Chin‐Hui Lai

712 total citations
26 papers, 503 citations indexed

About

Chin‐Hui Lai is a scholar working on Information Systems, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Chin‐Hui Lai has authored 26 papers receiving a total of 503 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Information Systems, 8 papers in Sociology and Political Science and 6 papers in Artificial Intelligence. Recurrent topics in Chin‐Hui Lai's work include Recommender Systems and Techniques (16 papers), Digital Marketing and Social Media (7 papers) and Expert finding and Q&A systems (6 papers). Chin‐Hui Lai is often cited by papers focused on Recommender Systems and Techniques (16 papers), Digital Marketing and Social Media (7 papers) and Expert finding and Q&A systems (6 papers). Chin‐Hui Lai collaborates with scholars based in Taiwan and China. Chin‐Hui Lai's co-authors include Duen‐Ren Liu, Shin‐Jye Lee, Chi‐Chun Lo, Szu‐Yin Lin, Chia‐Yu Hsu, Churn‐Jung Liau, Mei‐Lan Liu, Yu-Chieh Chang, Ping-Shun Chen and Qi Xiao and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Chin‐Hui Lai

25 papers receiving 482 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chin‐Hui Lai Taiwan 14 315 153 83 80 74 26 503
Bharat Bhasker India 10 240 0.8× 191 1.2× 58 0.7× 68 0.8× 87 1.2× 40 464
Maryam Khanian Najafabadi Malaysia 7 298 0.9× 164 1.1× 64 0.8× 72 0.9× 70 0.9× 23 507
Karamollah Bagherifard Iran 10 337 1.1× 220 1.4× 102 1.2× 76 0.9× 124 1.7× 21 574
Sujoy Bag India 7 211 0.7× 173 1.1× 88 1.1× 32 0.4× 79 1.1× 9 436
Wan Shiou Yang Taiwan 9 258 0.8× 102 0.7× 73 0.9× 92 1.1× 113 1.5× 15 446
Fernando Mourão Brazil 12 256 0.8× 274 1.8× 62 0.7× 75 0.9× 60 0.8× 50 508
Mingxin Gan China 16 375 1.2× 248 1.6× 79 1.0× 65 0.8× 50 0.7× 68 672
Yoon‐Joo Park South Korea 9 313 1.0× 263 1.7× 70 0.8× 41 0.5× 70 0.9× 22 554
Federico Michele Facca Italy 12 405 1.3× 213 1.4× 72 0.9× 193 2.4× 38 0.5× 30 591
Ewa Dominowska United Kingdom 2 396 1.3× 215 1.4× 152 1.8× 79 1.0× 102 1.4× 2 659

Countries citing papers authored by Chin‐Hui Lai

Since Specialization
Citations

This map shows the geographic impact of Chin‐Hui Lai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chin‐Hui Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chin‐Hui Lai more than expected).

Fields of papers citing papers by Chin‐Hui Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chin‐Hui Lai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chin‐Hui Lai. The network helps show where Chin‐Hui Lai may publish in the future.

