Deriving concept hierarchies from text

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Deriving concept hierarchies from text

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Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval table of contents

Berkeley, California, United States

Pages: 206 - 213

Year of Publication: 1999

ISBN:1-58113-096-1

Authors

Mark Sanderson	Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
Bruce Croft	CIIR, Computer Science Department, University of Massachusetts, Amherst, MA

Sponsor

SIGIR: ACM Special Interest Group on Information Retrieval

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 18, Downloads (12 Months): 133, Citation Count: 62

Additional Information:

references cited by index terms collaborative colleagues peer to peer

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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INDEX TERMS

Primary Classification:
H. Information Systems
H.3 INFORMATION STORAGE AND RETRIEVAL

Additional Classification:
I. Computing Methodologies
I.2 ARTIFICIAL INTELLIGENCE
I.2.7 Natural Language Processing
Subjects: Text analysis

General Terms:
Design, Documentation, Experimentation, Management, Measurement, Performance, Theory

Keywords:
concept hierarchy, multi-document summary, subsumption, term co-occurence

Collaborative Colleagues:

Mark Sanderson: colleagues

Bruce Croft: colleagues

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