Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System

Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical...

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Main Authors: K. R. Uthayan, G. S. Anandha Mala
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2015/414910
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spelling doaj-b058bd8da3434654a5f5118972f6b28c2020-11-25T00:54:23ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/414910414910Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing SystemK. R. Uthayan0G. S. Anandha Mala1Department of Information Technology, SSN College of Engineering, Chennai 603110, IndiaDepartment of Computer Science Engineering, Easwari Engineering College, Chennai 600089, IndiaOntology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.http://dx.doi.org/10.1155/2015/414910
collection DOAJ
language English
format Article
sources DOAJ
author K. R. Uthayan
G. S. Anandha Mala
spellingShingle K. R. Uthayan
G. S. Anandha Mala
Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
The Scientific World Journal
author_facet K. R. Uthayan
G. S. Anandha Mala
author_sort K. R. Uthayan
title Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
title_short Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
title_full Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
title_fullStr Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
title_full_unstemmed Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
title_sort hybrid ontology for semantic information retrieval model using keyword matching indexing system
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2015-01-01
description Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.
url http://dx.doi.org/10.1155/2015/414910
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