A Hybrid Multi-Word Terms Extraction System Applied to Topic Detection
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2014, Vol 13, Issue 10
Abstract
Mutli-word Terms extraction plays an important role in many Natural Language Processing (NLP) tasks. Despite their major importance, few works were dedicated to Arabic multi-word terms extraction. This paper proposes an automatic Arabic multi-word terms (MWTs) extraction system based on two major filtering steps: linguistics filter using a part-of-speech tagger along with morphological patterns and statistical filter based on probabilistic methods, namely: Log-Likelihood Ratio (LLR) and C-value. We evaluate the performances of the realized systems on Wattan; an Arabic oriented topic newspaper corpus. Our system manages to achieve 90.23% in term of multi-word extraction precision. We also study the use of MWTs as features in Arabic Topic Detection. The conducted experiments show good results.
Authors and Affiliations
Rim Koulali, Abdelouafi Meziane
Keywords
Related Articles
- EP ID EP650603
- DOI 10.24297/ijct.v13i10.2333
- Views 94
- Downloads 0
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