文献类型：期刊文献

英文题名：UFTDRDH: A novel user-oriented solution for full-text database retrieval in Chinese digital humanities

作者：Yan, Chengxi[1,2];Fang, Xiaoke[3];Li, Yang[4]

第一作者：Yan, Chengxi

通讯作者：Li, Y[1]

机构：[1]Renmin Univ China, Sch Informat Resource Management, Beijing, Peoples R China;[2]Renmin Univ China, Res Ctr Digital Humanities, Beijing, Peoples R China;[3]Beijing Union Univ, Coll Appl Arts & Sci, Beijing, Peoples R China;[4]Hangzhou Dianzi Univ, Chinese Acad Sci & Educ Evaluat, Hangzhou 310018, Peoples R China

第一机构：Renmin Univ China, Sch Informat Resource Management, Beijing, Peoples R China

通讯机构：[1]corresponding author), Hangzhou Dianzi Univ, Chinese Acad Sci & Educ Evaluat, Hangzhou 310018, Peoples R China.

年份：0

外文期刊名：JOURNAL OF INFORMATION SCIENCE

收录：;EI(收录号：20224813175191);Scopus(收录号：2-s2.0-85142611533);WOS:【SSCI(收录号:WOS:000889636300001)，SCI-EXPANDED(收录号:WOS:000889636300001)】；

基金：This study is supported by China Postdoctoral Science Foundation (No. 2021M703564) and National Social Science Foundation of China (NO. 18CTQ041). We are also grateful to the editors and the anonymous reviewers for their insightful suggestions.

语种：英文

外文关键词：Automatic query formulation; database search; digital humanities; full-text retrieval

摘要：Information technology boosts the development of database retrieval in the Chinese digital humanities domain. However, most database providers adopt a system-oriented design pattern, which fails to handle the problem of query gaps in users' retrieval process. This issue seriously hinders the effective use of database retrieval functionalities, peculiarly among those historical and humanities researchers. To address it, we propose UFTDRDH, a novel user-oriented solution based on automatic query formulation (AQF) technologies, which integrates a human-machine interactive module for the selection of new query-related expansion terms and a powerful query expansion algorithmic component (UFTDRDH-QEV) optimised by a topic-enhancing relevance feedback model approach (ToQE). To verify the effectiveness of UFTDRDH, several comparative experiments are conducted, including quantitative evaluation for retrieval efficiency and user satisfaction, as well as qualitative studies for interpretative traceability. The empirical results are multidimensional and robust, which not only shows the positive effects of different AQFs on gap reduction, especially the importance of query expansion as the most effective technology, but also underlines the remarkably advantageous performance of UFTDRDH compared with traditional system-oriented automatic query expansion in different task contexts. We believe the application of UFTDRDH can further strengthen the research focus on user-centred design and improve the level of current full-text database retrieval in the field of Chinese digital humanities. Broadly speaking, this solution can be also extended to the full-text database retrieval in other languages and digital humanities domains.