Improving Information Retrieval Results for Persian Documents using FarsNet

2018/11/01 by Adel Rahimi, Rahimi, Adel, Mohammad Bahrani +1
Computer Science · #Baseline (sea) #Computation and Language (cs.CL) #Computer science #Concept search #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Information retrieval #Linguistics #Natural Language Processing Techniques #Persian #Query expansion #Query language #Query optimization #Search engine #Semantic Web and Ontologies #Semantic query #Topic Modeling #Web search query #WordNet #cs.CL #cs.IR

paper · pdf · doi:10.48550/arxiv.1811.00854

published in arXiv (Cornell University) (Cornell University) · 4 pages

arxiv created 2018/11/01 · openalex publication_date 2018/11/01 · arxiv updated 2018/11/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

In this paper, we propose a new method for query expansion, which uses FarsNet (Persian WordNet) to find similar tokens related to the query and expand the semantic meaning of the query. For this purpose, we use synonymy relations in FarsNet and extract the related synonyms to query words. This algorithm is used to enhance information retrieval systems and improve search results. The overall evaluation of this system in comparison to the baseline method (without using query expansion) shows an improvement of about 9 percent in Mean Average Precision (MAP).

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