Skip to main navigation Skip to search Skip to main content

A self-organizing semantic map for information retrieval

  • University of Maryland, College Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

252 Scopus citations

Abstract

A neural network's unsupervised learning algorithm, Kohonen's feature map, is applied to constructing a self-organizing semantic map for information retrieval. The semantic map visualizes semantic relationships between input documents, and has properties of economic representation of data with their interrelationships. The potentials of the semantic map include using the map as a retrieval interface for an online bibliographic system. A prototype system that demonstrates this potential is described.

Original languageEnglish
Title of host publicationProceedings of the 14th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1991
PublisherAssociation for Computing Machinery, Inc
Pages262-269
Number of pages8
ISBN (Print)0897914481, 9780897914482
DOIs
StatePublished - Sep 1 1991
Event14th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1991 - Chicago, United States
Duration: Oct 13 1991Oct 16 1991

Publication series

NameProceedings of the 14th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1991

Conference

Conference14th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1991
Country/TerritoryUnited States
CityChicago
Period10/13/9110/16/91

Fingerprint

Dive into the research topics of 'A self-organizing semantic map for information retrieval'. Together they form a unique fingerprint.

Cite this