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Information and Communication Technology pp 289–297Cite as

Information Extraction Approaches: A Survey

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 625))

Abstract

In the recent years, the amount of available information in the Web is growing. Thereby, the search of pertinent information through those large documents has become a difficult task. That’s why, we need to develop information extraction systems in order to facilitate the treatment and the representation of data according to the user’s need. These systems should adopt an extraction approach for its implementation. In this paper, we provide an overview of the basic information extraction (IE) approaches used in the developed systems. We survey a specific class of IE approaches based on semantics, due to the importance of semantic processing of the data.

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References

  1. R Gishman, “Information extraction: Techniques and challenges.” In: Pazienza, M.T. (ed.) Information Extraction: A Multidisciplinary Approach to an Emerging Information Technology. Berlin, Heidelberg: Springer-Verlag, pp. 10–27, 1997.

    Google Scholar 

  2. E. Douglas, Appelt, R. Jerry, Hobbs, J. Bear, D. Israel, and M. Tyson “FASTUS: A Finite- state Processor for Information Extraction from Real-world Text.,” In Proc. 13th Int’l Joint Conf. Artificial Intelligence (LJCAI-93), pages 1172–1178. 1993.

    Google Scholar 

  3. L. Eikvil,. “Information Extraction from World Wide Web A Survey”. Norwegian Computing Center, ISBN: 82-539-0429-0. 1999.

    Google Scholar 

  4. J. Cowie and W. Lehnert. “Information extraction In Special natural language processing” issue of the communications of the ACM (Vol. 39, pp. 80{91}). New York, NY, USA. 1996.

    Google Scholar 

  5. W. Gatterbauer, P. Bohunsky, M. Herzog, B. Krupl, and B. Pollak. “Towards Domain independent Information Extraction from Web Tables”., Proceedings of the 16th International Conference on World Wide Web, Canada, pp. 71–80, ISBN: 978-1-59593- 654-7.2007.

    Google Scholar 

  6. E. Feigenbaum and P. McCorduck. The Fifth Generation. artificial intelligence and japan’s computer challenge to the world, Addison-Wesley.1983.

    Google Scholar 

  7. J. Fox. “Formalizing knowledge and expertise: where have we been and where are we going?”. In The Knowledge Engineering Review, 26 (1), pp. 5–10 Cambridge university press. 2011.

    Google Scholar 

  8. H. Ji,. “Information Extraction: Techniques, Advances and Challenges.” Invited Lecture at the North American Chapter of the Association for Computational Linguistics (NAACL) Summer School. 2012.

    Google Scholar 

  9. K. Kaiser and S Miksch,. “Information Extraction a Survey”. Vienna University of Technology, Institute of Software Technology and Interactive Systems, Vienna, Technical Report, Asgaard-TR 2005.

    Google Scholar 

  10. G. La Rocca, “Knowledge based engineering: Between AI and CAD”. Review of a language based technology to support engineering design. Advanced Engineering Informatics Volume 26, Issue 2, Pages 159–179 Knowledge based engineering to support complex product design 2012.

    Google Scholar 

  11. Hobbs, Appelt, E; Douglas., R. Jerry, B. John, D. Israel, M. kameyama and M. Tyson. “FASTUS: A Finite-State Processor for Information Extraction from Real-World Text”, Proceedings. IJCAI-93, Chambery, France, August 1993.

    Google Scholar 

  12. J. Miller, D. Job and V. Vassilev, “Principles in the evolutionary design of digital circuits” - part I. Genetic Programming and Evolvable Machines, 1: 7–36, April 2000.

    Google Scholar 

  13. D, Collins. “Three Generative, Lexicalized Models for Statistical Parsing. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics”, pages 16–23, Madrid, Spain 1997.

    Google Scholar 

  14. M. Ipalakova. “Information Extraction,” Initial background report, University of Manchester school of computer science. 2010.

    Google Scholar 

  15. P. Blunsom. “Maximum Entropy Markov models for semantic role labelling.” Proceedings of the Australasian Language Technology Workshop 2004. Pages 109–116. Sydney‚ Australia 2004.

    Google Scholar 

  16. A. Ratnaparkhi, “A Simple Introduction to maximum Entropy Models for Natural Language” Processing. Institute for Research in Cognitive Science IRCS Technical Reports Series. 2007.

    Google Scholar 

  17. M; Moens. “Information Extraction: Algorithms and Prospects in a Retrieval Context”. New York: Springer Netherlands. 2006.

    Google Scholar 

  18. S. Soderland, D. Fisher, J. Aseltine and W. Lehnert. 1995. CRYSTAL: inducing a conceptual dictionary. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI’95), pages 1314–1319, 1995.

