Document Classification by Fuzzy Attribute Evaluation

Abstract

A technique for classifying objects is proposed that combines classification estimates based on the properties of object attributes. The technique was developed as an aid to classifying captured foreign documents on the battlefield. In this approach, the input information consists of linguistic assessments of the document's classification; these assessments are based on document attributes such as document age, format, and place of discovery. The assessments are modeled as fuzzy sets and combined with the help of a decision function into an output fuzzy set that represents the overall assessment of the document. For a final linguistic classification, the output of the decision function is compared with target classes. The procedure achieves good performance if the decision function is trained on representative sets of classified objects. Although the classification procedure was developed for classification of captured documents, it might be also applied to target recognition from approximate sensor inputs, triage procedures and diagnostics in medical praxis, risk assessments, and similar problems where classification requires the combination of uncertain judgments.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2000
Accession Number
ADA385669

Entities

People

  • Aivars Celmins

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Battlefields
  • Center Of Gravity
  • Classification
  • Coefficients
  • Detectors
  • Disparities
  • Fuzzy Sets
  • Military Research
  • Recognition
  • Risk
  • Risk Analysis
  • Target Recognition
  • Test And Evaluation
  • Test Sets
  • Training

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Regression Analysis.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.