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A Semi-supervised Approach for Key-Synset Extraction to Be Used in Word Sense Disambiguation

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Information Retrieval Technology (AIRS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7097))

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Abstract

Nowadays, although many researches is being done in the field of word sense disambiguation in some languages like English, still some other languages like Persian have many things to be done. Some difficulties are in this way which might have made it less interactive for researchers. For example, Persian WordNet or FarsNet is newly developed and there is no sense tagged corpus developed based on it yet. So we propose a semi-supervised approach for extending FarsNet with some new relations and then use it for WSD. Also a method to extract semantic keywords or key-concepts from textual documents is used. As the key-concepts are extracted exploiting FarsNet, we call them Key-synsets. In fact Key-synsets of a document are those synsets which are semantically related to the main subjects of that document. This method is exploited to improve the precision of the proposed WSD. Although our approach is tested on Persian it can be easily adopted for other languages such as English.

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Author information

Authors and Affiliations

  1. NLP Research Lab, Faculty of ECE, Shahid Beheshti University, Tehran, Iran

    Maryam Haghollahi & Mehrnoush Shamsfard

Authors
  1. Maryam Haghollahi
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  2. Mehrnoush Shamsfard
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Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Engineering, University of Wollongong, Dubai Knowledge Village, P.O. Box 20182, Dubai, United Arab Emirates

    Mohamed Vall Mohamed Salem

  2. Faculty of Engineering and IT, Dubai International Academic City, Block 11, 1st and 2nd Floor, P.O. Box 345015, Dubai, United Arab Emirates

    Khaled Shaalan

  3. Faculty of Computer Science and Engineering, University of Wollongong, Dubai Knowledge Village, P.O. Box 20183, Dubai, United Arab Emirates

    Farhad Oroumchian

  4. Department of Electrical and Computer Engineering, University of Tehran, Faculty of Engineering, North Kargar Street, P.O. Box 14395-515, Tehran, Iran

    Azadeh Shakery

  5. Faculty of Computer Science and Engineering, University of Wollongong, Dubai knowledge Village, P.O. Box 20183, Dubai, United Arab Emirates

    Halim Khelalfa

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© 2011 Springer-Verlag Berlin Heidelberg

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Haghollahi, M., Shamsfard, M. (2011). A Semi-supervised Approach for Key-Synset Extraction to Be Used in Word Sense Disambiguation. In: Salem, M.V.M., Shaalan, K., Oroumchian, F., Shakery, A., Khelalfa, H. (eds) Information Retrieval Technology. AIRS 2011. Lecture Notes in Computer Science, vol 7097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25631-8_54

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  • DOI: https://doi.org/10.1007/978-3-642-25631-8_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25630-1

  • Online ISBN: 978-3-642-25631-8

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