Jian JIN (靳健)

Jian JIN (靳健)

Professor at Dept of IM, BNU

Publications

PUBLICATIONS(* corresponding author)

SCI/SSCI indexed Journal

  1. Qian Geng, Ziang Chuai and Jian Jin*. “Cross-organizational data exchange based on consortium blockchain with consistency guarantee”, Journal of Supercomputing, 2024. [doi] (SCI, Q2)
  2. Kejia Chen, Jingjing Zheng and Jian Jin*. “Ranking products through online opinions: A text analysis and regret theory-based approach”. Applied Soft Computing, Volume 158, June 2024, 111571. [doi] (SCI, Q1)
  3. Qian Geng, Ziang Chuai and Jian Jin*. “Webpage Retrieval Based on Query by Example for Think Tank Construction”. Information Processing and Management. 59(1), January 2022, 102767 [doi] (SCI, SSCI, Q1)
  4. Jian Jin, Danping Jia and Kejia Chen. “Mining online reviews with a Kansei-integrated Kano model for innovative product design”. International Journal of Production Research, 44216, 2021, Taylor & Francis [doi] (SCI, Q1)
  5. Kejia Chen, Jian Jin* and Jiayi Luo. “Big consumer opinion data understanding for Kano categorization in new product development”. Journal of Ambient Intelligence and Humanized Computing, 44216, 2021, Springer Berlin Heidelberg [doi] (SCI, Q1)
  6. Qian Geng, Ziang Chuai and Jian Jin*. “Automatic construction of academic profile: A case of information science domain”. Journal of Information Science, 165551521998048, 2021, SAGE Publications Sage UK: London, England [doi] (SSCI, Q2)
  7. Yonghe Su, Fei Tao, Jian Jin and Changzhi Zhang. “Automated Overheated Region Object Detection of Photovoltaic Module with Thermography Image”. IEEE Journal of Photovoltaics, (11),2:535-544, 2021, IEEE, [doi] (SCI, Q2)
  8. Kejia Chen, Jian Jin*, Zheng Zhao and Ping Ji. “Understanding customer regional differences from online opinions: a hierarchical Bayesian approach”. Electronic Commerce Research, [doi] (SSCI, Q2)
  9. Jian Jin, Haiyuan Zhao and Ping Ji. Topic attention encoder: A self-supervised approach for short text clustering. Journal of Information Science, 165551520977453, 2020, SAGE Publications Sage UK: London, England [doi] (SSCI, Q2)
  10. Qian Geng, Siyu Deng, Danping Jia and Jian Jin*. “Cross-domain Ontology Construction and Alignment from Online Customer Product Reviews”. Information Science, Volume 531, August 2020, Pages 47-67, [doi] (SCI, Q1)
  11. Ying Liu, Anthony Soroka, Liangxiu Han, Jian Jin and Min Tang. “Cloud-based big data analytics for customer insight-driven design innovation in SMEs” International Journal of Information Management, Volume 51, April 2020, 102034, [doi] （SCI，SSCI，Q1）
  12. Yonghe Su, Fei Tao, Jian Jin, Tian Wang, Qingguo Wang and Lei Wang. “Failure Prognosis of Complex Equipment with Multi-stream Deep Recurrent Neural Network”. Journal of Computing and Information Science in Engineering, 20(2): 021007, April 2020 [doi] （SCI，Q3）
  13. Jian Jin, Qian Geng, Haikun Mou and Chong Chen. “Author Subject Topic Model for Reviewer Recommendation”. Journal of Information Science, 45(4), 554-570, 2019 [doi] （SCI，SSCI，Q2）
  14. Min Tang, Jian Jin, Ying Liu, Chunping Li and Weiwen Zhang. “Integrating Topic, Sentiment and Syntax for Modeling Online Reviews: A Topic Model Approach”. Journal of Computing and Information Science in Engineering. 19(1), 011001, 2018 [doi] （SCI，Q3）
  15. Jian Jin, Ying Liu, Ping Ji and C. K. Kwong. “Review on Recent Advances of Information Mining from Big Consumer Opinion Data for Product Design”. Journal of Computing and Information Science in Engineering. 19(1), 010801, 2018 [doi] （SCI，Q3）
