NDLI: Information retrieval for probabilistic pattern matching based on neural network

Content Provider	IEEE Xplore Digital Library
Author	Yanyan Sun Xudong Lin Qin Jia Xuefei Liu Fei Chen
Copyright Year	2012
Description	Author affiliation: Yanshan University, Qinhuangdao, China (Fei Chen) \|\| Environmental Management College of China, Qinhuangdao, China (Yanyan Sun; Xudong Lin; Qin Jia; Xuefei Liu)
Abstract	Distributed information systems tend to be highly heterogeneous, integrating different computer platforms, data storage structure, different database management systems and schemas which converted data structure under one model to data structure under a different model. For these reasons, a probabilistic pattern matching framework based on neural network is introduced. Our approach gives a probabilistic interpretation of the prediction weights of the candidates, selects the rule set with highest matching probability. Pattern matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain. Through the union formulae, distributed information system may achieve uniform retrieval and provide a strong reference for the research of information retrieval.
Starting Page	2623
Ending Page	2625
File Size	207327
Page Count	3
File Format	PDF
ISBN	9781467301985
e-ISBN	9781467301992
DOI	10.1109/ICSAI.2012.6223592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heterogeneous Computational modeling Neural networks Probabilistic Information retrieval Probabilistic logic Educational institutions Data models Neural network Pattern matching
Content Type	Text
Resource Type	Article

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