A Theory of Term Importance in Automatic Text Analysis
Loading...
No Access Until
Permanent Link(s)
Collections
Other Titles
Author(s)
Abstract
Most existing automatic content analysis and indexing techniques are based on word frequency characteristics applied largely in an ad hoc manner. Contradictory requirements arise in this connection, in that terms exhibiting high occurence frequencies in individual documents are often useful for high recall performance (to retrieve many relevant items), whereas terms with low frequency in the whole collection are useful for high precision (to reject nonrelevant items).
Journal / Series
Volume & Issue
Description
Sponsorship
Date Issued
1974-07
Publisher
Cornell University
Keywords
computer science; technical report
Location
Effective Date
Expiration Date
Sector
Employer
Union
Union Local
NAICS
Number of Workers
Committee Chair
Committee Co-Chair
Committee Member
Degree Discipline
Degree Name
Degree Level
Related Version
Related DOI
Related To
Related Part
Based on Related Item
Has Other Format(s)
Part of Related Item
Related To
Related Publication(s)
Link(s) to Related Publication(s)
References
Link(s) to Reference(s)
Previously Published As
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR74-208
Government Document
ISBN
ISMN
ISSN
Other Identifiers
Rights
Rights URI
Types
technical report