Next: 1 Introduction
An Association Based Method for Automatic Indexing with a
Controlled Vocabulary
Christian Plaunt
School of Information Management and Systems,
University of California at Berkeley, Berkeley, CA 94720
chris@www.sims.berkeley.edu, (510) 642-6656
Barbara A. Norgard
School of Information Management and Systms,
University of California at Berkeley, Berkeley, CA 94720
barbara@briet.berkeley.edu, (510) 642-6656
25 August 1997
Abstract:
In this paper we describe and test a two stage algorithm based on a lexical
collocation technique which maps from the lexical clues contained in a
document representation into a controlled vocabulary list of subject
headings. Using a collection of 4,626 INSPEC documents, we create a
``dictionary'' of associations between the lexical items contained in the
titles, authors and abstracts and controlled vocabulary subject headings
assigned to those records by human indexers using a likelihood ratio
statistic as the measure of association. In the deployment stage, we use
the dictionary to predict which of the controlled vocabulary subject
headings best describe new documents when they are presented to the system.
Our evaluation of this algorithm, in which we compare the automatically
assigned subject headings to the subject headings assigned to the test
documents by human catalogers, shows that we can obtain results comparable
to and consistent with human cataloging. In effect, we have cast this as a
classic partial match information retrieval problem. We consider the
problem to be one of ``retrieving'' (or assigning) the most probably
``relevant'' (or correct) controlled vocabulary subject headings to a
document based on the clues contained in that document.
Next: 1 Introduction
Up: Papers on IR Systems
Christian Plaunt
School of Information Management and
Systems
UC Berkeley
chris@www.sims.berkeley.edu
Wed Dec 20 16:53:25 PST 1995