期刊论文

Ranking Answer Quality of Popular Q&A Community

中文

数据分析与知识发现

2096-3467

2019

3

6

12-20

10.11925/infotech.2096-3467.2018.0696

国家社会科学基金项目(16BTQ076)

本校为第一机构

【目的】针对大众性问答社区答案质量参差不齐的现状,对答案质量排序方法进行探讨。【方法】依据信息接受模型,从感知价值角度构建答案质量排序初始指标体系;采用K-Medoids聚类算法对初始指标进行离散化,同时利用粗糙集理论对初始指标进行约简并赋予权值,进而修正指标体系;运用加权灰色关联分析计算答案的加权灰色关联度,以产生排序结果。【结果】针对"知乎"6类话题下6个问题的2 297条相关数据进行实验分析,排序靠前的答案通常采用图文结合的表达方式、答案所含信息量高,且回答者社区参与度较高,从而答案的质量较高。【局限】数据规模需要扩大,对排序方法的评价还可以优化。【结论】73名"知乎"用...

[Objective] This paper proposes a new method to rank the quality of answers from a popular Q&A community in China.[Methods] First,based on the information acceptance model,we established initial quality indicators for the answer’s perceived values.Then,we discretized these indicators with the K-Medoids clustering algorithm.Third,we reduced and weighted the indictors with the help of rough set theory.Finally,we generated the formal rankings with the weighted grey correlation analysis.[Results] We evaluated the proposed method with 2 297 answers...