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Automatically constructing semantic link network on documents
Author(s) -
Zhuge Hai,
Zhang Junsheng
Publication year - 2010
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1624
Subject(s) - computer science , set (abstract data type) , information retrieval , semantic network , semantic computing , probabilistic logic , probabilistic latent semantic analysis , artificial intelligence , semantic web , programming language
Knowing semantic links among resources is the basis of realizing machine intelligence over large‐scale resources. Discovering semantic links among resources with limited human interference is a challenge issue. This paper proposes an approach to automatically discovering and predicting semantic links in a document set based on a model of document semantic link network (SLN). The approach has the following advantages: it supports probabilistic relational reasoning; SLNs and the relevant rules automatically evolve; and, it can adapt to the update of the adopted techniques. The approach can support cyber space applications, such as documentation recommendation and relational queries, on large documents. Copyright © 2010 John Wiley & Sons, Ltd.