Multidocument summarization: An added value to clustering in interactive retrieval

ACM Transactions on Information Systems

Volumn 22, Issue 2, 2004, Pages 215-241

  Maña López, Manuel J ^a,c   De Buenaga, Manuel ^b   Gómez Hidalgo, José M ^b  

^a UNIVERSITY OF VIGO   (Spain)

^b UNIVERSIDAD EUROPEA DE MADRID   (Spain)

^c UNIVERSITY OF HUELVA   (Spain)

Author keywords

Multidocument summarization; Topic segmentation

Indexed keywords

CLUSTERING ALGORITHMS; CLUSTERING TECHNIQUES; MULTIDOCUMENT SUMMARIZATION; TOPIC SEGMENTATION;

ALGORITHMS; DATABASE SYSTEMS; INFORMATION RETRIEVAL SYSTEMS; INTERFACES (COMPUTER); PROBABILITY; PROBLEM SOLVING; QUERY LANGUAGES; SEARCH ENGINES;

INFORMATION RETRIEVAL;

EID: 3042785005     PISSN: 10468188     EISSN: None     Source Type: Journal    
DOI: 10.1145/984321.984323     Document Type: Article

References (42)

1. ABRAÇOS, J. AND LOPES, G. P. 1997. Statistical methods for retrieving most significant paragraphs in news paper articles. In Proceedings of the Workshop on Intelligent Scalable Text Summarization at the 35th Meeting of the Association for Computational Linguistics, and the 8th Conference of the European Chapter of the Assocation for Computational Linguistics (Madrid, Spain). I. Mani and M. T. Maybury, Eds.
2. ANDO, R., BOGURAEV, B., BYRD, R., AND NEFF, M. 2000. Multidocument summarization by visualizing topical content. In Proceedings of the Workshop on Automatic Summarization at the 6th Applied Natural Language Processing Conference and the 1st Conference of the North American Chapter of the Association for Computational Linguistics (Seattle, Wash.).
3. BAXENDALE, P. B. 1958. Man-made index for technical literature - An experiment. IBM J. Res. Develop. 2, 4, 354-361.
4. BUCKLEY, C. 1985. Implementation of the Smart information retrieval system. Tech. Rep. 85-686. Cornell University.
5. CAREY, M., KRIWACZEK, F., AND RÜGER, S. 2000. A visualization interface for document searching and browsing. In Proceedings of CIKM 2000 Workshop on New Paradigms in Information Visualization and Manipulation (Washington, D.C.).
6. EDMUNDSON, H. P. 1969. New methods in automatic extracting. J. ACM 16, 2 (Apr.), 264-285.
7. FULLER, M., KASZKIEL, M., NG, C., WU, M., ZOBEL, J., KIM, D., ROBERTSON, J., AND WILKINSON, R. 1998. Ad hoc, speech, and interactive tracks at MDS/CSIRO. In Proceedings of the 7th Text REtrieval Conference (TREC-7) (Gaithersburg, Md.). 465-474.
8. GOLDSTEIN, J., MITTAL, V. O., CARBONELL, J., AND CALLAN, J. P. 2000. Creating and evaluating multidocument sentence extract summaries. In Proceedings of the 9th ACM International Conference on Information and Knowledge Management (CIKM) (Washington, D.C.). ACM, New York, 165-172.
9. HEARST, M. A. 1997. TextTiling: Segmenting text into multi-paragraph subtopic passages. Computat. Ling. 23, 1, 33-64.
10. HEARST, M. A. AND PEDERSEN, J. O. 1996. Reexamining the cluster hypothesis: Scatter/gather on retrieval results. In Proceedings of the 19th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval (Zurich, Switzerland). ACM, New York, 76-84.
11. HERSH, W. AND OVER, P. 1999. TREC-8 interactive report. In Proceedings of the 8th Text REtrieval Conference (TREC-8) (Gaithersburg, Md.). 57-64.
12. JABDINE, N. AND VAN RIJSBERGEN, C. J. 1971. The use of hierarchic clustering in information retrieval. Inf. Star. Ret. 7, 217-240.
13. KAN, M., MCKEOWN, K. R., AND KLAVANS, J. L. 2001. Domain-specific informative and indicative summarisation for information retrieval. In Proceedings of the Workshop on Text Summarization, 24th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval (New Orleans, La.). ACM, New York.
14. KARYPIS, G. 2002. Cluto: A Software Package for Clustering High Dimensional Datasets. Release 1.5. Department of Computer Science, University of Minnesota.
15. KRISHNAIAH, P. R. AND KANAL, L. 1982. Classification, Pattern Recognition and Reduction in Dimensionality: Handbook of Statistics. Vol. 2. North-Holland Publishing Company, Amsterdam, The Netherlands.
16. LEUSKI, A. 2001. Evaluating document clustering for interactive information retrieval. In Proceedings of 10th International Conference on Information and Knowledge Management (CIKM'01). 33-40.
17. LUHN, H. P. 1958. The automatic creation of literature abstracts. IBM J. Res. Develop. 2, 2, 159-165.
