Research Interests:

I am broadly interested in machine learning and deep learning as well as their practical applications. My research focuses on information retrieval and fusion of large-scale heterogeneous data derived from online sources. My previous research includes traffic forecasting, question answering, user engagement modelling, and text mining. My passion lies in innovative research for solving real-world problems with complex and large-scale data using my data mining research experience.

Github: https://github.com/long4coventry

Employment

Feb 2018–present Innovation Research Fellow (Line Manager: Dr JinhYun Hong) Urban Big Data Center, Glasgow Title: Social and economic implications of transport sharing and automation Feb 2015–Feb 2018 Research Assistant on EPSRC S4 Programme Grant (PI: Prof. Joemon Jose) School of Computing Science, University of Glasgow Keywords: topic modelling, event detection, semantic web Aug 2014– Feb 2015 Intern (PI:Liam Ellis ) Wonga, London Keywords: scorecard, risk modelling

Education

2009 – 2014 PhD School of Computing Science – Birkbeck, University of London Supervisors: Dell Zhang and Mark Levene Title: Understanding and exploiting user intent in community question answering 2006 – 2009 Master’s degree in Computer Science, Central China Normal University 2002 – 2006 Bachelor’s degree in Computer Science, Central China Normal University ###Teaching As part of my PhD and Research Fellow position, I have been a teaching assistant from 2013 until now in the following courses: • Feb 2020– Feb 2021 Programming Tools for Urban Analytics, University of Glasgow (Lecture 9 Machine Learning and Deep learning, which is also available on Moodle) • Feb 2017– Feb 2019 Web Science, University of Glasgow (Lecture 5, NoSQL, Lecture 7, Deep Learning) • Feb 2013– Feb 2014 Quantitative Method, University of London (Lecture 8, Statistical Analysis Using SPSS)

COMPUTER EXPERTISE

• In-depth understanding of programming language such as Python (IPython Notebook), JAVA, R, C#, and C++ • In-depth understanding of statistical tools such as SPSS, Matlab, and Excel • Skilled in SQL queries, MongoDB, VISUM, VISSIM

SELECTED PUBLICATIONS/CONFERENCES

Journal Articles

  1. Long Chen., Thakuriah, P. (V.) and Ampountolas, K. (2021) Short-term prediction of demand for ridehailing services: a deep learning approach. Journal of Big Data Analytics in Transportation, 3(2), pp. 175-
  2. (doi: 10.1007/s42421-021-00041-4)
  3. Long Chen, Zhang, H., Jose, J. M. , Yu, H., Moshfeghi, Y. and Triantafillou, P. (2018) Topic detection and tracking on heterogeneous information. Journal of Intelligent Information Systems, 51(1), pp. 115-
  4. (doi: 10.1007/s10844-017-0487-y)
  5. Yu, H.-T., Jatowt, A., Blanco, R., Joho, H., Jose, J. M., Long Chen and Yuan, F. (2018) Revisiting the cluster-based paradigm for implicit search result diversification. Information Processing and Management, 54(4), pp. 507-528. (doi: 10.1016/j.ipm.2018.03.003)
  6. Long Chen., Jose, J. M. , Yu, H., Yuan, F. and Zhang, H. (2016) Probabilistic Topic Modelling with Semantic Graph. Computer Science, 9626, pp. 240-251. (doi: 10.1007/978-3-319-30671-1_18)

