[1] 李蕾. 学术型社会化问答平台上答案质量评估研究[D].南京:南京理工大学,2018.
[2] SHAH C, OH J S, OH S. Exploring characteristics and effects of user participation in online social Q&A sites[J/OL].First monday,2008,13(9).[2020-09-25].https://firstmonday.org/article/view/2182/2028.
[3] 张宁, 袁勤俭. 学术社交网络信息质量的治理和提升[J].图书情报工作,2019,63(23):79-86.
[4] 姜雯, 许鑫. 在线问答社区信息质量评价研究综述[J].现代图书情报技术,2014(6):41-50.
[5] YAO Y, TONG H, XIE T, et al. Detecting high-quality posts in community question answering sites[J]. Information sciences,2015,302(1):70-82.
[6] WANG R Y, STOREY V C, FIRTH C P. A framework for analysis of data quality research[J].IEEE transactions on knowledge & data engineering,1995,7(4):623-640.
[7] TENOPIR C, LEVINE K, ALLARD S, et al. Trustworthiness and authority of scholarly information in a digital age:results of an international questionnaire[J].Journal of the association for information science & technology,2016,67(10):2344-2361.
[8] WANG R Y, STRONG D M. Beyond accuracy:what data quality means to data consumers[J].Journal of management information systems,1996,12(4):5-33.
[9] American Public Health Association. Criteria for assessing the quality of health information on the Internet.[J].American journal of public health,2001,91(3):513-514.
[10] 孙晓宁, 赵宇翔, 朱庆华. 基于SQA系统的社会化搜索答案质量评价指标构建[J].中国图书馆学报,2015,41(4):65-82.
[11] DAISUKE I N K, SAKAI O T. What makes a good answer in community question answering? An analysis of assessors' criteria[EB/OL].[2021-01-05].https://www.researchgate.net/publication/228449185.
[12] 吴雅威, 张向先, 陶兴, 等. 基于用户感知的学术问答社区答案质量评价指标构建[J].情报科学,2020,38(10):141-147.
[13] 张煜轩. 基于外部线索的社会化问答平台答案信息质量感知研究[D].武汉:华中师范大学,2016.
[14] CAI Y Z, CHAKRAVARTHY S. Predicting answer quality in Q/A social networks:using temporal features[R].Arlington:University of Texas at Arlington, 2011.
[15] 孔维泽, 刘奕群, 张敏, 等. 问答社区中回答质量的评价方法研究[J].中文信息学报,2011,25(1):3-8.
[16] 姜雯, 许鑫, 武高峰. 附加情感特征的在线问答社区信息质量自动化评价[J].图书情报工作,2015,59(4):100-105.
[17] 郭顺利, 张向先, 陶兴, 等. 社会化问答社区用户生成答案质量自动化评价研究——以"知乎"为例[J]. 图书情报工作,2019,63(11):118-130.
[18] LI L, HE D, JENG W, et al. Answer quality characteristics and prediction on an academic Q&A site:a case study on ResearchGate[C]//24th international conference on World Wide Web. Florence:ACM, 2015:1453-1458.
[19] LE L T, SHAH C, CHOI E. Assessing the quality of answers autonomously in community question-answering[J].International journal on digital libraries,2019,20(4):351-367.
[20] VEKARIYA D V, LIMBASIYA N R. A novel approach for semantic similarity measurement for high quality answer selection in question answering using deep learning methods[C]//6th international conference on advanced computing and communication systems (ICACCS). Coimbatore:IEEE, 2020:518-522.
[21] 贺勋. 在线中文问答社区答案质量预测研究[D].济南:齐鲁工业大学,2020.
[22] GOODWIN S, JENG W, HE D. Changing communication on ResearchGate through interface updates[EB/OL].[2021-01-05].https://www.researchgate.net/publication/273664849.
[23] LI L, ZHANG C, HE D. Factors influencing the importance of criteria for judging answer quality on academic social Q&A platforms[J].Aslib journal of information management,2020,72(6):887-907.
[24] LI L, ZHANG C, HE D, et al. Researchers' judgment criteria of high-quality answers on academic social Q&A platforms[J].Online information review,2020,44(3):603-623.
[25] 任平平. ResearchGate实现学术社交网络国际化[J].国际人才交流,2020(5):52-53.
[26] 王伟, 冀宇强, 王洪伟, 等. 中文问答社区答案质量的评价研究:以知乎为例[J].图书情报工作,2017,61(22):36-44.
[27] 李展, 巢文涵, 陈小明, 等. 中文社区问答中问题答案质量评价和预测[J].计算机科学,2011,38(6):230-236.
[28] LI Y, MA S, ZHANG Y, et al. An improved mix framework for opinion leader identification in online learning communities[J].Knowledge-based systems,2013,43(2):43-51.
[29] 刘永恒. 基于神经网络和时间序列的汽车销量预测研究[D].南昌:南昌大学,2019.
[30] ZHU Z M, BERNHARD D, GUREVYCH I. A multi-dimensional model for assessing the quality of answers in social Q&A sites[EB/OL].[2020-09-30].https://tuprints.ulb.tu-darmstadt.de/1940/.
[31] 贾佳, 宋恩梅, 苏环. 社会化问答平台的答案质量评估——以"知乎"?"百度知道"为例[J].信息资源管理学报,2013,3(2):19-28.
[32] 刘乙蓉, 刘芸. 问答平台中的答案聚合及其优化:以Quora为例[J].图书馆学研究,2017(6):48-56,13.
[33] 袁红, 张莹. 问答社区中询问回答的质量评价——基于百度知道与知乎的比较研究[J].数字图书馆论坛,2014(9):43-49.
[34] 周志华. 机器学习[M].北京:清华大学出版社,2016.
[35] 李宵宵. 随机森林方法在个人信用风险分析中的应用[D].昆明:云南大学,2019.
[36] 周琪. 类别不平衡数据的个人信用风险评估算法研究[D].保定:河北大学,2020.
[37] MCLAUGHLIN G. SMOG grading-a new readability formula[J].Journal of reading,1969,12(8):639-646.
[38] 张海涛, 孙彤, 张鑫蕊, 等. 社会化问答社区用户角色转变的动力机理研究[J].现代情报,2020,40(9):32-41. |