Co-authorship network of co-authors of Chin‐Hui Lai

This figure shows the co-authorship network connecting the top 25 collaborators of Chin‐Hui Lai. A scholar is included among the top collaborators of Chin‐Hui Lai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chin‐Hui Lai. Chin‐Hui Lai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lai, Chin‐Hui, et al.. (2024). Using data-driven techniques to predict outpatient ultrasound examination time for the multi-clinic outpatient appointment scheduling problem. Communications in Statistics - Simulation and Computation. 1–19.
2.
Chen, Chiung‐Mei, et al.. (2024). Neuroprotection effects of kynurenic acid-loaded micelles for the Parkinson’s disease models. Journal of Liposome Research. 34(4). 593–604. 3 indexed citations
3.
Chen, Ping-Shun, et al.. (2023). Developing a prototype system of computer-aided appointment scheduling: A radiology department case study. Technology and Health Care. 32(2). 997–1013. 2 indexed citations
4.
Lai, Chin‐Hui, et al.. (2023). A Hybrid Deep Learning Method to Extract Multi-features from Reviews and User–Item Relations for Rating Prediction. International Journal of Computational Intelligence Systems. 16(1). 4 indexed citations
5.
Lai, Chin‐Hui, et al.. (2022). Applying Simulation Optimization to Minimize Drug Inventory Costs: A Study of a Case Outpatient Pharmacy. Healthcare. 10(3). 556–556. 6 indexed citations
6.
Lai, Chin‐Hui, et al.. (2021). A hybrid of XGBoost and aspect-based review mining with attention neural network for user preference prediction. International Journal of Machine Learning and Cybernetics. 12(5). 1203–1217. 14 indexed citations
7.
Lai, Chin‐Hui & Chia‐Yu Hsu. (2021). Rating prediction based on combination of review mining and user preference analysis. Information Systems. 99. 101742–101742. 14 indexed citations
8.
Lai, Chin‐Hui & Yu-Chieh Chang. (2019). Document recommendation based on the analysis of group trust and user weightings. Journal of Information Science. 45(6). 845–862. 5 indexed citations
9.
Lai, Chin‐Hui, et al.. (2018). A social recommendation method based on the integration of social relationship and product popularity. International Journal of Human-Computer Studies. 121. 42–57. 37 indexed citations
10.
Zhang, Xingjian, Zhongzhong Liu, Qi Xiao, et al.. (2017). Donor Treatment With a Hypoxia‐Inducible Factor‐1 Agonist Prevents Donation After Cardiac Death Liver Graft Injury in a Rat Isolated Perfusion Model. Artificial Organs. 42(3). 280–289. 13 indexed citations
11.
Lai, Chin‐Hui, Duen‐Ren Liu, & Mei‐Lan Liu. (2015). Recommendations based on personalized tendency for different aspects of influences in social media. Journal of Information Science. 41(6). 814–829. 11 indexed citations
12.
Lai, Chin‐Hui. (2014). Applying knowledge flow mining to group recommendation methods for task‐based groups. Journal of the Association for Information Science and Technology. 66(3). 545–563. 9 indexed citations
13.
Lai, Chin‐Hui, et al.. (2013). Novel personal and group-based trust models in collaborative filtering for document recommendation. Information Sciences. 239. 31–49. 35 indexed citations
14.
Liu, Duen‐Ren, et al.. (2012). Document recommendations based on knowledge flows: A hybrid of personalized and group‐based approaches. Journal of the American Society for Information Science and Technology. 63(10). 2100–2117. 16 indexed citations
15.
Liu, Duen‐Ren, et al.. (2011). Sequence-based trust in collaborative filtering for document recommendation. International Journal of Human-Computer Studies. 69(9). 587–601. 19 indexed citations
16.
Liu, Duen‐Ren & Chin‐Hui Lai. (2010). Mining group-based knowledge flows for sharing task knowledge. Decision Support Systems. 50(2). 370–386. 26 indexed citations
17.
Lai, Chin‐Hui & Duen‐Ren Liu. (2009). Integrating knowledge flow mining and collaborative filtering to support document recommendation. Journal of Systems and Software. 82(12). 2023–2037. 28 indexed citations
18.
Liu, Duen‐Ren, et al.. (2007). A Hybrid of Sequential Rules and Collaborative Filtering for Product Recommendation. 211–220. 4 indexed citations
19.
Liu, Duen‐Ren, et al.. (2007). Document recommendation for knowledge sharing in personal folder environments. Journal of Systems and Software. 81(8). 1377–1388. 15 indexed citations
20.
Liu, Duen‐Ren, et al.. (2007). Mining the change of event trends for decision support in environmental scanning. Expert Systems with Applications. 36(2). 972–984. 20 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026