Ontology-based structured cosine similarity in document summarization: With applications to mobile audio-based knowledge management

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 35, Issue 5, 2005, Pages 1028-1040

  Yuan, Soe Tsyr ^a   Sun, Jerry ^b  

^a NATIONAL CHENGCHI UNIVERSITY   (Taiwan)

^b Tornado Technologies Co Ltd   (Taiwan)

Author keywords

B2E M Commerce; Spherical K means clustering; Structured cosine similarity (SCS); Text categorization; Text summarization

Indexed keywords

DATA MINING; DATA STRUCTURES; KNOWLEDGE ACQUISITION; MATHEMATICAL MODELS; SPEECH RECOGNITION; TEXT PROCESSING; WIRELESS TELECOMMUNICATION SYSTEMS;

DOCUMENT SUMMARIZATION; K MEANS CLUSTERING; MOBILE AUDIO-BASED KNOWLEDGE MANAGEMENT; ONTOLOGY BASED STRUCTURED COSINE SIMILARITY; TEXT CATEGORIZATION; TEXT SUMMARIZATION;

KNOWLEDGE BASED SYSTEMS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; AUTOMATIC SPEECH RECOGNITION; CLUSTER ANALYSIS; COMPUTER INTERFACE; DOCUMENTATION; EVALUATION; FACTUAL DATABASE; INFORMATION RETRIEVAL; LINGUISTICS; METHODOLOGY; NATURAL LANGUAGE PROCESSING; ONLINE SYSTEM; TELECOMMUNICATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; DATABASES, FACTUAL; DOCUMENTATION; INFORMATION STORAGE AND RETRIEVAL; NATURAL LANGUAGE PROCESSING; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED; SPEECH RECOGNITION SOFTWARE; TELECOMMUNICATIONS; USER-COMPUTER INTERFACE; VOCABULARY, CONTROLLED;

EID: 26844449436     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2005.850153     Document Type: Article

References (23)

1. Ericsson Enterprise. The Path to the Mobile Enterprise. [Online]. Available: http://www.ericsson.com/products/whitepapers_pdf/ whitepaper_mobile_enterprise_rc.pdf.
2. IBM. (2001) IBM WebSphere voice server gives voice to e-business applications. [Online]. Available: http://www-3.ibm.com/software/ pervasive/products/pdf/WebSphere_VS_SS_PageView.pdf.
3. M. A. Hearst, "Text data mining: issues, techniques, and the relationship to information access," presented at the UW/MS Workshop on Data Mining, 1997.
4. K. Lang, "NewsWeeder: learning to Ffilter news," presented at the Int. Conf. Machine Learning, Tarragona, Spain, 1995.
5. S. Deerwester, S. T. Dmais, G. W. Fumas, T. K. Landauer, and R. Harshman, "Indexing by latent semantic analysis," J. Amer. Soc. Inf. Sci., vol. 41, no. 6, pp. 391-407, 1990.
6. S. T. Dumais, "Using LSI for information filtering: TREC-3 experiments," in Proc. 3rd Text Retrieval Conf. (TREC3), Gaithersburg, MD, 1995, pp. 500-525.
7. M. L. Littman and G. A. Keim, "Cross-language text retrieval with three languages," presented at the Int. Conf. Neural Information Processing Systems. Breckenridge, CO, 1997.
8. J. I. Hung. (2000) An overview of latent semantic indexing. [Online]. Available: http://www.cs.berkeley.edu/~jasonh/classes/sims240/ sims240-final-paper-lsi_files/sims-240-final-paper-lsi.doc.
9. I. S. Dhillon, J. Fan, and Y. Guan, "Efficient clustering of very large document collections," in Data Mining for Scientific and Engineering Applications, R. Grossman, G. Kamath, and R. Nabum, Eds. Dordrecht, The Netherlands: Kluwer, 2001.
10. I. S. Dhillon and D. S. Modha, "Concept decompositions for large sparse text data using clustering," Mach. Learn., vol. 42, no. 1, pp. 143-175, 2001.
11. J. A. Hartigan and M. A. Wong, "A K-means clustering algorithm," Appl. Statist., vol. 28, pp. 100-108, 1979.
12. J. G. Strehl and R. Mooney, "Impact of similarity measures on web-page clustering," in Proc. 7th Nat. Conf. Artificial Intelligence: Workshop of Artificial Intelligence for Web Search, 2000, pp. 58-64.
13. T. R. Gruber, "A translation approach to portable ontologies," Knowl. Acquisit., vol. 5, no. 2, pp. 199-220, 1993.
14. J. Sun and S.-T. Yuan, "Ontology-based task-oriented audio mining for Mobile B2E applications," Inf. Manage. Dept., Fu Jen Catholic Univ., Taipei, Taiwan, R.O.C., Tech. Rep., 2003.
15. S.-T. Yuan and K. J. Lin, "WISE - Building simple intelligence into e-commerce," presented at the Int. Conf. Web Intelligence, Halifax, NS, Canada, 2003.
16. D. Jimenez, C. F. Engnix, and V. Vidal, "A comparison of experiments with the bisecting-spherical K-means clustering and SVD algorithms," presented at the Workshop on Processing and Information Retrieval, Valencia, Spain, 2002.
17. E. J. Glover, K. Tsioutsiouliklis, S. Lawrence, D. M. Pennock, and G. W. Flake, "Using web structure for classifying and describing web pages," presented at the WWW Conf., Honolulu, HI, 2002.
18. P. Sinka, M. Corne, and D. W. Corne, "Evolving document features for web document clustering: A feasibility study," presented at the IEEE Congr. Evolutionary Computation, Portland, OR, 2004.
19. G. Salto and M. J. McGill, An Introduction to Modern Information Retrieval. New York: McGraw-Hill, 1983.
20. J. Sedding and D. Kazakov, "WordNet-Based text document clustering," presented at the 3rd Workshop on Robust Methods in Analysis of Natural Language Data (ROMAND), Geneva, Switzerland, 2004.
21. P. Resnik and D. Yarowsky, "Distingnishing systems and distinguishing senses: New evaiuatioumethods for word sense disambiguation," Nat. Lang. Eng., vol. 5, no. 2, pp. 113-133, 2000.
22. N. Poso. (2004, Sep.) The cost of knowledge management. [Online]. Available: http://itmatters.com.ph/column/poso_09132004.html.
23. I. S. Dhillon, Y. Guan, and J. Kogan, "Iterative clustering of high dimensional text data augmented by locasearch," presented at the IEEE Int. Conf. Data Mining, Maebashi City, Japan, 2002.