A survey on Short text analysis in Web

3rd International Conference on Advanced Computing, ICoAC 2011

Volumn , Issue , 2011, Pages 365-370

  Rafeeque, P C ^a   Sendhilkumar, S ^a  

^a ANNA UNIVERSITY   (India)

Author keywords

Classification; Clustering; Opinion mining; Short text

Indexed keywords

CLUSTERING; ISSUES AND CHALLENGES; OPINION MINING; SHORT TEXT CLASSIFICATIONS; SHORT TEXTS; SIMILARITY MEASURE; SYNTACTICAL STRUCTURES; TEXT CLASSIFICATION;

CLASSIFICATION (OF INFORMATION); INTERNET; SURVEYS;

TEXT PROCESSING;

EID: 84880905555     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICoAC.2011.6165203     Document Type: Conference Paper

References (46)

1. Li YH, McLean D, Bandar ZA et al, "Sentence similarity based on semantic nets and corpus statistics.", IEEE Trans Knowl Data Engg 18, pp.1138-1150, 2006.
2. Khaled Abdalgader, Andrew Skabar, "Short-Text Similarity Measurement Using Word Sense Disambiguation and Synonym Expansion.", LNAI 64649(Springer), pp.435-444, 2010.
3. Mihalcea, R., Corley, C., Strapparava, C, "Corpus-based and Knowledge-based Measures of Text Semantic Similarity.", In 21st National Conference on Art. Int., vol. 1, 2006, pp.775-780.
4. Ramage, D., Rafferty, A., Manning, C, "Random Walks for Text Semantic Similarity.", In ACL-IJCNLP 2009, pp.2331.
5. Islam, A., Inkpen, D, "Semantic Text Similarity using Corpus-based Word Similarity and String Similarity.", ACM Trans. on KDD 2(2), pp 1-25, 2008.
6. Okazaki N, Matsuo Y, Matsumura N et al, "Sentence extraction by spreading activation through sentence similarity.", IEICE Trans Inform Syst E86D(9), pp.1686-1694, 2003.
7. Phan X, Nguyen L, Horiguchi S, "Learn to classify Short and sparse text and web with hidden topics from large-scale data collections.", In Proceedings of the 17th international conference on World Wide Web, 2008, pp.91-100.
8. M. Sahami, T. Heilman, "A web-based kernel function for measuring the similarity of Short text snippets.", In Proc. of 15th International World Wide Web Conference, WWW 2006, May 2326, 2006, Edinburgh, Scotland, pp.377-386
9. Xiaojun Quan, Gang Liu et al., "Short text similarity based on probabilistic topics.", Knowl Inf Syst, pp. 473-491, 2009.
10. Metzler D, Dumais S, Meek C, "Similarity measures for Short segments of text.", In Proceedings of the 29th European conference on information retrieval (ECIR 2007), LNCS(Springer), Vol 4425, Berlin, 2007, pp 16-27
11. Yih W, Meek C, "Improving similarity measures for Short segments of text.", In Proceedings of twenty-second conference on artificial intelligence (AAAI-07), Vancouver, 2007, pp 1489-1494.
12. Bollegala D, Matsuo Y, Ishizuka M, "Measuring semantic similarity between words using Web search engines.", In Proceedings of the 16th international conference on World Wide Web, 2007, ACM Press, New York, pp. 757-766.
13. S. Zelikovitz and H. Hirsh, "Improving Short-Text Classification using Unlabeled Data for Classification Problems.", In Proceedings of the Sev-enteenth International Conference on Machine Learning, 2000, pp.1191-1198.
14. Qiang Pu and Guo-Wei Yang, "Short-Text Classification Based on ICA and LSA.", LNCS(Springer) 3972, pp 265-270, 2006.
15. Andreas Heb, Philipp Dopichaj and Christian Maab, "Multi-Value Classification of Very Short Texts.", In Proceedings of the 31st annual German conference on Advances in Artificial Intelligence, Springer-Verlag Berlin, 2008, pp.70-77.
16. Bharath Sriram, David Fuhry, Murat Demirbas, "Short Text Classification in Twitter to Improve Information Filtering.", ACM SIGIR, Geneva, Switzerland, 2010, pp.841-842.
17. Evan Wei Xiang, Qiang Yang, "Knowledge Base assisted Text Categorization.", ACM-HK Student Research and Career Day, 2009.
18. Sarah Zelikovitz, Haym Hirsh, "Using LSI for text classification in the presence of background text.", In Proceedings of the tenth international conference on Information and knowledge management(CIKM), 2001, pp. 113-118.
19. S. Zelikovitz, Transductive LSI for Short Text Classification Problems, In Proceedings of the Seventeenth International FLAIRS, 2004.
20. HUANG Wei, Li Shan-fei, Tan Yue-jin, Gao Bing, "Association Rules Based Short Text Feature Extension.", IJCSNS International Journal of Computer Science and Network Security, VOL.9 No.10, pp. 227-230, Oct. 2009.
21. Zitao Liu, Wenchao Yu, Wei Chen, Shuran Wang, Fengyi Wu, "Short Text Feature Selection for Micro-blog Mining.", In proceedings of Com-putational Intelligence and Software Engineering (CiSE), Wuhan, 2010, pp. 1-4.
