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

2012 ◽  
Vol 16 (3) ◽  
pp. 277 ◽  
Author(s):  
Ziyu Liu ◽  
Junxia Chen ◽  
Xuehui Li ◽  
Ying Qu ◽  
Fachao Li
Keyword(s):  
Query Expansion ◽  
Domain Ontology ◽  
Semantic Query ◽  
Design And Application

A Study of Semantic Query Expansion Based on Domain Ontology and Local Co-Occurrence Probability Model

2015 ◽  
Vol 731 ◽  
pp. 231-236
Author(s):  
Wu Xia Ning ◽  
Qiang Wang ◽  
Jin Kai Li ◽  
Feng Wang
Keyword(s):  
Query Expansion ◽  
Probability Model ◽  
Expansion Method ◽  
Domain Ontology ◽  
Occurrence Probability ◽  
Semantic Query ◽  
Retrieval Efficiency ◽  
Online Book ◽  
Filtering Function ◽  
Typical Solution

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.

Semantic Query Expansion using Cluster Based Domain Ontologies

2012 ◽  
Vol 2 (2) ◽  
pp. 13-28 ◽  
Author(s):  
Suruchi Chawla
Keyword(s):  
Query Expansion ◽  
Domain Ontology ◽  
Search Query ◽  
Semantic Query ◽  
Search Results ◽  
The Past ◽  
User Query ◽  
Similar Cluster ◽  
Rapid Pace ◽  
The Web

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.

Towards a Possibilistic Information Retrieval System Using Semantic Query Expansion

2012 ◽  
pp. 216-242
Author(s):  
Bilel Elayeb ◽  
Ibrahim Bounhas ◽  
Oussama Ben Khiroun ◽  
Fabrice Evrard ◽  
Narjès Bellamine-BenSaoud
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
Retrieval System ◽  
Possibility Theory ◽  
Information Retrieval System ◽  
Test Collection ◽  
Expansion Process ◽  
Semantic Query ◽  
Linguistic Resources ◽  
Relevance Measure

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.

Integration of association rules and ontologies for semantic query expansion

2007 ◽  
Vol 63 (1) ◽  
pp. 63-75 ◽  
Author(s):  
Min Song ◽  
Il-Yeol Song ◽  
Xiaohua Hu ◽  
Robert B. Allen
Keyword(s):  
Association Rules ◽  
Query Expansion ◽  
Semantic Query

scholarly journals Tweet Contextualization Approach Using a Semantic Query Expansion

2021 ◽  
Vol 192 ◽  
pp. 387-396
Author(s):  
Amira Dhokar ◽  
Lobna Hlaoua ◽  
Lotfi Ben Romdhane
Keyword(s):  
Query Expansion ◽  
Semantic Query ◽  
Tweet Contextualization
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