  16. Jian Jin, Baozhuang Niu, Ping Ji and Qian Geng. “An Integer Linear Programming Model of Reviewer Assignment with Research Interest Considerations”. Annals of Operations Research. 291, pages 409–433, 2020, [doi] （SCI，Q2）
  17. Jian Jin, Ping Ji and Sixing Yan. “Comparison of series products from customer online concerns for competitive intelligence”. Journal of Ambient Intelligence and Humanized Computing. Volume 10, Issue 3, March 2019 [doi] （SCI，Q3）
  18. Jian Jin and Ping Ji. “Scheduling jobs with resource-dependent ready times and processing times depending on their starting times and positions”. Computer Journal. Volume 61, Issue 9, 1 September 2018, Pages 1323–1328, [doi] （SCI，Q3）
  19. Hongguang Liu, Ping Ji and Jian Jin. “Intra-day trading system design based on the integrated model of wavelet de-noise and genetic programming”. Entropy, 18(12), 435, 2016 [doi] （SCI，Q2）
  20. Jian Jin, Ying Liu, Ping Ji and Hongguang Liu. “Understanding Big Consumer Opinion Data for Market-driven Product Design”, International Journal of Production Research, Volume 54, Issue 10, Pages 3019-3041, 2016 [doi] （SCI，Q1）
  21. Jian Jin, Ping Ji and Rui Gu. “Identifying Comparative Customer Requirements from Product Online Reviews for Competitor Analysis”, Engineering Applications of Artificial Intelligence. Volume 49, Pages 61–73, March 2016 [doi] （SCI，Q1）
  22. Yuan-Yuan Lu, Jian Jin, Ping Ji and Ji-Bo Wang. “Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine”. Neural Computing & Applications, October 2016, Volume 27, Issue 7, pp 1993–2000 [doi] （SCI，Q1）
  23. Binda Wang, Yunwen Miao, Hongya Zhao, Jian Jin and Yizeng Chen. “A biclustering-based method for market segmentation using customer pain points”. Engineering Applications of Artificial Intelligence. Volume 47, January 2016, Pages 101–109. [doi] （SCI，Q1）
  24. Jian Jin, Ping Ji and C. K. Kwong. “What makes consumers unsatisfied with your products: Review analysis at a fine-grained level”. Engineering Applications of Artificial Intelligence. Volume 47, Pages 38–48, January 2016 [doi] （SCI，Q1）
  25. Limin Wang, Jian Jin, Ji-Bo Wang and Ping Ji. “Research on scheduling problems with general effects of deterioration and learning”, Information Sciences. Volume 307, Pages 89-94, June 2015 [doi] （SCI，Q1）
  26. Jian Jin, Ping Ji, Ying Liu and S. C. Johnson Lim. “Translating Online Customer Opinions into Engineering Characteristics in QFD: A Probabilistic Language Analysis Approach”, Engineering Applications of Artificial Intelligence, Volume 41, Pages 115–127, May 2015 [doi] （SCI，Q1）
  27. Jian Jin, Ping Ji and Ying Liu. “Prioritising engineering characteristics based on customer online reviews for quality function deployment”, Journal of Engineering Design, Volume 25, Issue 7-9, Pages 303-324, December 2014. [doi] （SCI，Q2）
  28. Ping Ji, Jian Jin, Ting Wang and Yizeng Chen. “Quantification and integration of Kano’s model into QFD for optimising product design”, International Journal of Production Research, Volume 52, No. 21 Pages 6335–6348, July 2014. [doi] （SCI，Q1）
  29. Xueru, Wang, Jibo Wang, Jian Jin and Ping Ji. “Single machine scheduling with truncated job-dependent learning effect”. Optimization Letters, 8(2), 669-677, 2014 [doi] （SCI，Q2）
  30. Ying Liu, Jian Jin, Ping Ji, Jenny A. Harding and Richard Y. K. Fung, “Identifying Helpful Online Reviews: A Product Designer’s Perspective”, Computer-Aided Design, 45(2), 180–194, 2013 [doi] （SCI，Q1）

