Abstract
Given the steady increase of published and stored information in the form of Arabic unstructured texts, current Information Retrieval (IR) systems must be able to suit the nature and requirements of this language for an accurate and efficient search. This paper sheds light on the challenges in Arabic IR (AIR) and proposes an approach for enhancing the process of AIR based on transforming these texts into structured documents in XML format through a document ontology as well as a set of linguistic grammars. The IR system hence is done on the XML documents. The aim of such system is to incorporate the knowledge on the document structure and on specific content elements in computing the relevance of an information element. A query expansion module mainly based on domain ontology as well as user profile is proposed for the enhancement of the search results.
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References
Atwan, J., Mohd, M., Rashaideh, H., Kanaan, G.: Semantically enhanced pseudo relevance feedback for arabic information retrieval. J. Inf. Sci. 42(2), 246–260 (2016)
Hanandeh, E., Mabreh, K.: Effective information retrieval method based on matching adaptative genetic algorithm. J. Theoret. Appl. Inf. Technol. 81(3), 446–452 (2015)
Ibrahim, H., Abdou, S., Gheith, M.: Idioms-proverbs lexicon for modern standard arabic and colloquial sentiment analysis. Int. J. Comput. Appl. 118(11), 26–31 (2015)
Keskes, I., Benamara, F., Belguith, L.H.: Clause-based discourse segmentation of arabic texts. In: Proceedings of the Eight International Conference on Language Resources and Evaluation, LREC 2012, Istanbul, Turkey, pp. 2826–2832 (2012)
Mahgoub, A., Rashwan, M., Raafat, H., Zahran, M., Fayek, M.: Semantic query expansion for arabic information retrieval. In: Proceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing (ANLP), Doha, Qatar, pp. 87–92 (2014)
Maitah, W., Al-Rababaa, M., Kannan, G.: Improving the effectiveness of information retrieval system using adaptive genetic algorithm. Int. J. Comput. Sci. Inf. Technol. 5(5), 91–105 (2013)
Mohamed, A.: Design of arabic dialects information retrieval model for solving regional variation problem. Thesis, Sudan University of Science and Technology, Sudan (2015)
Yousef, N., Abu-Errub, A., Odeh, A., Khafajeh, H.: An improved arabic words roots extraction method using n-gram technique. J. Comput. Sci. 10(4), 716–719 (2014)
Yousef, N., Khafajeh, H.: Evaluation of different query expansion techniques by using different similarity measures in arabic documents. Int. J. Comput. Sci. Inf. Technol. 10(4), 160–166 (2013)
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Mezghanni, I.B., Gargouri, F. (2016). Information Retrieval from Unstructured Arabic Legal Data. In: Booth, R., Zhang, ML. (eds) PRICAI 2016: Trends in Artificial Intelligence. PRICAI 2016. Lecture Notes in Computer Science(), vol 9810. Springer, Cham. https://doi.org/10.1007/978-3-319-42911-3_4
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DOI: https://doi.org/10.1007/978-3-319-42911-3_4
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