Query Expansion on the Role of Word and Sentence Similarity for Domain Ontology Driven Fuzzy Retrieval Systems

2017 ◽  
Vol 14 (6) ◽  
pp. 2612-2619
Author(s):  
M. Uma Devi ◽  
G. Meera Gandhi
Keyword(s):  
Query Expansion ◽  
Domain Ontology ◽  
Retrieval Systems ◽  
Fuzzy Retrieval ◽  
Sentence Similarity

The role of manually-assigned keywords in query expansion

2004 ◽  
Vol 40 (3) ◽  
pp. 441-458 ◽  
Author(s):  
Kazem Taghva ◽  
Julie Borsack ◽  
Thomas Nartker ◽  
Allen Condit
Keyword(s):  
Query Expansion

An Ontological Approach to Managing Project Memories in Organizations

2011 ◽  
pp. 233-261 ◽  
Author(s):  
Davy Monticolo ◽  
Vincent Hilaire ◽  
Samuel Gomes ◽  
Abderrafiaa Koukam
Keyword(s):  
Mechanical Design ◽  
Domain Ontology ◽  
Organizational Memory ◽  
Knowledge Modeling ◽  
Distributed Knowledge ◽  
Agent Model ◽  
Professional Activities ◽  
Ontological Approach ◽  
Multi Agent

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their knowhow and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.

scholarly journals Arabic Query Expansion Using WordNet and Association Rules

2016 ◽  
Vol 12 (3) ◽  
pp. 51-64 ◽  
Author(s):  
Ahmed Abbache ◽  
Farid Meziane ◽  
Ghalem Belalem ◽  
Fatma Zohra Belkredim
Keyword(s):  
Performance Improvement ◽  
Association Rules ◽  
Query Expansion ◽  
Arabic Language ◽  
Selection Method ◽  
Retrieval Performance ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Significant Performance ◽  
Selection Of

Query expansion is the process of adding additional relevant terms to the original queries to improve the performance of information retrieval systems. However, previous studies showed that automatic query expansion using WordNet do not lead to an improvement in the performance. One of the main challenges of query expansion is the selection of appropriate terms. In this paper, the authors review this problem using Arabic WordNet and Association Rules within the context of Arabic Language. The results obtained confirmed that with an appropriate selection method, the authors are able to exploit Arabic WordNet to improve the retrieval performance. Their empirical results on a sub-corpus from the Xinhua collection showed that their automatic selection method has achieved a significant performance improvement in terms of MAP and recall and a better precision with the first top retrieved documents.

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.

An Ontological Approach to Managing Project Memories in Organizations

2009 ◽  
pp. 244-269 ◽  
Author(s):  
Davy Monticolo ◽  
Vincent Hilaire ◽  
Samuel Gomes ◽  
Abderrafiaa Koukam
Keyword(s):  
Mechanical Design ◽  
Domain Ontology ◽  
Organizational Memory ◽  
Knowledge Modeling ◽  
Distributed Knowledge ◽  
Agent Model ◽  
Professional Activities ◽  
Ontological Approach ◽  
Multi Agent

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their knowhow and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.

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