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Author Cameron, Delroy Huborn
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Abstract Literature-Based Discovery (LBD) refers to the process of uncovering hidden connections that are implicit in scientific literature. Numerous hypotheses have been generated from scientific literature using the LBD paradigm, which influenced innovations in diagnosis, treatment, preventions and overall public health. However, much of the existing research on discovering hidden connections among concepts have used distributional statistics and graph-theoretic measures to capture implicit associations. Such metrics do not explicitly capture the semantics of hidden connections. Rather, they only allude to the existence of meaningful underlying associations. To gain in-depth insights into the meaning of hidden (and other) connections, complementary methods have often been employed. Some of these methods include: 1) the use of domain expertise for concept filtering and knowledge exploration, 2) leveraging structured background knowledge for context and to supplement concept filtering, and 3) developing heuristics a priori to help eliminate spurious connections.
Description Affiliation: Wright State University (Cameron, Delroy Huborn)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-07-01
Publisher Place New York
Journal ACM SIGWEB Newsletter (LINK)
Issue Number Winter
Page Count 2
Starting Page 1
Ending Page 2


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Source: ACM Digital Library