This paper describes how to apply a probabilistic Text Categorization method to a different and new domain where documents are answers to open end questionnaires and codes viewed as categories consist of a hierarchical model. A reduced size training set may be used taking advantage of the hierarchical organization of categories. The system developed in this framework aims at helping psychologists in the evaluation of open end surveys inquiring about job candidates' competencies.

Mapping an Automated Survey Coding Task into a Probabilistic Text categorization Framework

Prodanof I;
2002

Abstract

This paper describes how to apply a probabilistic Text Categorization method to a different and new domain where documents are answers to open end questionnaires and codes viewed as categories consist of a hierarchical model. A reduced size training set may be used taking advantage of the hierarchical organization of categories. The system developed in this framework aims at helping psychologists in the evaluation of open end surveys inquiring about job candidates' competencies.
2002
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Codifica interviste
Apprendimento
Estrazione info
Machine Learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/50333
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