Yang, Y. W., Liu C., Cheng, L. C.* (2023) The dynamic impact of eWOM on movie box office sales: based on innovation diffusion theory, Managerial And Decision Economics (forthcoming)
Cheng, L. C., Lu, W. T., & Yeo, B. (2023). Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach. Financial Innovation, 9(1), 1-23.
Cheng, L. C*.; Cheng, Y.L.; Liao, Y. Y. (2022) Aspect-based sentiment analysis with component focusing multi-head co-attention networks, Neurocomputing, 489, 9-17, (SCI, IF=5.719)
Cheng, L. C.; Huang, Y. H.; Hsieh, M. H.; Wu, M. E. (2021) A Novel Trading Strategy Framework Based on Reinforcement Deep Learning for Financial Market Predictions. Mathematics, 9(23), 3094. (SCI, IF=2.258)
Cheng, L.C., Li Wei, & Tseng, C. R. (2021) Effects of an automated programming assessment system on the learning performances of experienced and novice learners, Interactive Learning Environments, (SSCI, IF=3.928)
Cheng, L.C., Yang, Y. W. The effect of online reviews on movie box office sales. Journal of Global Information Management,(accepted). (SSCI, IF=1.373) —2011年資管學界評比英文核心期刊
鄭麗珍*、王毅、陳詳翰(2023)。結合來源與內容之虛假資訊偵測機制。電子商務學報(TSSCI)
Cheng, L.C.*, Chen, K., Lee, M.C., & Li, K.M. (2021). User-Defined SWOT analysis : A change mining perspective on user-generated content. Information Processing & Management, 58(5), 102613 (SSCI, IF=6.222) (INFORMATION SCIENCE & LIBRARY SCIENCE, Q1)
Cheng, L.C.*, Lin, W.S., & Lien, Y.H. (2021). A hybrid deep learning model for predicting stock market trend prediction. International Journal of Information and Management Sciences, 32(2),121-140. (EI)
Cheng, L.C., Hu, H.W., & Wu, C.C. (2021). Spammer group detection using machine learning technology for observation of new spammer behavioral features. Journal of Global Information Management, 29(2), 61-76. (SSCI,IF=1.373) --2011年資管學界評比英文核心期刊
Chen, Y.L., Cheng,L.C.*, & Zhang, Y.J. (2021). Building a training dataset for classification under a cost limitation. The Electronic Library, 39(1), 77-96. (SSCI, IF=1.453) (INFORMATION SCIENCE & LIBRARY SCIENCE, Q2)
Cheng, L.C.*,& Lin, M.C. (2019). A hybrid recommender system for the mining of consumer preferences from their reviews. Journal of Information Science, 46(5),664-682. (SSCI, IF=3.282) (INFORMATION SCIENCE & LIBRARY SCIENCE, Q1)
Cheng, L.C.*, & Huang, C.L. (2020). Exploring contextual factors from consumer reviews affecting movie sales: an opinion mining approach. Electronic Commerce Research. 20(4), 807–832 (SSCI, IF=3.747).
Cheng, L.C.*, Wu, C.C., & Chen, C.Y. (2019). Behavior Analysis of Customer Churn for a Customer Relationship System: An Empirical Case Study. Journal of Global Information Management, 27(1), 111-127. (SSCI, IF=1.373). 2011年資管學界評比英文核心期刊
Cheng, L.C.*, & Chu, H.C. (2019). An innovative consensus map embedded collaborative learning system for ER diagram learning: sequential analysis of students’ learning achievements. Interactive Learning Environments, 27(3),410-425. (SSCI, IF=3.928)
Cheng, L.C., Hu, Y.H., & Chiou, S.H. (2017). Applying the Temporal Abstraction Technique to the Prediction of Chronic Kidney Disease Progression. Journal of Medical Systems, 41(5),1-12.(SCI, IF=4.460).
Cheng, L.C.*, Chen, Y.L., & Chiang,Y.C. (2016). Identifying conflict patterns to reach a consensus –A novel groupdecision approach. European Journal of Operational Research, 254(2), 622-631,(SCI, IF=5.334)(OPERATIONS RESEARCH & MANAGEMENT SCIENCE, Q1)
Cheng, L.C.*, & Jhang, M.J.(2015). A novel approach to exploring maximum consensus graphs from users’preference data in a new age environment. Electronic Commerce Research, 15(4),543-569. (SSCI, IF=3.747).
Cheng, L.C.*, Chu, H.C., & Shiue, B.M. (2015). An Innovative Approach for Assisting Teachers in Improving Instructional Strategies via Analyzing Historical Assessment Data of Students. International Journal of Distance Education Technologies, 13(4), 40-61. (EI).
Cheng, L.C.*, & Wang, H.A. (2014). A fuzzy recommender system based on the integration of subjective preferences and objective information. Applied Soft Computing, 18, 290–301. (SCI, IF=6.725) (COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, Q1)
Chen, Y.L., Cheng, L.C., & Hsu, W.Y. (2013). A New Approach to the Group Ranking Problem: Finding Consensus Ordered Segments from Users' Preference Data. Decision Sciences, 44(6), 1091-1119. (SSCI, IF=4.147)
Cheng, L.C., Sun, L. M. (2012), Exploring consumer adoption of new services by analyzing the behavior of 3G subscribers: an empirical case study, Electronic Commerce Research and Applications, 11(2), 89-100. (SSCI, IF=6.014)
Chen, Y.L., Cheng, L.C (2010) An approach to group ranking decisions in a dynamic environment, Decision Support Systems, 48(4), 622-634. (SCI, IF=5.795).
Chen, Y.L., Cheng, L.C., (2009) Mining maximum consensus sequences from group ranking data, European Journal of Operational Research, 198(1), 241-251. (SCI, IF=5.334)
Cheng, L.C.*, & Choi, S. (2021). Applying a text mining technique to explore user satisfaction of Kakaobank. 2021第三十二屆國際資訊管理學術研討會(ICIM 2021),臺北市,臺灣。
Cheng, L.C.*, & Sharmayne, L.R. (2020). Analyzing Digital Banking Reviews Using Text Mining. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2020).
Lu, W.T., Cheng, L.C.*, & Chen, J.H. (2020). The Prediction Model of Abnormal Stock Price Impacted by Financial News. 2020第二十六屆臺灣網際網路研討會(TANET 2020),臺北市,臺灣
Cheng, L.C.*, & Tsai, L.S. (2019). Deep Learning for Automated Sentiment Analysis of Social Media. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019), Vancouver, BC, Canada.