    Google Scholar 

  19. Duda, O. Richard, Hart, E. Peter, Stork and G. David, “Unsupervised Learning and Clustering”, Chapter 10 in Pattern classification (2nd edition), p. 571, New York, NY: Wiley, ISBN 0-471-05669-3.2001G. O. Young, “Synthetic structure of industrial plastics,” in Plastics, 2nd ed. vol. 3, J. Peters, Ed. New York: McGraw-Hill, 1964, pp. 15–64.

    Google Scholar 

  20. E. Riloff,1996. “An Empirical Study of Automated Dictionary Construction for Information Extraction in Three Domains”, AI Journal, Vol. 85. W. D. Doyle, “Magnetization reversal in films with biaxial anisotropy,” in Proc. 1987 INTERMAG Conf., 1987, pp. 2.2-1–2.2-6.

    Google Scholar 

  21. G. Morente, Historia universal Contiene tablas cronológicas p. 609–659 • Indíce alfabético p. 661–736;1964.

    Google Scholar 

  22. FJohn. Sowa:,. “Ontology, Metadata, and Semiotics”. On Conceptual Structures: Logical Linguistic, and Computational Issues ICCS, 2000, page 55–81.2000.

    Google Scholar 

  23. Jonquet, C,. Mark A. Musen, Nigam H. Shah (2009). Help will be provided for this task: Ontology-Based Annotator Web Service. 2009.

    Google Scholar 

  24. Cimianoa, P,. Reyleb, U., Šarićc, j,. 2005. Ontology-driven discourse analysis for information extraction.

    Google Scholar 

  25. H. Saggion, A. Funk, D. Maynard,. and Bontcheva K 2007. Ontology-based Information Extraction for Business Intelligence; ISWC/ASWC 2007: 843–856.

    Google Scholar 

  26. Labsky, M,. 2008. Information Extraction from Websites using Extraction Ontologies. A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science. University of Economics Prague.

    Google Scholar 

  27. Maynard, D., Yankova, M,. Kourakis, A., Kokossis, A., Ontology-based information extraction for market monitoring and technology watch 2013.

    Google Scholar 

  28. Amit V. Deokar, Sagnika Sen, 2010 Ontology-Based Information Extraction for Analyzing IT Services. In proceeding of: Proceedings of the International Conference on Information Systems, ICIS 2010, Saint Louis, Missouri, USA.

    Google Scholar 

  29. I. Oren, EO Mann, O Paulsen, Hajos N Synaptic currents in anatomically identified CA3 neurons during hippocampal gamma oscillations in vitro. J Neurosci 26:9923–9934.2006.

    Google Scholar 

  30. Salton, G. (1971). The SMART retrieval system: Experiments in automatic document processing.

    Google Scholar 

  31. H. Prentice, Upper Saddle R, NJ. R. Baeza, Y and Ribeiro-Neto,B.1999. Modern Information Retrieval. Addison Wesley.

    Google Scholar 

  32. G. Tsatsaronis, and V. Panagiotopoulou, A Generalized Vector Space Model for Text Retrieval Based on Semantic Relatedness 2009.

    Google Scholar 

  33. J. Reisinger,. J. Raymond Mooney,. “Multi-Prototype Vector-Space Models of Word Meaning”. search engines. 2010.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Science Department, High Institute of Management, University of Tunis, Bouchoucha, Bardo-Tunis, Tunisie

    Monia Mannai & Wahiba Ben Abdessalem Karâa

  2. Computer Science Department, National School of Computer Sciences, University of Manouba, Manouba, Tunisie

    Henda Hajjami Ben Ghezala

Authors
  1. Monia Mannai
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  2. Wahiba Ben Abdessalem Karâa
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  3. Henda Hajjami Ben Ghezala
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Corresponding author

Correspondence to Monia Mannai .

Editor information

Editors and Affiliations

  1. Microsoft Innovation Centre, Sri Aurobindo Institute of Technology Microsoft Innovation Centre, Indore, Madhya Pradesh, India

    Durgesh Kumar Mishra

  2. Faculty of Computers and Information, Banha University Faculty of Computers and Information, Banha, Egypt

    Ahmad Taher Azar

  3. Sabar Institute of Technology, Asst. Prof., Dept. of Info. Tech. Sabar Institute of Technology, Gujarat, Gujarat, India

    Amit Joshi

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© 2018 Springer Nature Singapore Pte Ltd.

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Mannai, M., Karâa, W.B.A., Ghezala, H.H.B. (2018). Information Extraction Approaches: A Survey. In: Mishra, D., Azar, A., Joshi, A. (eds) Information and Communication Technology . Advances in Intelligent Systems and Computing, vol 625. Springer, Singapore. https://doi.org/10.1007/978-981-10-5508-9_28

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  • DOI: https://doi.org/10.1007/978-981-10-5508-9_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5507-2

  • Online ISBN: 978-981-10-5508-9

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