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A Survey to Text Summarization Methods for Turkish

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Çağdaş Can Birant, Özgün Koşaner, Özlem Aktaş

Çağdaş Can Birant, Özgün Koşaner and Özlem Aktaş. A Survey to Text Summarization Methods for Turkish. International Journal of Computer Applications 144(6):23-28, June 2016. BibTeX

	author = {Çağdaş Can Birant and Özgün Koşaner and Özlem Aktaş},
	title = {A Survey to Text Summarization Methods for Turkish},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2016},
	volume = {144},
	number = {6},
	month = {Jun},
	year = {2016},
	issn = {0975-8887},
	pages = {23-28},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2016910358},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Nowadays, people deal with a huge amount of data, especially while they are surfing on internet. So, this makes the topic of automatic summarization is very important and in the forefront. In this paper, a review for text summarization methods in Turkish is presented. Brief summary of the methods used for automatic text summarization in the literature, and also brief definitions of summary, abstraction and automatic text summarization are given.


  1. Torres-Moreno, J.-M. 2014. Automatic Text Summarization, New Jersey: Wiley-ISTE.
  2. ANSI/NISO. (1997). Guideline for Abstracts, Z39.14-1997, Maryland: Niso Press.
  3. Mani, I., Klein, G., House, D., Hirschman, L., Firmin, T. & Sundheim, B. (2002). “SUMMAC: a text summarization evaluation” in Natural Language Engineering, vol. 8 no. 1, pp. 43–68.
  4. Luhn, H. P. (1958). “The automatic creation of literature abstracts”, IBM Journal of Research and Development, vol. 2, no. 2, pp. 159–165.
  5. Radev, D.R, Hovy, E., McKeown, K. (2002). “Introduction to the Special Issue on Summarization”, Computational Linguistics, Volume 28, Number 4, 399-408.
  6. Baxendale, P. B. (1958). “Machine-made Index for Technical Literature: An Experiment”, IBM Journal of Research Developlment, vol. 2, no. 4, pp. 354–361, 1958.
  7. Vasiliev, A. (1963), “Automatic Abstracting and Indexing”, Automatic Documentation – Storage and Retrieval, UNESCO/NS/WS 1163.112, pp. 1–12, Paris.
  8. Edmundson, H. P. (1969). “New methods in automatic extraction”, Journal of the Association for Computing Machinery, vol. 16, no. 2, pp. 264–285.
  9. Rush, J. E., Salvador, R. & Zamora, A. (1971). “Automatic abstracting and indexing. II. Production of indicative abstracts by application of contextual inference and syntactic coherence criteria”, Journal of the American Society for Information Science, vol. 22, no. 4, pp. 260–274.
  10. Pollock, J.J., Zamora, A. (1975). Automatic Abstracting Research at Chemical Abstracts Service, Journal of Chemical Information and Computer Science, 15,4, pp. 226-232.
  11. DeJong, G. F. (1982). “An overview of the FRUMP system”, in W. G. Lehnert and M. H. Ringle (eds.), Strategies for Natural Language Processing, New Jersey: Lawrence Erlbaum Associates, pp. 149–176.
  12. Spärck-Jones K. (1993) “What might be in a summary?” in G. Knorz, J. Krause & C. Womser-Hacker, (eds.), Information Retrieval’93: Von der Modellierung zur Anwendung, Universitatsverlag Konstanz, Constance, Germany, pp. 9–26.
  13. Halliday, M. A. K., & Hasan, R. (1976) Cohesion in English. London: Longman.
  14. Rumelbart, D. E. (1977). Toward an interactive model of reading. In S. Dornic (Ed.), Attention and performance VI. Hillsdale, N.J.: Erlbaum, 1977.
  15. Kintsch, W. & Van Dijk, T.A. (1978). Toward a model of text comprehension and production. Psychological Review, 85 (5), 363-394.
  16. Kupiec, J., Pedersen, J. & Chen, F. (1995). “A trainable document summarizer”, 18th Conference ACM Special Interest Group on Information Retrieval (SIGIR’95), Seattle, WA, ACM Press, New York, pp. 68–73.
  17. McKeown, K. & Radev, D. R. (1995). “Generating summaries of multiple news articles”, 18th Conference ACM Special Interest Group on Information Retrieval (SIGIR ’95), Seattle, WA, ACM Press, New York, pp. 74–82.
  18. Marcu, D. (1998). The rhetorical parsing, summarization, and generation of natural language texts, PhD Thesis, Computer Science, University of Toronto, Toronto, Canada.
  19. Mann, W.C. and Thompson, S.A. (1988). Rhetorical Structure Theory: Toward a Functional Theory of Text Organization. Text 8(3): 243–81.
  20. Barzilay, R. & Elhadad, M. (1997). “Using lexical chains for text summarization”, Workshop on Intelligent Scalable Text Summarization (ACL ’97/EACL ’97), Madrid, Spain, pp. 10–17, 11 July 1997.
  21. Carbonelli, J. G. & Goldstein, J. (1998). “The use of MMR, diversity based reranking for reordering documents and producing summaries”, in A. Moffat & J. Zobel (eds.), ACM Special Interest Group on Information Retrieval (SIGIR ’98), Melbourne, Australia, pp. 335–336.