22. Zhou Faguo, Zhang Fan, Yang Bingru, Yu Xingang, "Research on Short Text Classification Algorithm Based on Statistics and Rules.", In proceedings of third International Symposium on Electronic Commerce and Security(2010), pp. 3-7.
23. Banerjee S, Ramanathan K, Gupta A, "Clustering Short text using Wikipedia.", In Proceedings of the 30th international ACM SIGIR conference on research and development in information retrieval (SIGIR), 2007, pp. 787-788.
24. Xia Hu, Nan Sun, Chao Zhang, Tat-Seng Chua, "Exploiting internal and external semantics for the clustering of Short texts using world knowledge.", In Proc. CIKM Hong Kong, China, Nov. 2009, pp. 919-928.
25. Zamir O, Etzioni O, "Grouper: A dynamic clustering interface to web search results.", In Proceedings of the 8th international conference on World Wide Web, 1999, pp.1361-1374.
26. Zamir O, Etzioni O, "Web document clustering: a feasibility demonstration.", In Proceedings of the 21th international ACM SIGIR conference on research and development in information retrieval (SIGIR), 1998, pp. 46-54.
27. Hui He, Bo Chen, Weiran Xu, Jun Guo, "Short Text Feature Extraction and Clustering for Web Topic Mining.", In Proceedings of Third International Conference on Semantics, Knowledge and Grid, 2007, pp. 382-385.
28. Kummamuru K, Lotlikar R, Roy S, Singal K, Krishnapuram R, "A hierarchical monothetic document clustering algorithm for summarization and browsing search results.", In Proceedings of the 13th international conference on World Wide Web, 2004, pp. 658-665.
29. Makagonov, P., Alexandrov, M., Gelbukh, A, "Clustering abstracts instead of full texts.", In: Proceedings of TSD-2004, LNAI, vol. 3206, pp129-135.
30. Alexandrov, M., Gelbukh, A., Rosso, P, "An approach to clustering abstracts.", In: Proceedings of NLDB-05, LNCS(Springer), vol. 3513, pp. 8-13, 2005.
31. Pinto, D. "On Clustering and Evaluation of Narrow Domain Short-Text Corpora.", PhD Dissertation. Universidad Politencnica de Valencia, 2008
32. Pinto D., Rosso P., Jimnez H, "A Self-enriching methodology for clustering narrow domain Short texts.", The Computer Journal, 54(7), pp. 1148-1165, 2011. qq.
33. Li Yang, Adnan Rahi, "Dynamic Clustering of Web Search Results.", LNCS 2667(Springer), 2003, pp. 153-15.
34. Hua-Jun Zeng, Qi-Cai He, Zheng Chen, Wei-Ying Ma, Jinwen Ma, "Learning to Cluster Web Search Results.", ACM SIGIR04, South Yorkshire, UK, 2004, pp.210-217.
35. Wang X, Zhai C, "Learn from web search logs to organize search re-sults.", In Proceedings of the 15th international ACM SIGIR conference on research and development in information retrieval, 2007, pp. 8794
36. Xingliang Ni, Xiaojun Quan, Zhi Lu, Liu Wenyin, Bei Hua, "Short text clustering by finding core terms.", Knowledge and Information Systems, Springer, 27, pp.345-365, 2011.
37. Hsinchun Chen, David Zimbra, "AI and Opinion mining.", IEEE Intelligent Systems, vol. 25 no.4, 2010.
38. Huifeng Tang, Songbo Tan, Xueqi Cheng, "A survey on sentiment detection of reviews.", Expert Systems with Applications, ELsevier, 36, pp. 10760-10773, 2009
39. Bing Liu, "Sentiment Analysis and Subjectivity.", Handbook of Natural Language Processing, Second Edition, 2010
40. Yelena Mejova, "Sentiment Analysis: An Overview, Comprehensive Exam Paper.", 2009.
41. Yee W. LO, Vidyasagar, "A Review of Opinion Mining and Sentiment Classification Framework in Social Networks.", 3rd IEEE International Conference on Digital Ecosystems and Technologies, 2009, pp 396-401.
42. Thelwall, M., Buckley, K et. al. "Sentiment strength detection in Short informal text.", Journal of the American Society for Information Science and Technology, 61(12), pp.25442558, 2010.
43. L. Xu, A. Krzyzak, E. Oja, "Rival Penalized Competitive Learning for Clustering Analysis, RBF Net and Curve Detection.", IEEE Transactions on Neural Networks, pp.636-649, 1993
44. David M. Blei, Andrew Y. Ng, Michael I. Jordan, "Latent Dirichlet Allocation.", Journal of Machine Learning Research 3, pp.993-1022, 2003
45. Dolan, W., Chris Quirk, C., Brockett, C.V, "Unsupervised Construction of Large Paraphrase Corpora: Exploiting Massively Parallel News Sources.", In proceedings 20th International Conf. on Computational Linguistics, 2004, pp. 350-356.
46. J. Han, M. Kamber, "Data Mining: Concepts and Techniques.", Morgan Kaufmann Publishers(Elsevier), San Francisco, 2001