Ontology-based Query Expansion for Arabic Text Retrieval

Alromima, Waseem; Moawad, Ibrahim F.; Elgohary, Rania; Aref, Mostafa

doi:10.14569/ijacsa.2016.070830

Cited by 9 publications

(9 citation statements)

References 17 publications

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“…Ontology is useful in query expansion because it provides a means for discovering unstated concepts that can be used to expand the initial user query. Early works have explored the use of ontology in query expansion techniques that have been extended eventually in different ways, such as domain-specific ontology [5][6][7], general ontology [8][9] and linguistic expansion [10][11].…”

Section: Related Workmentioning

confidence: 99%

Sensual Semantic Analysis for Effective Query Expansion

Raza¹,

Rahmah²,

Noraziah³

et al. 2018

ijacsa

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The information has evolved rapidly over the World Wide Web in the past few years. To satisfy information needs, users mostly submit a query via traditional search engines, which retrieve results on the basis of keyword matching principle. However, a keyword-based search cannot recognize the meanings of keywords and the semantic relationship among the terms in the user's query; thus, this technique cannot retrieve satisfactory results. The expansion of an initial query with relevant meaningful terms can solve this issue and enhance information retrieval. Generally, query expansion methods consider concepts that are semantically related to query terms within the ontology as candidates in expanding the initial query. An analysis of the correct sense of query terms, rather than only considering semantic relations, is necessary to overcome language ambiguity problems. In this work, we proposed a query expansion framework on the basis of query sense analysis and semantics mining using computer science domain ontology, followed by working prototype of the system. The experts analyzed the results of system prototype over test dataset and Web data, and found a remarkable improvement in the overall search performance. Furthermore, the proposed framework demonstrated better mean average precision and recall values than the baseline method.

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Section: Related Workmentioning

confidence: 99%

Sensual Semantic Analysis for Effective Query Expansion

Raza¹,

Rahmah²,

Noraziah³

et al. 2018

ijacsa

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show abstract

“…These words don't give any hint for the content of their documents. In information retrieval systems, stop-words should be eliminated (by referring to a stop-word list) from the query text and from the set of index terms [18,20]. Figure 3 shows the tokens of a document title after removing the stop-words.…”

Section: ) Removal Of Stop-wordsmentioning

confidence: 99%

“…To facilitate the matching process, a matching model is used. In this paper, the Vector Space Model (VSM) is used for the matching operation [18,20,[27][28][29][30][31][32]. The VSM is an algebraic model where it uses non-binary weights that are assigned to the index terms of documents and queries.…”

Section: Matching and Rankingmentioning

confidence: 99%

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Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification

Elnahaas

El-Fishawy

Elsayed

et al. 2018

The Egyptian Journal of Language Engineering

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Information retrieval aims to find all relevant documents responding to a query from textual data. A good information retrieval system should retrieve only those documents that satisfy the user query. Although several models were developed, most of Arabic information retrieval models do not satisfy the user needs. This is because the Arabic language is more powerful and has complex morphology as well as high polysemy. This paper first investigates the most recent Arabic information retrieval model and then presents two different approaches to enhance the effectiveness of the adopted model. The main idea of the proposed approaches is to modify and/or expand the user query. The first approach expands user query by using semantics of words according to an Arabic dictionary. The second approach modifies and/or expands user query by adding some useful information from the pseudo relevance feedback. In other words, the query is modified by selecting relevant textual keywords for expanding the query and weeding out the non-related textual words. The adopted retrieval model and the two proposed approaches are implemented, tested, compared, and evaluated considering Arabic document collection. The obtained results show that the proposed approaches enhance the effectiveness of the Arabic information retrieval model by about 15% to 35%.

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“…Language Research Group University of Leeds [10,14] has developed 'The Quranic Arabic Corpus' which is focused on linguistic resource based on Arabic grammar, syntax and morphology for each word in the Holy Quran, however, a description of the concepts are insufficient especially in performing semantic search [15]. In [17] has introduced semantic-based retrieval system for the Arabic text, which will expand input query semantically for Arabic domain ontology. In [11] constructed an ontology that related to prayer in the Quran, and in [12] developed an ontology of semantic lexicons of Arabic that focuses on verses related to 'time'.…”

Section: Quranic Ontology Examplesmentioning

confidence: 99%

Retrieval Performance for USIM's Quranic Search Engine

Basir¹,

Nabila²,

Zaizi³

et al. 2018

IJET

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The Quran covers every field of life namely medical, political, social, economic, and others. The extraction of quranic knowledge is a challenging task, as the Quran is rich in its linguistic and multi-layered meanings, difficult if done without the use of other resources such as the Hadith and Tafsir by Muslim Scholars. Several Quranic ontologies have been developed, however, most of these only focus on certain domains and language, rather than the content of the Quran. In many cases, the searching cannot retrieve the relevant fields. Discovering the fields of a keyword searched in the Quran can become a guidance to enhance knowledge in a particular domain. In this paper, we propose that the keyword searched in the Quranic ontology can be applied for extracting the relevant fields. For this purpose, exploratory search has been done. The sample domain ontology based on the medical and economic fields mentioned in the Quran has been developed in TopBraid Composer. Queries have been run to depict the proper role of ontology. Then, certain recommendation for the proposed Quranic ontology attaining semantic search from all domains and the result by searching from verse to domain, or domain to verse, has been proposed.

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Ontology-based Query Expansion for Arabic Text Retrieval

Cited by 9 publications

References 17 publications

Sensual Semantic Analysis for Effective Query Expansion

Sensual Semantic Analysis for Effective Query Expansion

Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification

Retrieval Performance for USIM's Quranic Search Engine

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