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基于TF-PIDF的网络问答社区中的知识供需研究
李明,李莹,周庆,王君
(中国石油大学(北京)经济管理学院 北京  102249)
(北京航空航天大学经济管理学院 北京  100191)
Knowledge Demand and Supply Analysis in Community Questions Answering Based on TF-PIDF
Li Ming,Li Ying,Zhou Qing,Wang Jun
(School of Economics and Management, China University of Petroleum-Beijing, Beijing 102249, China)
(School of Economics and Management, Beihang University, Beijing 100191, China)
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摘要 

[目的] 网络问答社区是知识共享的重要平台。为了掌握民众的知识需求以及社区知识供给情况,进而有针对性的干预,本文构建了网络问答社区中的知识需求和知识供应分析方法。

[方法] 首先针对问答对中的问题和答案均是多部分组成特点,构造了新的词权重计算方法TF-PIDF,分别对问题和答案建模。通过对问题和答案分别聚类获得知识需求和知识供给的主要类别,然后获得各类别的主题以及热度。针对各知识需求类别,发现相应知识供给的主要方面。提出了知识需求覆盖度算法,计算知识需求被知识供给覆盖程度,在此基础上提出对知识需求从热度和覆盖度进行交叉分析。

[结果] 以知乎社区中的流感话题为实际案例进行应用研究,分别获得知识需求和知识供应的6个主题类别,其中热点主题均为“疫情”,但其知识供应覆盖度较低,是突发流感事件下的热门实时知识需求。实验结果表明该方法合理可行。

[局限] 提出的分析框架和方法尽管能够有效的挖掘网络问答社区中知识需求和知识供应的主题,但识别出的主题主要是在特征词聚类所表达的主题含义层面上。

[结论] 通过本方法不仅能够获得民众的知识需求和社区的知识供给的情况,还能为知识补给以及社区运营提供重要依据。

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关键词 网络问答社区知识需求知识供应     
Abstract

[Objective] Community Question Answering (CQA) is an important platform for knowledge sharing. In order to master people's knowledge demand and knowledge supply in CQA, and then make targeted interventions, in the paper, the method for analyzing knowledge demand and knowledge supply in community questions answering is proposed.

[Methods] Firstly, in view of the characteristics that the questions and answers in the question and answer pair are composed of multiple parts, a novel word weight calculation method TF-PIDF is constructed to model the questions and answers respectively. The main categories of knowledge demand and knowledge supply are obtained by clustering the questions and answers, and then the topics and hot degree of each category are obtained. For each category of knowledge demand, the main aspects of the corresponding knowledge supply are identified. The knowledge demand coverage algorithm is proposed to calculate the coverage of knowledge demand by knowledge supply, then it is proposed to carry out a cross-analysis of knowledge demand from heat and coverage.

[Results] The case study on influenza in the community ZHIHU is conducted. Six topic categories of knowledge demand and knowledge supply are obtained, respectively. The hot topic is both "epidemic", but its coverage of knowledge supply is low, which is considered to be the hot real-time knowledge demand under the emergency of influenza. The experimental results show that the method is feasible and performs well.

[Limitations] Although the analysis framework and method proposed in this paper can effectively mine the topic of knowledge demand and knowledge supply in CQA, the identified topic still stays on the topic meaning level expressed by the feature word clustering.

[Conclusions] With the proposed method, the knowledge demand of people and knowledge supply of CQA are mastered. It also provides important basis for knowledge supplement and operation of the community.

Key words Community questions and answers    Knowledge demand    Knowledge supply    Knowledge management
     出版日期: 2020-11-11
ZTFLH:  TP393,G250  
引用本文:   
李明, 李莹, 周庆, 王君. 基于TF-PIDF的网络问答社区中的知识供需研究 [J]. 数据分析与知识发现, 10.11925/infotech.2096-3467. 2020.0395.
Li Ming, Li Ying, Zhou Qing, Wang Jun. Knowledge Demand and Supply Analysis in Community Questions Answering Based on TF-PIDF . Data Analysis and Knowledge Discovery, 0, (): 1-.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467. 2020.0395      或      http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y0/V/I/1
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[2] 马天翼,张朋柱,冯浩垠. 网络外包任务的知识需求建模研究*[J]. 现代图书情报技术, 2016, 32(3): 74-81.
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