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Tytuł artykułu

Evaluation of Sentence-Selection Text Summarization Methods on Polish News Articles

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents the goals, results and conclusions from an experiment in which several shallow text summarization methods have been applied to news articles written in Polish. Specifically, we focused on various techniques of salient sentence selection, as these algorithms are most popular in the English-speaking world and are computationally efficient. The quality of automatically generated summaries was evaluated by comparing them against a reference set of man-made summaries. This reference set of summaries is a valuable resource on its own, as it comes from a survey where user groups from different backgrounds had been asked to select "the most appropriate" set of sentences to form a generic, informative summary.
Rocznik
Strony
27--41
Opis fizyczny
Bibliogr 21 poz.
Twórcy
autor
autor
  • Poznan Supercomputing and Networking Center, ul. Noskowskiego 10, 61-704 Poznań, Poland
Bibliografia
  • [1] Alonso, L., Castellón, I., Climent, S., Fuentes, M., Padró, L., and Rodriquez, H. Approaches to text summarization: Question and answers. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 22 (2003), 79-102.
  • [2] Baeza-Yates, R. A., and Ribeiro-Neto, B. Modem Information Retrieval Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1999.
  • [3] Barzilay, R., and Elhadad, M. Using lexical chains for text summarization. Inteligent Scalable Text Summarization Workshop (ISTS'97) (1997), 10-17.
  • [4] Brandow, R., Mitze, K., and Rau, L. F. Automatic condensation of electronic publications by sentence selection. Inf. Process. Manage. 31, 5 (1995), 675-685.
  • [5] Branny, E., and Gajęcki, M. Text summarizing in Polish. Computer Science 7, 2 (2005), 31-48.
  • [6] Ciura, M., Grund, D., Kulików, S., and Suszczańska, N. A System to Adapt Techniques of Text Summarizing to Polish. International Journal of Computational Intelligence 1, 4 (2005), 259-262.
  • [7] Dalianis, H. SweSum - A Text Summarizer for Swedish. Available on-line [07/2009]: http: //people.dsv.su.se/~hercules/papers/Textsumsummary.html, 2000.
  • [8] Dudczak, A., Stefanowski, J., and Weiss, D. Automatyczna selekcja zdań dla tekstów prasowych w języku polskim (Automatic sentence selection for Polish newspaper texts.). Technical Report RA-03/08, Institute of Computing Science, Poznan University of Technology, Poland, 2008.
  • [9] Klopotek, M. A., Ciesielski, K., Czerski, D., Dramiński, M., and Wierzchoń, S. T. BEATCA: map-based intelligent navigation in WWW. In Proceedings of 12th International Conference on Artificial Intelligence: Methodology, Systems, Applications, Varna, Bulgaria (13th-15th September 2006) (2006), vol. 4183 of LNAI, pp. 245-254.
  • [10] Kupiec, J., Pederson, J., and Chen, F. A trainable document summarizer. In Proceedings of the 18th ACM-SIGIR Conference (1995), pp. 68-73.
  • [11] Mani, I. Automatic Summarization, vol. 3 of Natural Language Processing. John Benjamins Publishing Company, Amsterdam/Philadelphia, June 2001.
  • [12] Mann, W. C., and Thompson, S. A. Rhetorical structure theory: Toward a functional theory of text organization. Text 8, 3 (1988), 243-281.
  • [13] Morris, J., and Hirst, G. Lexical cohesion computed by thesaural relations as an indicator of the structure of text. Comput. Linguist. 17, 1 (1991), 21-48.
  • [14] Perez-Breva, L., and Yoshimi, O. Model selection in summary evaluation. Tech. Rep. AI Memo 2002-023, Massachusetts Institute of Technology, AI laboratory, 2002.
  • [15] Piasecki, M., and Radziszewski, A. Polish morphological guesser based on a statistical a tergo index. In Proceedings of the International Multiconference on Computer Science and Information Technology - 2nd International Symposium Advances in Artificial Intelligence and Applications (2007), pp. 247-256.
  • [16] Rath, G. J., Resnick, A., and Savage, T. R. The formation of abstracts by the selection of sentences. American Documentation 2, 12 (1961), 139-143.
  • [17] Spärck Jones, K. Automatic summarising: Factors and directions. In Advances in Automatic Text Summarisation, I. Mani and M. Maybury, Eds. MIT Press, Cambridge MA, 1998.
  • [18] Spärck Jones, K. Automatic summarising: The state of the art. Inf. Process. Manage. 43, 6 (2007), 1449-1481.
  • [19] Spärck Jones, K., Walker, S., and Robertson, S. E. A probabilistic model of information retrieval: development and comparative experiments, part 2. Information Processing and Management 36, 6 (2000), 809-840.
  • [20] Weiss, D. Descriptive Clustering as a Method for Exploring Text Collections. PhD thesis, Poznan University of Technology, Poznan, Poland, 2006.
  • [21] Zechner, K. A literature survey on information extraction and text summarization. Available on-line [07/2009]: http://www.csi.uottawa.ca/tanka/ArtDB/infoextr.ps.gz, 1996.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPP2-0019-0036
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