Mining novel connections from large online digital library using biomedical ontologies
| Date | 01 May 2005 |
| Pages | 261-270 |
| Published date | 01 May 2005 |
| DOI | https://doi.org/10.1108/01435120510596107 |
| Author | Xiaohua Hu |
| Subject Matter | Library & information science |
Mining novel connections from
large online digital library using
biomedical ontologies
Xiaohua Hu
College of Information Science and Technology, Drexel University, Philadelphia,
Pennsylvania, USA
Abstract
Purpose – The huge volume of biomedical literature provides a nice opportunity and challenge to
induce novel knowledge by finding some connections among logical-related medical concepts This
paper aims to propose a semantic-based knowledge discovery system for mining novel connections
from large online digital libraries.
Design/methodology/approach – The method takes advantages of the biomedical ontologies,
MeSH and UMLS, as the source of semantic knowledge. A prototype system, Biomedical
Semantic-based Knowledge Discovery System (Bio-SbKDS), is designed to uncover novel
hypothesis/connections hidden in the biomedical literature. Using only the starting concept and the
initial semantic relation derived from UMLS, Bio-SbKDS can automatically generate the semantic
types as category restrictions for concepts. Using the semantic types and semantic relations of the
biomedical concepts, Bio-SbKDS can identify the relevant concepts collected from Medline in terms of
the semantic type and generate the novel hypothesis between these concepts based on the semantic
relations.
Findings – The system successfully replicates Dr Swanson’s famous discover ies: Raynaud
disease/fish oil automatically, and generates much less intermediate concepts and spurious
connections.
Originality/value – The method takes full advantage of the semantic knowledge of the biomedical
concepts, compared with previous approaches, our methods generate much less but more relevant
novel hypotheses. Another significant advantage over other traditional approaches is that our method
requires much less human intervention in the discovery procedure.
Keywords Digital libraries,Knowledge management, Medicalinformatics, Data handling
Paper type General review
Introduction
The problem of mining novel connection (also known as undiscovered public
knowledge) from biomedical literature was exemplified by Swanson’s pioneering work
on Raynaud disease/fish-oil discovery in 1986. Back then, the Raynaud disease had no
known cause or cure, and the goal of his literature-based discovery was to uncover
novel suggestions for how Raynaud disease might be caused, and how it might be
treated. During Swanson’s initial readings in around 560 documents that discussed
Raynaud disease in the most recent five-year period in 1985, he found that those
literature mention that Raynaud dis ease is a peripheral circulatory di sorder
aggravated by high platelet aggregation, high blood viscosity and vasoconstriction.
The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at
www.emeraldinsight.com/researchregister www.emeraldinsight.com/0143-5124.htm
This work was supported in part by the research grants from the PA Department of Health
(No. 240205, 240196).
Mining novel
connections
261
Library Management
Vol. 26 No. 4/5, 2005
pp. 261-270
qEmerald Group Publishing Limited
0143-5124
DOI 10.1108/01435120510596107
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