Paper Info
Title
MedEvi: retrieving textual evidence of relations between biomedical concepts from Medline.
Abstract
Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given concepts. The limitations are mainly due to the problem that the search engines do not effectively deal with multi-term queries which may imply semantic relations between the terms. To address this problem, we present MedEvi, a novel search engine that imposes positional restriction on occurrences matching multi-term queries, based on the observation that terms with semantic relations which are explicitly stated in text are not found too far from each other. MedEvi further identifies additional keywords of biological and statistical significance from local context of matching occurrences in order to help users reformulate their queries for better results.
Year
DOI
Venue
2008
10.1093/bioinformatics/btn117
BIOINFORMATICS
Keywords
Field
DocType
artificial intelligence,statistical significance,search engine,database management systems,natural language processing
Data mining,Search engine,Semantic search,Information retrieval,Computer science,MEDLINE
Journal
Volume
Issue
ISSN
24
11
1367-4803
Citations 
PageRank 
References 
22
0.88
3
Authors
3
Name
Order
Citations
PageRank
Jung-Jae Kim134327.42
P Pezik21419.07
dietrich rebholzschuhmann3102375.06