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  • 标题:Visual Support System for Report Distinctiveness Evaluation
  • 本地全文:下载
  • 作者:Wataru Sunayama ; Toshiaki Kawaguchi
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2008
  • 卷号:23
  • 期号:6
  • 页码:392-401
  • DOI:10.1527/tjsai.23.392
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:In recent years, as the Internet has grown, electronic reports have come to be used in educational organizations such as universities. Though reports written by hand must be evaluated by hand except for stereotype descriptions or numerical answers, electronic reports can be rated by computer. There are two major criteria in rating reports, correctness and distinctiveness. Correctness is rated by absolute criteria and distinctiveness is rated by relative criteria. Relative evaluation is difficult because raters should memorize all contents of submitted reports to provide objective rates. In addition, electronic data are easily copied or exchanged by students. This paper presents a report evaluation support system with which raters can compare each report and give objective rates for distinctiveness. This system evaluates each report by objective similarity criteria and visualizes them in a two-dimensional interface as the calculated distinctiveness order. Experimental results show the system is valid and effective for estimating associations between reports.
  • 关键词:report evaluation support ; information visualization ; distinctiveness evaluation
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