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Linguistically Enhanced Collocate Words Model

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Book cover Information Retrieval Technology (AIRS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8870))

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Abstract

Bag-of-word (BOW) or fixed size window approach for word extraction in natural language text has ignored text structure and context information. Similarly, word co-occurrence based on linear word proximity has also ignored the linguistic criteria of words. This paper aims to propose a semantic window of word to address the needs to provide a context for capturing the structure and context of word in a sentence for analysis. The semantic window of word has linguistic elements which can be injected for collocate word identification. Selected data has been used as case studies. Quantitative analysis has been conducted as well. The proposed approach is evaluated and compared to sliding window which is the baseline. Semantic window is found to perform better than sliding window for linguistically enhanced collocate word extraction.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, University Malaysia Sarawak, Kuching, Malaysia

    Siaw Nyuk Hiong, Bali Ranaivo-Malançon, Narayanan Kulathuramaiyer & Jane Labadin

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  1. Siaw Nyuk Hiong
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  2. Bali Ranaivo-Malançon
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  3. Narayanan Kulathuramaiyer
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  4. Jane Labadin
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Editor information

Editors and Affiliations

  1. Institute of Visual Informatic, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Azizah Jaafar

  2. Institute of Visual Informatics, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Nazlena Mohamad Ali

  3. Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Shahrul Azman Mohd Noah

  4. Insight Centre for Data Analytics, Dublin City University, Glasnevin, 9, Dublin, Ireland

    Alan F. Smeaton

  5. Information Systems, Queensland University of Technology, 4001, Brisbane, QLD, Australia

    Peter Bruza

  6. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia

    Zainab Abu Bakar  & Nursuriati Jamil  & 

  7. Cyber Security Center, Universiti Pertahanan Nasional Malaysia, Kem Sungai Besi, 57000, Kuala Lumpur, Malaysia

    Tengku Mohd Tengku Sembok

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Hiong, S.N., Ranaivo-Malançon, B., Kulathuramaiyer, N., Labadin, J. (2014). Linguistically Enhanced Collocate Words Model. In: Jaafar, A., et al. Information Retrieval Technology. AIRS 2014. Lecture Notes in Computer Science, vol 8870. Springer, Cham. https://doi.org/10.1007/978-3-319-12844-3_20

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  • DOI: https://doi.org/10.1007/978-3-319-12844-3_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12843-6

  • Online ISBN: 978-3-319-12844-3

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