Graph-based Cluster Analysis to Identify Similar Questions: A Design Science Approach

被引：12

作者：

John, Blooma Mohan ^{[1
]}

Chua, Alton Yeow Kuan ^{[2
]}

Goh, Dion Hoe Lian ^{[2
]}

Wickramasinghe, Nilmini ^{[3
,4
]}

机构：

[1] Univ Canberra, Fac Business Govt & Law, Canberra, ACT 2601, Australia

[2] Nanyang Technol Univ, Div Informat Studies, Singapore, Singapore

[3] Deakin Univ, Epworth HealthCare, Geelong, Vic 3217, Australia

[4] Deakin Univ, Fac Hlth, Geelong, Vic 3217, Australia

来源：

JOURNAL OF THE ASSOCIATION FOR INFORMATION SYSTEMS | 2016年 / 17卷 / 09期

关键词：

Cluster Analysis; Graph Theory; Design Science; Social Question Answering; INFORMATION; SYSTEMS; KNOWLEDGE; ALGORITHM; QUALITY;

D O I：

10.17705/1jais.00437

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Social question answering (SQA) services allow users to clarify their queries by asking questions and obtaining answers from other users. To enhance the responsiveness of such services, one can identify similar questions and, thereafter, return the answers available. However, identifying similar questions is difficult because of the complex language structure of user-generated questions. For this reason, we developed an approach to cluster similar questions based on a web of social relationships among the questions, the answers, the askers, and the answerers. To do so, we designed a graph-based cluster analysis using design science research guidelines. In evaluating the results, we found that the proposed graph-based cluster analysis is more promising than baseline methods.

引用

页码：590 / 613

页数：24

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