Semantic Similarity Analysis for Corpus Development and Paraphrase Detection in Arabic

Semantic Similarity Analysis for Corpus Development and Paraphrase Detection in Arabic

Adnen Mahmoud1,2, and Mounir Zrigui1

1University of Monastir, Research Laboratory in Algebra, Numbers Theory and Intelligent Systems RLANTIS, Tunisia

2University of Sousse, Higher Institute of Computer Science and Communication Techniques ISITCom, Tunisia

Abstract: Paraphrase detection allows determining how original and suspect documents convey the same meaning. It has attracted attention from researchers in many Natural Language Processing (NLP) tasks such as plagiarism detection, question answering, information retrieval, etc., Traditional methods (e.g., Term Frequency-Inverse Document Frequency (TF-IDF), Latent Dirichlet Allocation (LDA), and Latent Semantic Analysis (LSA)) cannot capture efficiently hidden semantic relations when sentences may not contain any common words or the co-occurrence of words is rarely present. Therefore, we proposed a deep learning model based on Global Word embedding (GloVe) and Recurrent Convolutional Neural Network (RCNN). It was efficient for capturing more contextual dependencies between words vectors with precise semantic meanings. Seeing the lack of resources in Arabic language publicly available, we developed a paraphrased corpus automatically. It preserved syntactic and semantic structures of Arabic sentences using word2vec model and Part-Of-Speech (POS) annotation. Overall experiments shown that our proposed model outperformed the state-of-the-art methods in terms of precision and recall.

Keywords: Arabic language processing, word2vec, part-of-speech annotation, paraphrasing, semantic analysis, recurrent convolutional neural networks.

Received January 24, 2019; accepted February 5, 2020

https://doi.org/10.34028/iajit/18/1/1

Full Text


Last modified on Wednesday, 20 January 2021 11:56
Share:

Upcoming courses

  • Diploma Courses
  • Business and Enterprise
  • Digital Literacy & IT
  • Health Literacy
  • Business Literacy

Free courses

Starting from Jun. 14 2016

the degree finder

in 3 easy steps
Top
We use cookies to improve our website. By continuing to use this website, you are giving consent to cookies being used. More details…