eCommons

 

On the Role of Words and Phrases in Automatic Text Analysis

Other Titles

Abstract

One of the most crucial operations in automatic information retrieval is the assignment to written texts and documents of appropriate identifiers, capable of representing information content for search and retrieval purposes. This operation known as automatic indexing normally consists in assigning to the documents either single terms, or more specific entities such as phrases, or more general entities such as term classes. A model, known as discrimination value analysis is introduced which assigns an appropriate role in the indexing operation to the terms, term phrases, and thesaurus classes. The model is used to determine effectiveness criteria for the content identifiers and to generate useful indexing policies. Experimental evidence is given to validate the theory.

Journal / Series

Volume & Issue

Description

Sponsorship

Date Issued

1975-06

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/TR75-247

Government Document

ISBN

ISMN

ISSN

Other Identifiers

Rights

Rights URI

Types

technical report

Accessibility Feature

Accessibility Hazard

Accessibility Summary

Link(s) to Catalog Record