International Journal Paper

  1. Feng Sun, Li Liu, Jian Jin*. “An Expert Recommendation Model for Academic Talent Evaluation”. Computing Conference 2019 (CompCom 2019), London, United Kingdom, July 16 – 17 2019. In: Arai K., Bhatia R., Kapoor S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 997. Springer, Cham [doi]
  2. Sixing Yan, Jian Jin, Qian Geng, Yue Zhao and Xiurui Huang. “Utilizing Academic-Network-Based-Conflict of Interests for Paper Reviewer Assignment”. 6th International Conference on Computer Technology and Science (ICCTS 2017), Singapore, December 2017. International Journal of Knowledge Engineering 2017 Vol.3(2): 65-73 ISSN: 2382-6185 [doi]
  3. Jinchuan Chen, Reynold Cheng, Yinuo Zhang and Jian Jin, “A Probabilistic Filter Protocol for Continuous Queries”, First International Workshop on Quality of Context (QuaCon 2009), Pages 88-97, Stuttgart, Germany, Quality of Context, Lecture Notes in Computer Science, Springer, June 2009 [doi]

Book Chapter

  1. Jian Jin, Ping Ji and Ying Liu, “Recommending Rating Values on Reviews for designers”, In: John Wang (ed.), Encyclopedia of Business Analytics and Optimization, pages 1998-2009, IGI Global, February 2014

Book

  1. 靳健，耿骞，陈翀。面向智能任务的专家遴选与推荐研究. 科学出版社，2019年11月
  2. 政府数据资产运营白皮书. 北京师范大学，2019年

Chinese Journal Paper

  1. 耿骞,揣子昂,靳健*. 基于联盟链的跨组织数据交换操作一致性模型，计算机科学,2024(Z6)
  2. 苏梦泽,耿骞,刘志刚,靳健*. 基于属性分析及文本聚类的我国养老政策演化研究. 人口与发展,2023,29(05):133-144
  3. 揣子昂,耿骞,潘慧瑶,靳健*.产业政策知识图谱的自动化构建.情报工程,2022,8(3):028-051
  4. 黄崑, 郑明煊, 罗士超, 靳健. 探索式搜索中基于面部表情识别的用户情绪及影响因素研究.图书情报工作,2022, 66(5): 93-104
  5. 苏雍贺,左颖,靳健,张贺,谢祥颖,任天翔.基于多站支路功率联合学习的分布式光伏支路异常检测方法.计算机集成制造系统,2022,28(07):2149-2161
  6. 耿骞,邓斯予, 靳健*.融合词语义表示和新词发现的领域本体演化——以产品评论数据为例.图书情报工作,2021,65(08):85-96.
  7. 欧一鸣,苏雍贺,靳健,倪玮晨,陶飞.基于知识图谱的分布式光伏运维方案匹配方法.计算机集成制造系统,2021,27(07):1860-1870.
  8. 遆慧颖,耿骞,靳健*.一种基于重叠社区标签传播的学科划分方法[J].农业图书情报学报,2021,33(01):41-52.
  9. 高鹏,苏雍贺,靳健,谢祥颖,张长志,陶飞.基于分布式光伏运维的多类型资源调度技术.计算机集成制造系统,2021,27(03):787-799.
  10. 陈可嘉,郑晶晶,靳健,赵政.基于词频和情景语义的产品特征提取方法[J].广西大学学报(自然科学版),2020,45(06):1413-1422.
  11. 欧一鸣,苏雍贺,邹孝付,靳健,张长志,陶飞.面向智慧运维的分布式光伏知识库构建方法.计算机集成制造系统,2020,26(12):3205-3215.
  12. 贾丹萍，靳健*，耿骞，邓斯予. 感性工学视角下的用户需求挖掘研究.情报学报, 2020, 39(03):308-316，2020年03月24日 [link]
  13. 靳健*，张黎雪，耿骞，刘馨儿. 面向用户需求分析的产品评论用例提取研究.情报理论与实践，2020,43(01):104-111+126，2019年09月17日
  14. 邓斯予，耿骞，靳健*，王锴，贾丹萍. 基于产品评论分析的领域知识库构建与应用.情报理论与实践，2019,42(11):115-122+127，2019年06月20日
  15. 耿骞，景然，靳健*，罗清扬.学术论文引用预测及影响因素分析. 图书情报工作，2018,62(14):29-40，2018年07月20日
  16. 靳健，杨海慈，李凝，耿骞. 基于主题契合度的专家推荐模型研究. 数字图书馆论坛, 2017(04):47-55，2017年04月25日
  17. 赵千，耿骞，靳健*，韦娱. 一种面向主题覆盖度与权威度的评审专家推荐模型研究. 图书情报工作, 2017,61(01):80-88，2017年01月05日
  18. 靳健，季平. 用于在线产品评论质量分析的Co-training算法. 上海大学学报（自然科学版），2014,20(03):289-295，2014年06月20日
  19. 靳健，刘国荣，张博渊. 基于JavaScript的虚拟作物知识引擎的构建. 微电子学与计算机, 2007(03):66-68，2007年03月05日

