NDLI: An intelligent matcher for schema mapping problem

Content Provider	IEEE Xplore Digital Library
Author	Wei-Jung Shiang Hsin-Chih Chen Hsin Rau
Copyright Year	2008
Description	Author affiliation: Dept. of Ind. Eng., Chung Yuan Christian Univ., Chungli (Wei-Jung Shiang; Hsin-Chih Chen; Hsin Rau)
Abstract	Data exchange between companies needs to fulfill the requirements of common data format and data representation. The core technique for solving schema conflict in data exchange is matching imported XML documents into internal schemas. There are two major methods in schema mapping: linguistic matching and structural matching. Based on previous research results, one single method can not effectively solve the schema mapping problems. Therefore, this paper proposes an intelligent schema matcher based on the similarity flooding method to solve the schema matching problem in one-to-one case. This intelligent matcher uses linguistic similarity values to simplify the directed graph to increase the effectiveness of schema mapping. This matcher reduces the computational effort due to the simplification of the graph, and it increases the matching performances compared to the original similarity flooding method in many indices.
Starting Page	3172
Ending Page	3177
File Size	570554
Page Count	6
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620953
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	XML Floods Machine learning Cybernetics Databases Machine learning algorithms Companies Data exchange Schema matching Similarity flooding
Content Type	Text
Resource Type	Article

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