Design and application for the model of semantic query expansion based on domain ontology

Author(s):  
Ziyu Liu ◽  
Junxia Chen ◽  
Xuehui Li ◽  
Ying Qu ◽  
Fachao Li
2015 ◽  
Vol 731 ◽  
pp. 231-236
Author(s):  
Wu Xia Ning ◽  
Qiang Wang ◽  
Jin Kai Li ◽  
Feng Wang

Keyword-based online book retrieval can not fully understand the user's query intent. Query expansion is a typical solution, but the rate of recall and precision is still very low in existing methods. In response to these problems, this paper presents a semantic query expansion method based on domain ontology and local co-occurrence probability model. First, ontology reasoning and concepts related calculation are used to obtain the initial expansion terms. Furthermore, the local co-occurrence probability model is used to filter the candidate expansion terms and the filtering function is used for secondary selection. Experiment results show that this method can effectively improve retrieval efficiency.


2012 ◽  
Vol 2 (2) ◽  
pp. 13-28 ◽  
Author(s):  
Suruchi Chawla

Information on the web has been growing at a very rapid pace and has become quite voluminous over the past few years. The users search query on the web could not retrieve sufficient relevant documents and is responsible for low precision of search results. To improve the precision of search results, an algorithm is proposed in this paper for semantic query expansion using domain ontology based on clustered web query sessions. Domain ontology is created for each cluster of query sessions. The input query of a user is used to select the most similar cluster. The domain ontology of the selected cluster is used to suggest the related concepts for query expansion and the expanded query is used for information retrieval to test its effectiveness. The experiment was conducted on the captured user query sessions on the web and results prove the efficacy of the proposed approach.


Author(s):  
Bilel Elayeb ◽  
Ibrahim Bounhas ◽  
Oussama Ben Khiroun ◽  
Fabrice Evrard ◽  
Narjès Bellamine-BenSaoud

This paper presents a new possibilistic information retrieval system using semantic query expansion. The work is involved in query expansion strategies based on external linguistic resources. In this case, the authors exploited the French dictionary “Le Grand Robert”. First, they model the dictionary as a graph and compute similarities between query terms by exploiting the circuits in the graph. Second, the possibility theory is used by taking advantage of a double relevance measure (possibility and necessity) between the articles of the dictionary and query terms. Third, these two approaches are combined by using two different aggregation methods. The authors also benefit from an existing approach for reweighting query terms in the possibilistic matching model to improve the expansion process. In order to assess and compare the approaches, the authors performed experiments on the standard ‘LeMonde94’ test collection.


2007 ◽  
Vol 63 (1) ◽  
pp. 63-75 ◽  
Author(s):  
Min Song ◽  
Il-Yeol Song ◽  
Xiaohua Hu ◽  
Robert B. Allen

2021 ◽  
Vol 192 ◽  
pp. 387-396
Author(s):  
Amira Dhokar ◽  
Lobna Hlaoua ◽  
Lotfi Ben Romdhane

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