Effective Ontology Alignment: An Approach for Resolving the Ontology Heterogeneity Problem for Semantic Information Retrieval

Kandpal, Ankita; Goudar, R. H.; Chauhan, Renu; Garg, Shalini; Joshi, Kajal

doi:10.1007/978-81-322-1665-0_110

Cited by 4 publications

(1 citation statement)

References 4 publications

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“…Sometimes irrelevant information is retrieved on the semantic web but it is meaningful, and with ontology mapping, the relevance can be improved. Kandpal et al [ 11 ] described a new technique for ontology mapping. Two various ontologies of a domain are considered, and the concepts which are similar to each other are retrieved, that is, ontology alignment.…”

Section: Related Materialsmentioning

confidence: 99%

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

Uthayan¹,

Mala²

2015

The Scientific World Journal

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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.

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Section: Related Materialsmentioning

confidence: 99%

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

Uthayan¹,

Mala²

2015

The Scientific World Journal

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Ontology-Based Automatic Annotation: An Approach for Efficient Retrieval of Semantic Results of Web Documents

Tulasi

Rao²,

Ankita

et al. 2016

Advances in Intelligent Systems and Computing

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Semantic Interoperability-Enabled Architecture for Connected Health Services

Taweel

2016

Reshaping Medical Practice and Care With Health Information Systems

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With the increasing availability of connected health organisations, key medical information is expected to be accessible at the point of care. However, the high sensitivity of the clinical data and the large heterogeneity in health information systems pose a great interoperability challenge, including solutions that rely solely on the use of data exchange standards. Due to low adoption of these standards, such solutions will not sufficiently scale to achieve this objective. This chapter presents a service-based approach that utilises domain models combined with extensible problem models, enriched with domain terminology and knowledge services to enable autonomous data governance and semantic interoperability. The chapter addresses the resulting requirements, describes the proposed a solution and reports the results from the prototype of the approach.

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Effective Ontology Alignment: An Approach for Resolving the Ontology Heterogeneity Problem for Semantic Information Retrieval

Cited by 4 publications

References 4 publications

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

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

Ontology-Based Automatic Annotation: An Approach for Efficient Retrieval of Semantic Results of Web Documents

Semantic Interoperability-Enabled Architecture for Connected Health Services

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