期刊名称：International Journal of Database Management Systems
印刷版ISSN：0975-5985
电子版ISSN：0975-5705
出版年度：2014
卷号：6
期号：6
页码：1
DOI：10.5121/ijdms.2014.6601
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Information is growing more rapidly on the World Wide Web (WWW) has made it necessary to make allthis information not only available to people but also to the machines. Ontology and token are widely beingused to add the semantics in data processing or information processing. A concept formally refers to themeaning of the specification which is encoded in a logic-based language, explicit means concepts,properties that specification is machine readable and also a conceptualization model how people thinkabout things of a particular subject area. In modern scenario more ontologies has been developed onvarious different topics, results in an increased heterogeneity of entities among the ontologies. The conceptintegration becomes vital over last decade and a tool to minimize heterogeneity and empower the dataprocessing. There are various techniques to integrate the concepts from different input sources, based onthe semantic or syntactic match values. In this paper, an approach is proposed to integrate concept(Ontologies or Tokens) using edit distance or n-gram match values between pair of concept and conceptfrequency is used to dominate the integration process. The proposed techniques performance is comparedwith semantic similarity based integration techniques on quality parameters like Recall, Precision, FMeasure& integration efficiency over the different size of concepts. The analysis indicates that editdistance value based interaction outperformed n-gram integration and semantic similarity techniques.
