The method to analyze freely described data from questionnaires

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2 Citations (Scopus)

Abstract

Text mining has been growing; mainly due to the need to extract useful information from vast amounts of textual data. Our target here is text data, a collection of freely described data from questionnaires. Unlike research papers, newspaper articles, call-center logs and web pages, which are usually the targets of text mining analysis, the freely described data contained in the questionnaire responses have specific characteristics, including a small number of short sentences forming individual pieces of data, while the wide variety of content precludes the applications of clustering algorithms used to classify the same. In this paper, we suggest the way to extract the opinions which are delivered by multiple respondents, based on the modification relationships included in each sentence in the freely described data. Certain applications of our method are also presented after the introduction of our approach.

Original languageEnglish
Pages (from-to)268-274
Number of pages7
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume13
Issue number3
Publication statusPublished - 2009

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Clustering algorithms
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Keywords

  • Application
  • Modification relationships
  • Text mining

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

Cite this

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