Peer Refereed Conference Paper

  1. Danping Jia and Jian Jin*. “Mining Affective Needs from Online Opinions for Design Innovation”. APWeb-WAIM, The 4th APWeb-WAIM International Joint Conference on Web and Big Data. August 12-14, 2020, Tianjin, China. [doi]
  2. Qian Geng, Siyu Deng, Danping Jia and Jian Jin*. “Cross-domain Ontology Construction and Alignment from Online Product Reviews”. WWW, 8th International Workshop on Natural Language Processing for Social Media, 786–793, April 20–24, 2020, Taipei, Taiwan. [doi]
  3. Ziang Chuai, Qian Geng and Jian Jin* “Domain-Specific Automatic Scholar Profiling Based on Wikipedia”. WWW, 7th Wiki Workshop, 786–793, April 20–24, 2020, Taipei, Taiwan. [doi]
  4. Haiyuan Zhao, DannuoWang, Mingyan Wang, Xinrui He and Jian Jin*. “Mining the Impact of Investor Sentiment on Stock Market from WeChat”. The annual Wuhan International Conference on E-Business (WHICEB 2019), May 24-26, 2019 [link]
  5. Jian Jin, Qian Geng, Qian Zhao and Lixue Zhang. “Integrating the Trend of Research Interest for Reviewer Assignment”, WWW, 4th workshop on Big Scholarly Data, pages 1233-1241, Perth, Australia, April 2017 [doi]
  6. Sixing Yan, Jian Jin*, Ping Ji and Zihao Geng. “Extracting customer concerns from online reviews of series products for competitor analysis”. iConference, Wuhan, China, March, 2017 [link]
  7. 赵千，靳健*，耿骞，韦娱. “一种面向主题覆盖度与权威度的评审专家推荐模型研究”. iConference Chinese Paper Track, Wuhan, China, March, 2017
  8. Haikun Mou, Qian Geng, Jian Jin* and Chong Chen. “An Author Subject Topic Model for Expert Recommendation”. The Asia Information Retrieval Societies Conference (AIRS 2015), Information Retrieval Technology, Volume 9460, Pages 83-95, Lecture Notes in Computer Science, Springer, January 2016 [doi]
  9. Jian Jin and Ping Ji. “Mining Online Product Reviews to Identify Consumers’ Fine-grained Concerns”, the 12th International Symposium on Operations Research and its Applications in engineering, technology and management (ISORA), Luoyang, China, August, 2015 [doi]
  10. Ping Ji and Jian Jin. “Extraction of Comparative Opinionate Sentences from Product Online Reviews”. the 11th International Conference on Natural Computation(ICNC), the 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 1777-1785, Zhangjiajie, China, August, 2015 [doi]
  11. Ping Ji and Jian Jin, “Integer Linear Programming for Transforming Pairwise Based Results to the Original Ratings”, the 11th International Symposium on Operations Research and its Applications in engineering, technology and management (ISORA), p. 59 – 64, Yellow Mountain, China, August, 2013 [doi]
  12. Jian Jin, Ping Ji and Ying Liu, “Product Characteristic Weighting for Designer from Online Reviews: An Ordinal Classification Approach”, 3rd International Workshop on Business intelligence and the WEB, EDBT/ICDT, Berlin, pages 33-40, Germany, March, 2012, ACM [doi]
  13. Jian Jin, Ping Ji and Ying Liu, “Information Mining from Online Reviews for Engineering Design”, International Design Engineering Technical Conf (IDETC), Washington, DC, August, 2011, ASME (Student Poster)
  14. Jian Jin, Ying Liu, Ping Ji and Richard Y. K. Fung, “Design Preference Centered Review Recommendation: A Similarity Learning Approach”, International Design Engineering Technical Conf (IDETC), pages 1143-1152, Washington, DC, August, 2011, ASME [doi]
  15. Jian Jin and Ying Liu, “How to Interpret the Helpfulness of Online Product Reviews: Bridging the Needs between Customers and Designers”, 2nd International Workshop on Search and Mining User-generated Contents, CIKM, Pages 87-94, Toronto, Canada, October, 2010, ACM [doi]
  16. Jian Jin, Ying Liu, Jenny A. Harding, Richard Y. K. Fung and Han Tong Loh, “Learn to Rank: Automatic Helpfulness Analysis of Online Product Reviews”, International Design Engineering Technical Conf (IDETC), Pages 467-476, Montreal, Canada, August, 2010, ASME
  17. Jianpeng Zhu, Jian Jin and Ying Wang, “A Probabilistic Filter Protocol for Continuous Nearest-neighbor Query”, IEEE Youth Conf. on Information, Computing and Telecommunications (YC-ITC), Pages 399-402, Beijing, China, September, 2009, IEEE [doi]