18. MAÑA-LÓPEZ, M. J., DE BUENAGA, M., AND GÓMEZ-HIDALGO, J. M. 1999. Using and evaluating user directed summaries to improve information access. In Proceedings of the 3rd European Conference on Research and Advanced Technology for Digital Libraries (ECDL'99) (Paris, France). Springer-Verlag, New York, 198-214.
19. MANI, I. 2001. Automatic Summarization. John Benjamins Publishing Company, Amsterdam/ Philadephia.
20. MITTAL, V. O., KANTROWITZ, M., GOLDSTEIN, J., AND CARBONELL, J. 1999. Selecting text spans for document summaries: heuristics and metrics. In Proceedings of the Conference of the American Association of Artificial Intelligence (AAAI'99).
21. NAKAO, Y. 2000. An algorithm for one-page summarization of a long text based on thematic hierarchy detection. In Proceedings of the 38th Meeting of the Association for Computational Linguistics. 302-309.
22. OVER, P. 1997. TREC-6 interactive report. In Proceedings of the Sixth Text REtrieual Conference (TREC-6) (Gaithersburg, Md.). 73-82.
23. OVER, P. 1998. TREC-7 interactive track report. In Proceedings of the Seventh Text REtrieval Conference (TREC-7) (Gaithersburg, Md.). 65-72.
24. PAICE, C. D. 1990. Constructing literature abstracts by computer: Techniques and prospects. Inf. Proc. Manage. 26, 1, 171-186.
25. RADEV, D. R., JING, H., AND BUDZIKOWSKA, M. 2000. Centroid-based summarization of multiple documents: Sentence extraction, utility-based evaluation, and user studies. In Proceedings of the Workshop on Automatic Summarization at the 6th Applied Natural Language. Processing Conference and the 1st Conference of the North American Chapter of the Association for Computational Linguistics (Seattle, Wash.).
26. RASMUSSEN, E. 1992. Clustering algorithms. In Information Retrieval: Data Structures & Algorithms, W. Frakes and R. Baeza-Yates, Eds. Prentice-Hall International, London, England, 419-442.
27. RÜGER, S. AND GAUCH, S. E. 2000. Feature reduction for document clustering and classification. Tech. Rep. DTR 2000/8. Department of Computing, Imperial College, London, England.
28. SAHAMI, M. 1998. Using machine learning to improve information access. Ph.D. dissertation. Computer Science Department, Stanford Univ., Stanford Calif.
29. SALTON, G. 1968. Automatic Information Organization and Retrieval. McGraw-Hill, New York.
30. SALTON, G., ALLAN, J., AND SINGHAL, A. 1996. Automatic text decomposition and structuring. Inf. Proc. Manage. 32, 2, 127-138.
31. SALTON, G. AND BUCKLEY, C. 1988. Term-weighting approaches in automatic text retrieval. Inf. Proc. Manage. 24, 5, 513-523.
32. SALTON, G., SINGHAL, A., MITRA, M., AND BUCKLEY, C. 1997. Automatic text structuring and summarization. Inf. Proc. Manage. 33, 2, 193-207.
33. SKOHOCHOD'KO, E. F. 1972. Adaptive method of automatic abstracting and indexing. In Information Processing 71: Proceedings of the IFIP Congress 71, C. Freiman, Ed. North-Holland, Amsterdam, The Netherlands, 1179-1182.
34. SPINK, A., JANSEN, B., WOLFRAM, D., AND SARACEVIC, T. 2002. From e-sex to e-commerce: Web search changes. Computer 35, 3, 107-109.
35. STEINBACH, M., KARYPIS, G., AND KUMAR, V. 2000. A comparison of document clustering techniques. In Proceedings of the KDD Workshop on Text Mining.
36. TOMBROS, A. AND SANDERSON, M. 1998. Advantages of query biased summaries in information retrieval. In Proceedings of the 21st Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval (Melbourne, Australia). ACM, New York, 2-10.
37. VAITHYANATHAN, S. AND DOM, B. 1999. Model selection in unsupervised learning with applications to document clustering. In Proceedings of the 16th International Conference on Machine Learning (ICML-99) (Bled, Slovenia).
38. VAN RIJSBERGEN, C. J. 1979. Information Retrieval, 2nd ed. Buttersworth, London.
39. WITTEN, I. H. AND FRANK, E. 1999. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan-Kaufmann, San Mateo, Calif.
40. WU, M., FULLER, M., AND WILKINSON, R. 2001. Using clustering and classification approaches in interactive retrieval. Inf. Proc. Manage. 37, 3, 459-484.
41. ZAMIR, O. AND ETZIONI, O. 1998. Web document clustering: a feasibility demonstration. In Proceedings of the 21st Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval (Melbourne, Australia). 46-54.
42. ZHAO, Y. AND KARYPIS, G. 2001. Criterion functions for document clustering: Experiments and analysis. Tech. Rep. 01-40, Department of Computer Science, University of Minnesota.