Conference Proceedings

  1. Yu, H.-T., Jatowt, A., Joho, H., Jose, J. M. , Yang, X. and Long Chen,. (2019) WassRank: Listwise Document Ranking Using Optimal Transport Theory. In: Twelfth ACM International Conference on Web Search and Data Mining, Melbourne, Australia, 11-15 Feb 2019, pp. 24-32. ISBN 9781450359405 (doi:10.1145/3289600.3291006)
  2. Long Chen, Yuan, F., Jose, J. M. and Zhang, W. (2018) Improving Negative Sampling for Word Representation Using Self-embedded Features. In: The 11th International Conference on Web Searching and Data Mining (WSDM 2018), Los Angeles, CA, USA, 05-09 Feb 2018, pp. 99-107. ISBN 9781450355810 (doi:10.1145/3159652.3159695)
  3. Long Chen., Jose, J. M. , Yu, H. and Yuan, F. (2017) A Semantic Graph-Based Approach for Mining Common Topics From Multiple Asynchronous Text Streams. In: 26th International World Wide Web Conference: WWW 2017, Perth, Australia, 3-7 Apr 2017, pp. 1201-1209. ISBN 9781450349130 (doi:10.1145/3038912.3052630)
  4. Yuan, F., Jose, J. M. , Guo, G., Long Chen, Yu, H. and Alkhawaldeh, R. S. (2017) Joint Geo-Spatial Preference and Pairwise Ranking for Point-of-Interest Recommendation. In: 28th International Conference on Tools with Artificial Intelligence (ICTAI 2016), San Jose, CA, USA, 6-8 Nov 2016, pp. 46-
  5. ISBN 9781509044597 (doi:10.1109/ICTAI.2016.0018)
  6. Yuan, F., Guo, G., Jose, J. M. , Long Chen, Yu, H. and Zhang, W. (2017) BoostFM: Boosted Factorization Machines for Top-N Feature-based Recommendation. In: IUI 2017: 22nd Annual Meeting of the Intelligent User Interfaces Community, Limassol, Cyprus, 13-16 March 2017, pp. 45-54. ISBN 9781450343480 (doi:10.1145/3025171.3025211)
  7. Yuan, F., Guo, G., Jose, J. M. , Long Chen, Yu, H. and Zhang, W. (2016) Optimizing Factorization Machines for Top-N Context-aware Recommendations. In: 17th International Conference on Web Information Systems Engineering (WISE 2016), Shanghai, China, 7-10 Nov 2016, pp. 278-293. ISBN 9783319487397 (doi:10.1007/978-3-319-48740-3_20)
  8. Yuan, F., Guo, G., Jose, J. M. , Long Chen, Yu, H. and Zhang, W. (2016) LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates. In: 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), Indianapolis, IN, USA, 24-28 Oct 2016, pp. 227-236. ISBN 9781450340731 (doi:10.1145/2983323.2983758)
  9. Long Chen, Jose, J. M. , Yu, H., Yuan, F. and Zhang, D. (2016) A Semantic Graph based Topic Model for Question Retrieval in Community Question Answering. In: Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA, 22-25 Feb 2016, pp. 287-296. ISBN 9781450337168 (doi:10.1145/2835776.2835809)
  10. Fajie Yuan, Guibing Guo, Joemon M Jose, Long Chen and Haitao Yu. “Joint Geo-Spatial Preference and Pairwise Ranking for Point-of-Interest Recommendation” In Proceedings of the IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2016, Best Student Paper Award) 3
  11. Fajie Yuan, Guibing Guo, Joemon M Jose, Long Chen and Haitao Yu. “Optimizing Factorization Machines for Top-N Context-aware Recommendations” In Proceedings of the 17th International Conference on Web Information System Engineering (WISE 2016, Accept rate: 23%) Book Chapters
  12. Chen, L., Sun, Y. and Thakuriah, P. (2019) Modelling and Predicting Individual Salaries in United Kingdom with Graph Convolutional Network. In: Madureira, A. M., Abraham, A., Gandhi, N. and Varela, M. L. (eds.) Hybrid Intelligent Systems. Series: Advances in intelligent systems and computing (923). Springer: Cham, pp. 61-74. ISBN 9783030143466 (doi:10.1007/978-3-030-14347-3_7)

    Submitted Journal Articles

  13. Long Chen, Piyushimita Vonu Thakuriah, and Konstantinos Ampountolas. “ Predicting the Crowd Size through Twitter Data Analysis” Submitted to Journal of Information and Management.
  14. Long Chen, Piyushimita Vonu Thakuriah, and Konstantinos Ampountolas. “Understanding Bert’s Attention in Covid Sentiment Analysis via DBpedia” Submitted to Journal of Information Systems.
  15. Long Chen, Piyushimita Vonu Thakuriah, and Konstantinos Ampountolas. “ Learning the Semantic Embedding for Question Retrieval in Community Question Answering Platforms” Submitted to Journal of Web Semantics.
  16. Long Chen, Yashar Moshigihi, Peter Ttriantafillou. “SG-DE: A General Framework for Incorporating Semantic Graphs into Document Representation” Submitted to Proceedings of the 31th International Conference Companion on World Wide Web

Awards

• ESRC Fellowship (ESRC project PI, #ES/S001875/1)
U21 2020 Scholarship
• Conference Travel Grant (£1500)
Birkbeck 2013, Elite Scholarship
• Tuition fee waiver (£12000)
SIGIR 2013 Travel Grant
• Conference Travel Grant (£1000)
ECIR 2010 Travel Grant
• Conference Travel Grant (£500)

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