Peer Refereed Conference Presentation

  1. Ziang Chuai, Qian Geng and Jian Jin. “Healthcare Data Sharing and Ancillary Services Integration: A Blockchain-based Solution”. 2022 Annual Meeting of ASIS&T Asia Pacific Chapter (ASIS&T AP). December 17-18, 2022, Virtual.
  2. 揣子昂,耿骞,靳健.基于联盟链的跨部门政府数据异步更新机制, 第八届全国大数据与社会计算学术会议(BDSC 2023),乌鲁木齐,2023年7月
  3. 秦淑英，潘佳立，王博，靳健，耿骞。面向新产品设计的用户情绪原因发现研究，2022年中国情报学年会暨情报学与情报工作发展论坛，北京，2022年8月
  4. 潘佳立，秦淑英，王博，靳健，耿骞。基于多任务学习的产品创新型特征识别与用户满意度建模，2022年中国情报学年会暨情报学与情报工作发展论坛，北京，2022年8月
  5. Danping Jia, Siyu Deng, Jian Jin and Qian Geng. “Integrating Kansei Engineering with Sentiment Analysis for Customer Understanding from Online Opinions”. POMS International Conference in China (POMS China 2019), Tianjin, Jun 21-24, 2019
  6. Siyu Deng, Danping Jia, Qian Geng and Jian Jin. “Domain Knowledge Base Building and Application Based on Product Reviews”. POMS International Conference in China (POMS China 2019), Tianjin, Jun 21-24, 2019
  7. 宋诗佳，黄宇，王雪雯，靳健。基于连锁店数量指标的城市经济活力评价与预测，中国管理科学与工程学会大数据与商务分析研究会第三届学术年会，大连，2018年5月
  8. 靳健，季平，颜思行，耿子豪. “在线客户评论分析：以系列产品研发为角度”. 第二十九届全国计算机信息管理学术交流会，张掖，2016年10月
  9. Jian Jin and Ping Ji. “Understanding Big Consumer Opinion Data for Market-driven Product Design”, Asian Conference of Management Science & Applications (ACMSA2015) , Dalian, China, September 12-15, 2015
  10. Ping Ji and Jian Jin. “What Makes Consumers Unsatisfied with Your Products: Review Analysis in a Fine-Grained Level”. International Conference on Operations Research (OR 2015), University of Vienna, Vienna, Austria, September 1 – 4, 2015
  11. Ping Ji, Ning Li and Jian Jin, “Identifying Comparative Customer Requirements from Product Online Reviews for Competitor Analysis”, International Conference on Internet Studies (NETs), Tokyo, Japan, July 2015
  12. Jian Jin and Ping Ji, “Understanding the Customer Requirements in the Presence of Big Data”, Annual Conference on Engineering and Information Technology (ACEAIT), Tokyo, Japan, March, 2014
  13. Jian Jin and Ping Ji, “Relating Online Reviews to Product Characteristics”, 10th Conference on Information Science, Technology and Management (CISTM), Lisbon, Portugal, June, 2012