Arabic information retrieval: A relevancy assessment survey

Ahmad Hussein Ababneh, Joan Lu, Qiang Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


The paper presents a research in Arabic Information Retrieval (IR). It surveys the impact of statistical and morphological analysis of Arabic text in improving Arabic IR relevancy. We investigated the contributions of Stemming, Indexing, Query Expansion, Text Summarization (TS), Text Translation, and Named Entity Recognition (NER) in enhancing the relevancy of Arabic IR. Our survey emphasizing on the quantitative relevancy measurements provided in the surveyed publications. The paper shows that the researchers achieved significant enhancements especially in building accurate stemmers, with accuracy reaches 97%, and in measuring the impact of different indexing strategies. Query expansion and Text Translation showed positive relevancy effect. However, other tasks such as NER and TS still need more research to realize their impact on Arabic IR.

Original languageEnglish
Title of host publication25th International Conference on Information Systems Development, ISD 2016
PublisherAssociation for Information Systems
Number of pages13
ISBN (Electronic)9788378753070
Publication statusPublished - 2016
Event25th International Conference on Information Systems Development: Complexity in Information Systems Development - University of Economics , Katowice, Poland
Duration: 24 Aug 201626 Aug 2016
Conference number: 25 (Link to Conference Details)


Conference25th International Conference on Information Systems Development
Abbreviated titleISD 2016
Internet address


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