BRIEF SURVEY OF KNOWLEDGE AGGREGRATION METHODS.

Michael S. Landy, Robert A. Hummel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Several iterative knowledge aggregation methods are discussed. Such methods are used to choose one of a finite set of labels about each of a set of objects. First, a stimulus is analyzed locally at each object, yielding an initial state which assigns a weight of the evidence from that analysis to each of the labels. The methods continue as a sequence of trials where new evidence is gathered and the current state and new evidence are combined, resulting in a new state. This method iterates until sufficient confidence in a single label at each object is achieved. Several such methods are compared.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherIEEE
Pages248-252
Number of pages5
ISBN (Print)0818607424
StatePublished - 1986

Publication series

NameProceedings - International Conference on Pattern Recognition

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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