Embedded Files
Department of Information Management
Beijing Normal University
Beijing, China
EDUCATION
PUBLICATIONS
SCI/SSCI indexed Journal:
1. Kejia Chen, Jian Jin*, Zheng Zhao and Ping Ji. “Understanding customer regional differences from online opinions: a hierarchical Bayesian approach”. Electronic Commerce Research, https://doi.org/10.1007/s10660-020-09420-5 (SSCI)
2. 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, https://doi.org/10.1016/j.ins.2020.03.058 (SCI, Q1)
3. 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, https://doi.org/10.1016/j.ijinfomgt.2019.11.002 （SCI，SSCI，Q1）
4. 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 https://doi.org/10.1115/1.4045445 （SCI，Q3）
5. 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 https://doi.org/10.1177/0165551518806116 （SCI，SSCI，Q2）
6. 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 https://doi.org/10.1115/1.4041475 （SCI，Q3）
7. 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 https://doi.org/10.1115/1.4041087 （SCI，Q3）
8. 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. 2018 https://doi.org/10.1007/s10479-018-2919-7 （SCI，Q2）
9. 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 https://doi.org/10.1007/s12652-017-0635-9 （SCI，Q3）
10. 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, https://doi.org/10.1093/comjnl/bxx120 （SCI，Q3）
11. 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 https://doi.org/10.3390/e18120435 （SCI，Q2）
12. 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 https://doi.org/10.1080/00207543.2016.1154208 （SCI，Q1）
13. 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 https://doi.org/10.1016/j.engappai.2015.12.005 （SCI，Q1）
14. 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 https://doi.org/10.1007/s00521-015-1993-x （SCI，Q1）
15. 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. https://doi.org/10.1016/j.engappai.2015.06.005 （SCI，Q1）
16. 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 https://doi.org/10.1016/j.engappai.2015.05.006 （SCI，Q1）
17. 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 https://doi.org/10.1016/j.ins.2015.02.021 （SCI，Q1）
18. 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 https://doi.org/10.1016/j.engappai.2015.02.006 （SCI，Q1）
19. 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. http://dx.doi.org/10.1080/09544828.2014.984665 （SCI，Q2）
20. 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. https://doi.org/10.1080/00207543.2014.939777 （SCI，Q1）
21. 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 https://doi.org/10.1007/s11590-012-0579-0 （SCI，Q2）
22. 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 https://doi.org/10.1016/j.cad.2012.07.008 （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 https://doi.org/10.1007/978-3-030-22871-2_10
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 https://doi.org/10.18178/ijke.2017.3.2.089
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 https://doi.org/10.1007/978-3-642-04559-2_8
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
Chinese Journal Paper
1. 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 http://qbxb.istic.ac.cn/CN/Y2020/V39/I3/308
2. 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
3. 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
4. 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
5. 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
6. 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
7. 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
8. 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.
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, April 20–24, 2020, Taipei, Taiwan.
3. Ziang Chuai, Qian Geng and Jian Jin* “Domain-Specific Automatic Scholar Profiling Based on Wikipedia”. WWW, 7th Wiki Workshop, April 20–24, 2020, Taipei, Taiwan.
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
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
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 （http://hdl.handle.net/2142/96669
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
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
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
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
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
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
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
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
Peer Refereed Conference Presentation
1. 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
2. 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
3. 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
4. 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
5. 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
6. 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
7. 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
8. 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
9. Jian Jin and Ping Ji, “Relating Online Reviews to Product Characteristics”, 10th Conference on Information Science, Technology and Management (CISTM), Lisbon, Portugal, June, 2012
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