. Surender R. Yerva, Zoltan Miklos, and Karl Aberer. What have fruitsto do with technology? the case of Orange, Blackberry and Apple. InWIMS, 2011.
29. Surender R. Yerva, Zoltan Miklos, and Karl Aberer. Entity- basedclassification of twitter messages. International Journal of ComputerScience and Applications, 2012.
30. Wayne X. Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee P. Lim, HongfeiYan, and Xiaoming Li. Comparing twitter and traditional media usingtopic models. In ECIR, 2011.