QSMatching与Vector模型:问卷检索的有效性比较

R. H. D. Souza, C. Dorneles
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引用次数: 0

摘要

编制一份有用的问卷是描述性研究的一项重要任务。拙劣的问题可能会导致答案毫无意义或幼稚的解释。因此,部分或全部重复使用已经以相同目的创建的问卷可能会很有趣。本文将QSMatching与向量模型进行比较,计算问卷之间的相似度,从而根据用户的查询得到问卷的排序。为了验证该算法的有效性,将QSMatching与矢量模型进行了对比实验。实验分析结果表明,QSMatching在问卷检索方面比向量模型更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
QSMatching vs Vector model: comparing effectiveness in questionnaires retrieval
Elaborating an useful questionnaire represents an important task for descriptive research. Poorly elaborated questions can lead to answers with meaningless brased or naive interpretations. Therefore, it may be interesting to reuse, partially or totally, questionnaires already created with the same purpose. In this paper we compare QSMatching with the vector model to calculate the similarity between questionnaires and consequently to obtain a ranking of questionnaires according to the user's query. In order to verify the effectiveness, an experiment was carried out comparing QSMatching and the vector model. The result of the analysis of the experiment shows that QSMatching is more effective than the vector model for questionnaires retrieval.
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