Concept-based searching and browsing

A geoscience experiment

Roslin V. Hauck, Robin R. Sewell, Tobun D. Ng, Hsinchun Chen

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

In the recent literature, we have seen the expansion of information retrieval techniques to include a variety of different collections of information. Collections can have certain characteristics that can lead to different results for the various classification techniques. In addition, the ways and reasons that users explore each collection can affect the success of the information retrieval technique. The focus of this research was to extend the application of our statistical and neural network techniques to the domain of geological science information retrieval. For this study, a test bed of 22,636 geoscience abstracts was obtained through the NSF/DARPA/NASA funded Alexandria Digital Library Initiative project at the University of California at Santa Barbara. This collection was analyzed using algorithms previously developed by our research group: Concept space algorithm for searching and a Kohonen self-organizing map (SOM) algorithm for browsing. Included in this paper are discussions of our technique s, user evaluations and lessons learned.

Original languageEnglish (US)
Pages (from-to)199-210
Number of pages12
JournalJournal of Information Science
Volume27
Issue number4
StatePublished - 2001

Fingerprint

Information retrieval
information retrieval
experiment
Digital libraries
Experiments
Self organizing maps
neural network
NASA
Neural networks
science
evaluation
Group

ASJC Scopus subject areas

  • Information Systems
  • Library and Information Sciences

Cite this

Concept-based searching and browsing : A geoscience experiment. / Hauck, Roslin V.; Sewell, Robin R.; Ng, Tobun D.; Chen, Hsinchun.

In: Journal of Information Science, Vol. 27, No. 4, 2001, p. 199-210.

Research output: Contribution to journalArticle

Hauck, RV, Sewell, RR, Ng, TD & Chen, H 2001, 'Concept-based searching and browsing: A geoscience experiment', Journal of Information Science, vol. 27, no. 4, pp. 199-210.
Hauck, Roslin V. ; Sewell, Robin R. ; Ng, Tobun D. ; Chen, Hsinchun. / Concept-based searching and browsing : A geoscience experiment. In: Journal of Information Science. 2001 ; Vol. 27, No. 4. pp. 199-210.
@article{b0d2c586be1f4a3b9c293d5bb5893c45,
title = "Concept-based searching and browsing: A geoscience experiment",
abstract = "In the recent literature, we have seen the expansion of information retrieval techniques to include a variety of different collections of information. Collections can have certain characteristics that can lead to different results for the various classification techniques. In addition, the ways and reasons that users explore each collection can affect the success of the information retrieval technique. The focus of this research was to extend the application of our statistical and neural network techniques to the domain of geological science information retrieval. For this study, a test bed of 22,636 geoscience abstracts was obtained through the NSF/DARPA/NASA funded Alexandria Digital Library Initiative project at the University of California at Santa Barbara. This collection was analyzed using algorithms previously developed by our research group: Concept space algorithm for searching and a Kohonen self-organizing map (SOM) algorithm for browsing. Included in this paper are discussions of our technique s, user evaluations and lessons learned.",
author = "Hauck, {Roslin V.} and Sewell, {Robin R.} and Ng, {Tobun D.} and Hsinchun Chen",
year = "2001",
language = "English (US)",
volume = "27",
pages = "199--210",
journal = "Journal of Information Science",
issn = "0165-5515",
publisher = "SAGE Publications Ltd",
number = "4",

}

TY - JOUR

T1 - Concept-based searching and browsing

T2 - A geoscience experiment

AU - Hauck, Roslin V.

AU - Sewell, Robin R.

AU - Ng, Tobun D.

AU - Chen, Hsinchun

PY - 2001

Y1 - 2001

N2 - In the recent literature, we have seen the expansion of information retrieval techniques to include a variety of different collections of information. Collections can have certain characteristics that can lead to different results for the various classification techniques. In addition, the ways and reasons that users explore each collection can affect the success of the information retrieval technique. The focus of this research was to extend the application of our statistical and neural network techniques to the domain of geological science information retrieval. For this study, a test bed of 22,636 geoscience abstracts was obtained through the NSF/DARPA/NASA funded Alexandria Digital Library Initiative project at the University of California at Santa Barbara. This collection was analyzed using algorithms previously developed by our research group: Concept space algorithm for searching and a Kohonen self-organizing map (SOM) algorithm for browsing. Included in this paper are discussions of our technique s, user evaluations and lessons learned.

AB - In the recent literature, we have seen the expansion of information retrieval techniques to include a variety of different collections of information. Collections can have certain characteristics that can lead to different results for the various classification techniques. In addition, the ways and reasons that users explore each collection can affect the success of the information retrieval technique. The focus of this research was to extend the application of our statistical and neural network techniques to the domain of geological science information retrieval. For this study, a test bed of 22,636 geoscience abstracts was obtained through the NSF/DARPA/NASA funded Alexandria Digital Library Initiative project at the University of California at Santa Barbara. This collection was analyzed using algorithms previously developed by our research group: Concept space algorithm for searching and a Kohonen self-organizing map (SOM) algorithm for browsing. Included in this paper are discussions of our technique s, user evaluations and lessons learned.

UR - http://www.scopus.com/inward/record.url?scp=0034848850&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034848850&partnerID=8YFLogxK

M3 - Article

VL - 27

SP - 199

EP - 210

JO - Journal of Information Science

JF - Journal of Information Science

SN - 0165-5515

IS - 4

ER -