Contextual Models of Clinical Publications for Enhancing Retrieval from Full-Text Databases

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Citation: Gretchen P. Purcell and Edward H. Shortliffe. (1995) Contextual Models of Clinical Publications for Enhancing Retrieval from Full-Text Databases. In KSL-95-48, May,1995.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Gretchen P. Purcell and Edward H. Shortliffe
title Contextual Models of Clinical Publications for Enhancing Retrieval from Full-Text Databases
number KSL-95-48
institution Knowledge Systems, AI Laboratory
year 1995
month May
Bibtex more
note Updated September 1995. Medical Computer Science
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abstract Conventional methods for retrieving information from the medical literature are imprecise and inefficient. Information retrieval systems employ unmanageable indexing vocabularies or use full-text representations that overwhelm the user with irrelevant information. This paper describes a document representation designed to improve the precision of searching in textual databases without significantly compromising recall. There presentation augments simple text word representations with contextual models that reflect recurring semantic themes in clinical publications. Using this representation, a searcher may indicate both the terms of interest and the contexts in which they should occur. The contexts limit the potential interpretations of text words, and thus form the basis for more precise searching. In this paper, we discuss the shortcomings of traditional retrieval systems and describe our context-based representation. Improved retrieval performance with contextual models is illustrated by example, and a more extensive study is proposed. We present an evaluation of the contextual models as an indexing scheme, using a variation of the traditional inter-indexer consistency experiments, and we demonstrate that contextual indexing is reproducible by minimally trained physicians and medical students.

KSL Technical Report ID: KSL-95-48
Facts about Contextual Models of Clinical Publications for Enhancing Retrieval from Full-Text DatabasesRDF feed
Abstract Conventional methods for retrieving inform … Conventional methods for retrieving information from the medical literature are imprecise and inefficient. Information retrieval systems employ unmanageable indexing vocabularies or use full-text representations that overwhelm the user with irrelevant information. This paper describes a document representation designed to improve the precision of searching in textual databases without significantly compromising recall. There presentation augments simple text word representations with contextual models that reflect recurring semantic themes in clinical publications. Using this representation, a searcher may indicate both the terms of interest and the contexts in which they should occur. The contexts limit the potential interpretations of text words, and thus form the basis for more precise searching. In this paper, we discuss the shortcomings of traditional retrieval systems and describe our context-based representation. Improved retrieval performance with contextual models is illustrated by example, and a more extensive study is proposed. We present an evaluation of the contextual models as an indexing scheme, using a variation of the traditional inter-indexer consistency experiments, and we demonstrate that contextual indexing is reproducible by minimally trained physicians and medical students. y trained physicians and medical students.
Author Gretchen P. Purcell and Edward H. Shortliffe  +
Bibtype techreport  +
Has author Gretchen P. Purcell and Edward H. Shortliffe  +
Has identifier KSL-95-48  +
Has publishing details May,1995  +
Has title Contextual Models of Clinical Publications for Enhancing Retrieval from Full-Text Databases  +
Has where published KSL-95-48  +
Has year 1995  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-95-48  +
Month May  +
Note Updated September 1995. Medical Computer Science
Number KSL-95-48  +
Process note NO  +
Title Contextual Models of Clinical Publications for Enhancing Retrieval from Full-Text Databases  +
Year 1995  +
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