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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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/414910 |
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| author | K. R. Uthayan G. S. Anandha Mala |
| author_facet | K. R. Uthayan G. S. Anandha Mala |
| author_sort | K. R. Uthayan |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-b058bd8da3434654a5f5118972f6b28c |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-b058bd8da3434654a5f5118972f6b28c2025-02-03T05:44:43ZengWileyThe 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 |
| spellingShingle | K. R. Uthayan G. S. Anandha Mala Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System The Scientific World Journal |
| title | 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_short | 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 |
| url | http://dx.doi.org/10.1155/2015/414910 |
| work_keys_str_mv | AT kruthayan hybridontologyforsemanticinformationretrievalmodelusingkeywordmatchingindexingsystem AT gsanandhamala hybridontologyforsemanticinformationretrievalmodelusingkeywordmatchingindexingsystem |