Storage Retrieval

Download Intelligent Information Integration for the Semantic Web by Ubbo Visser PDF

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By Ubbo Visser

The semantic internet bargains new possibilities for info tactics. This booklet is dedicated to the middle factor of information integration on the semantic point and demonstrates the applicability of the options constructed to spatio-temporal illustration and reasoning and geographic info systems.

Preceded by means of a motivating advent and an summary of the cutting-edge within the box of knowledge integration, basic difficulties of terminological illustration, terminological reasoning, and semantic translation are taken care of intimately. The theoretical effects and methods constructed are utilized to clever conceptual and spatio-temporal queries of heterogeneous geographic info systems.

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Extra info for Intelligent Information Integration for the Semantic Web

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6 most of the times), they are not used homogeneously, involving a fairly loose semantic association. An example in the medical field is the semantic network of UMLS (Unified Medical Language System) [132]. A specific type of semantic network is a topic map. It is a representation of knowledge with an emphasis on the find-ability of information. A topic map defines a multidimensional topic space in which the locations are topics, and the kinds of relationships define the path from one topic to another [86].

Evolving from WordNet, EuroWordNet [203] was developed as its multilingual version consisting of a set of cross-related WordNets in several languages (French, German, Spanish, Dutch, Italian, Czech, Estonian and English). It includes the semantic relations between words of each provided European language and the relations among each word and the equivalents in the other languages. 6 most of the times), they are not used homogeneously, involving a fairly loose semantic association. An example in the medical field is the semantic network of UMLS (Unified Medical Language System) [132].

136] show an ontology editing, merging, and diagnostic environment called Chimaera. Kotis and Vouros [113] describe the HCONE approach on ontology merging. It is based on capturing the intended informal interpretations of concepts by mapping them to WordNet senses using lexical semantic indexing, and exploiting the formal semantics of concepts by means of description logics reasoning services. When the objective is to perform a model transformation, the alignment is needed to model the changes from the original to the transformed ontology.

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