  22. Witbrock, M. J. & Mittal, V. O. (1999). “Ultra-Summarization: A Statistical Approach to Generating Highly Condensed Non-Extractive Summaries”, 22nd Conference SIGIR’99, Berkeley, CA, USA, ACM, pp. 315–316, 15–19 August 1999.
  23. Hovy, E. & Lin, C. Y. (1999). “Automated text summarization in SUMMARIST”, in I. Mani & M. T. Maybury (eds.), Advances in Automatic Text Summarization, Cambridge: MIT Press, pp. 81–94.
  24. Knight, K. and Marcu, D. 2000. Statistics-based summarization – step one: sentence compression, 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence, Austin, TX, pp. 703–10.
  25. Radev, D. R., Jing, H. & Budzikowska, M. (2000). “Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies”, Workshop on Automatic Summarization (NAACL-ANLP-AutoSum’00), Seattle, WA, ACL, pp. 21–30.
  26. Saggion, H. & Lapalme, G. (2002). “Generating indicative-informative summaries with SumUM”, Computational Linguistics, vol. 28, no. 4, pp. 497–526.
  27. Marcu, D. 2000. The Rhetorical Parsing of Unrestricted Texts: A Surface-Based Approach. Computational Linguistics, 26 (3), pp. 395-448.
  28. Erkan, G. & Radev, D. R. (2004). “LexRank: graph-based lexical centrality as salience in text summarization”, Journal of Artificial Intelligence Research, vol. 22, no. 1, pp. 457–479.
  29. Barzilay, R. & McKeown, K. R. (2005). “Sentence fusion for multidocument news summarization”, Computational Linguistics, vol. 31, no. 3, pp. 297–328.
  30. Fernández, S., SanJuan, E. & Torres-Moreno, J.-M. (2007) “Textual energy of associative memories: performants applications of Enertex algorithm in text summarization and topic segmentation”, Mexican International Conference on Artificial Intelligence (MICAI ’07), Aguascalientes: Springer-Verlag, pp. 861–871.
  31. Svore, K., Vanderwende, L. & Burges, C. J. (2007). “Enhancing single-document summarization by combining RankNet and third-party sources”, Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLPCoNLL), Prague, Czech Republic, pp. 448–457.
  32. Saggion, H. (2008). “SUMMA: A Robust and Adaptable Summarization Tool”, Traitement Automatique des Langues, vol. 49, no. 2, pp. 103–125.
  33. Filippova, K. (2010). “Multi-sentence compression: finding shortest paths in word graphs”, International Conference on Computational Linguistics (COLING ’10), Beijing, China.
  34. Nenkova, A. & McKeown, K. (2011). “Automatic summarization”, Foundations and Trends in Information Retrieval, vol. 5, nos. 2–3, pp. 103–233.
  35. Torres-Moreno, J.-M. (2012). “Artex is another text summarizer”, CoRR, vol. abs/1210.3312.
  36. Litvak, M. & Vanetik, N. (2014). “Multi-document summarization using tensor decomposition”, Computación y Sistemas (CYS), vol. 18, no. 3.
  37. Köksal A. (1981) Tümüyle Özdevimli Deneysel Bir Belge Dizinleme ve Erişim Dizgesi: TÜRDER. In the Proceedings of 3. Ulusal Bilişim Kurultayı, Ankara, Turkey, ss. 37-44.
  38. Oflazer K. and Kuruöz, İ. 1994. Tagging and morphological disambiguation of Turkish text, Proceedings of the Fourth Conference on Applied Natural Language Processing, October 13-15, Stuttgart, Germany.
  39. Tür G., Hakkani-Tür D. and Oflazer, K. 2003. A statistical information extraction system for Turkish. Natural Language Engineering, 9, pp. 181-210.
  40. Bilgin O., Çetinoğlu Ö. and Oflazer K. 2004. Building a wordnet for Turkish. Romanian Journal of Information Science and Technology, 7 (1-2), pp. 163-72.
  41. Karakaya, K. M. and Güvenir, H. A. 2004. ARG: A Tool for Automatic Report Generation, Istanbul University - Journal of Electrical & Electronics Engineering, Vol. 4, No. 2, pp. 1101-9.
  42. Amasyalı, M. F. and Diri, B. 2006. Automatic Turkish text categorization in terms of author, genre and gender. NLDB'06 Proceedings of the 11th international conference on Applications of Natural Language to Information Systems, pp. 221-6.
  43. Ercan, G. 2006. Automated Text Summarization and Keyphrase Extraction. Unpublished MSc thesis, Bilkent University.
  44. Ercan, G. and Çiçekli, İ. 2007. Using lexical chains for Keyword Extraction. Information Processing and Management, 43: 1705-14.
  45. Kutlu, M., Çığır, C. and Çiçekli, İ. 2010. Generic Text Summarization in Turkish. The Computer Journal, 53: 8, pp. 1315-23.
  46. Özsoy, M. G., Çiçekli, İ. and Alpaslan, F. N. 2010. Text summarization of Turkish texts using latent semantic analysis. Proceedings of the 23rd International Conference on Computational Linguistics, COLING’10, pp. 869-76.
  47. Uzun-Per, M. 2011. Developing a Concept Extraction System for Turkish. Unpublished MSc. Thesis, Boğaziçi University.
  48. Demir, Ş.D., El-Kahlout, İ., Ünal, E. and Kaya, H. 2012. Turkish Paraphrase Corpus. Proceedings of the Eight International Conference on Language Resources and Evaluation LREC’12. pp. 4087-91.


Text Summarization, Natural Language Processing, Turkish.