Evaluation of unsupervised semantic mapping of natural language with Leximancer concept mapping

The Leximancer system is a relatively new method for transforming lexical co-occurrence information from natural language into semantic patterns in a nunsupervised manner. It employs two stages of co-occurrence information extraction-semantic and relational-using a different algorithm for each stage...

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Vydáno v:Behavior research methods Ročník 38; číslo 2; s. 262 - 279
Hlavní autoři: Smith, Andrew E., Humphreys, Michael S.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Austin, TX Psychonomic Society 01.05.2006
Psychonomic Society, Inc
Témata:
Algorithms
Automation
Biological and medical sciences
Collocations
Comorbidity
Computer Applications
Computer Generated Language Analysis
Concept mapping
Content analysis
Equipment Design
Extraction
Fundamental and applied biological sciences. Psychology
Human subjects
Humans
Information retrieval
Language
Learning
Lexical Semantics
Linguistics
Linguistics - instrumentation
Machine Learning
Mapping
Miscellaneous
Natural language
Natural Language Processing
Psychology
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Semantic Relations
Semantics
Statistical Analysis
Concept
Human
Evaluation
Semantics
Non linear model
Cognition
Natural language
Software
Text
Dynamic model
Algorithm
ISSN:1554-351X, 1554-3528
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Popis
Shrnutí:The Leximancer system is a relatively new method for transforming lexical co-occurrence information from natural language into semantic patterns in a nunsupervised manner. It employs two stages of co-occurrence information extraction-semantic and relational-using a different algorithm for each stage. The algorithms used are statistical, but they employ nonlinear dynamics and machine learning. This article is an attempt to validate the output of Leximancer, using a set of evaluation criteria taken from content analysis that are appropriate for knowledge discovery tasks.
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ISSN:1554-351X
1554-3528
DOI:10.3758/BF03192778