An Improved Technique for Ranking Semantic Associations

The primary focus of the search techniques in the first generation of the Web is accessing relevant documents from the Web. Though it satisfies user requirements, but it is insufficient as the user sometimes wishes to access actionable information involving complex relationships between two given en...

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Bibliographic Details
Published in:International journal of web & semantic technology 2013-10, Vol.4 (4), p.93-106
Main Authors: S, Narayana, G.P.S, Varma, A, Govardhan
Format: Article
Language:English
Subjects:
Computer information security
Information management
Metadata
Ranking
Repositories
Searching
Semantics
User requirements
Online Access:Get full text
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Summary:The primary focus of the search techniques in the first generation of the Web is accessing relevant documents from the Web. Though it satisfies user requirements, but it is insufficient as the user sometimes wishes to access actionable information involving complex relationships between two given entities. Finding such complex relationships (also known as semantic associations) is especially useful in applications such as National Security, Pharmacy, Business Intelligence etc. Therefore, the next frontier is discovering relevant semantic associations between two entities present in large semantic metadata repositories. Given two entities, there exist a huge number of semantic associations between two entities. Hence, ranking of these associations is required in order to find more relevant associations. For this Aleman Meza et al proposed a method involving six metrics viz context, subsumption, rarity, popularity, association length and trust. To compute the overall rank of the associations, this method computes context, subsumption, rarity and popularity values for each component of the association and for all the associations.
ISSN:0976-2280
0975-9026
DOI:10.5121/ijwest.2013.4407