TIARA: A visual exploratory text analytic system

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2010, Pages 153-162

  Wei, Furu ^a   Liu, Shixia ^a   Song, Yangqiu ^a   Pan, Shimei ^b   Zhou, Michelle X ^c   Qian, Weihong ^a   Shi, Lei ^a   Tan, Li ^a   Zhang, Qiang ^a  

^a IBM CHINA RESEARCH LAB   (China)

^b IBM T J WATSON RESEARCH CENTER   (United States)

^c IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

Document summarization; Exploratory analytics; Interactive visualization; Topic analysis; Visual text analytics

Indexed keywords

DOCUMENT SUMMARIZATION; EXPLORATORY ANALYTICS; INTERACTIVE VISUALIZATIONS; TOPIC ANALYSIS; VISUAL TEXT ANALYTICS;

VISUALIZATION;

EID: 77956220483     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835804.1835827     Document Type: Conference Paper

References (28)

1. D. Blei and J. Lafferty. Topic Models, chapter: Topic Models. Taylor and Francis, 2009. (in Press).
2. D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent Dirichlet allocation. J. Mach. Learn. Res., 3:993-1022, 2003.
3. C. Carpineto, S. Osiński, G. Romano, and D. Weiss. A survey of web clustering engines. ACM Comput. Surv., 41(3):1-38, 2009.
4. Y. Chen, L. Wang, M. Dong, and J. Hua. Exemplar-based visualization of large document corpus. IEEE Trans. Vis. Comput. Graph., 15(6):1161-1168, 2009.
5. E. Clarkson, K. Desai, and J. D. Foley. Resultmaps: Visualization for search interfaces. IEEE Trans. Vis. Comput. Graph., 15(6):1057-1064, 2009.
6. M. Dredze, H. M. Wallach, D. Puller, and F. Pereira. Generating summary keywords for emails using topics. In IUI, pages 199-206, 2008.
7. T. L. Griffiths and M. Steyvers. Finding scientific topics. Proceedings of the National Academy of Sciences, 101(Suppl. 1):5228-5235, April 2004.
8. F. V. Ham, M. Wattenberg, and F. B. Viégas. Mapping text with phrase nets. In InfoVis, pages 1169-1176, 2009.
9. S. Havre, E. Hetzler, P. Whitney, and L. Nowell. Themeriver: Visualizing thematic changes in large document collections. IEEE Trans. Vis. Comput. Graph., 8(1):9-20, 2002.
10. T. Iwata, T. Yamada, and N. Ueda. Probabilistic latent semantic visualization: topic model for visualizing documents. In KDD, pages 363-371, 2008.
11. A. Jain, M. Murty, and P. Flynn. Data clustering: A review. ACM Computing Surveys, 31(3):264-323, 1999.
12. W. Ke, C. R. Sugimoto, and J. Mostafa. Dynamicity vs. effectiveness: studying online clustering for scatter/gather. In SIGIR, pages 19-26, 2009.
13. B. Lee, G. Smith, G. G. Robertson, M. Czerwinski, and D. S. Tan. Facetlens: exposing trends and relationships to support sensemaking within faceted datasets. In CHI, pages 1293-1302, 2009.
14. J. Leskovec, L. Backstrom, and J. Kleinberg. Meme-tracking and the dynamics of the news cycle. In KDD, pages 497-506, 2009.
15. S. Liu, M. X. Zhou, S. Pan, W. Qian, W. Cai, and X. Lian. Interactive, topic-based visual text summarization and analysis. In CIKM, pages 543-552, 2009.
16. A. K. McCallum. Mallet: A machine learning for language toolkit. http://mallet.cs.umass.edu, 2002.
17. Q. Mei and C. Zhai. Discovering evolutionary theme patterns from text: an exploration of temporal text mining. In KDD, pages 198-207, 2005.
18. P. Pirolli, P. Schank, M. Hearst, and C. Diehl. Scatter/gather browsing communicates the topic structure of a very large text collection. In CHI, pages 213-220, 1996.
19. G. Salton and M. J. McGill. Introduction to Modern Information Retrieval. McGraw-Hill, New York, NY, USA, 1986.
20. G. Smith, M. Czerwinski, B. Meyers, D. C. Robbins, G. G. Robertson, and D. S. Tan. Facetmap: A scalable search and browse visualization. IEEE Trans. Vis. Comput. Graph., 12(5):797-804, 2006.
21. Y. Song, S. Pan, S. Liu, F. Wei, M. X. Zhou, and W. Qian. Constrained co-clustering for textual documents. In AAAI, 2010.
22. Y. Song, S. Pan, S. Liu, M. X. Zhou, and W. Qian. Topic and keyword re-ranking for LDA-based topic modeling. In CIKM, pages 1757-1760, 2009.
23. X. Wang and A. McCallum. Topics over time: a non-Markov continuous-time model of topical trends. In KDD, pages 424-433, 2006.
24. M. Wattenberg and F. B. Viégas. The word tree, an interactive visual concordance. In InfoVis, pages 1221-1228, 2008.
25. X. Wei and W. B. Croft. LDA-based document models for ad-hoc retrieval. In SIGIR, pages 178-185, 2006.
26. S. Xu, T. Jin, and F. C. M. Lau. A new visual search interface for web browsing. In WSDM, pages 152-161, 2009.
27. J. Zhang, Y. Song, C. Zhang, and S. Liu. Evolutionary hierarchical Dirichlet processes for multiple correlated time-varying corpora. In KDD, 2010.
28. C. Ziemkiewicz and R. Kosara. Preconceptions and individual differences in understanding visual metaphors. Comput. Graph. Forum, 28(3):911-918, 2009.