考虑问答语句之间的语义以获得因子得分

Yuya Yokoyama
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引用次数: 0

摘要

为了解决问答网站中提问者与被调查者意图不匹配的问题,通过对印象评价实验结果进行因子分析,得出了问答语句的九个印象因子。然后通过多元回归分析,利用语句的特征值估计因子得分。估计和获得的因素得分随后被用于检测预计会适当回答所发布问题的受访者。然而,到目前为止,还没有考虑到Q&A语句的含义和内容。因此,本文旨在考虑问答语句之间的语义。检查特征值并将其缩小到语法信息、结束句表达式、2-gram和word2vec。分析结果表明,在考虑交叉验证的情况下,所有试验都显示出良好的估计。也有人建议,应用word2vec可以在估计改进的因素得分方面发挥重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consideration of Semantics between Q&A Statements to Obtain Factor Score
In order to solve the issues of mismatches between the intentions of questioners and respondents at Question and Answer (Q&A) sites, nine factors of impressions for Q&A statements were obtained through factor analysis applied to the results of impression evaluation experiments. Then through multiple regression analysis, factor scores were estimated by using the feature values of statements. The factor scores estimated and obtained were subsequently utilized for detecting respondents who are expected to appropriately answer a posted question. Nevertheless, up to now the meanings and contents of Q&A statements have not been taken into consideration. Therefore, this paper aims to consider the semantics between Q&A statements. The feature values are reviewed and narrowed down to syntactic information, closing sentence expressions, 2-gram, and word2vec. The analysis result conveys that all the trials show good estimation with the consideration of cross-validation. It has also been suggested that applying word2vec could play a vital role in estimating improved factor scores.
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