Jie Yang

Brief Bio

I am a senior researcher at the eXascale Infolab, University of Fribourg. I obtained my PhD in 2017 from Delft University of Technology, Netherlands, where I worked in the Web Information Systems group. Prior to that, I completed my master program (with cum laude) in Eindhoven University of Technology, Netherlands, in 2013. Before, I received my bachelor degree from Zhejiang University, China, in 2011. During my study, I worked as a research intern in Philips Research, Eindhoven, Netherlands, and as a machine learning scientist in Amazon Research, Seattle, USA.

My research focuses on building effective Human-Machine Loop Systems that combine human intelligence with machine scalability to solve complex tasks at scale. This topic emerges at the intersection of Information Science and Artificial Intelligence, with relevant techniques spanning human computation, machine learning, recommendation, and user modeling. My work finds application in human computation, recommendation, question answering, and urban computing systems.

Research Interests

Human Computation and Crowdsourcing; Machine Learning; Recommender Systems; User Modeling; Conversational Agents; Urban Computing; Community Question Answering.

Selected Awards

Publications

  1. Jie Yang, Thomas Drake, Andreas Damianou, and Yoelle Maarek. “Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa.” In Proceedings of the 2018 Edition of The Web Conference (WWW 2018). ACM, 2018. Bibtex
  2. Jie Yang, Zhu Sun, Alessandro Bozzon, Jie Zhang, and Martha Larson. “CitRec 2017: International Workshop on Recommender Systems for Citizens.” In Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys 2017). ACM, 2017. Bibtex
  3. Ujwal Gadiraju, Jie Yang, and Alessandro Bozzon. “Clarity Is a Worthwhile Quality - On the Role of Task Clarity in Microtask Crowdsourcing.” In Proceedings of the 28th ACM Conference on Hypertext and Social Media (HyperText 2017). ACM, 2017. Bibtex
  4. Zhu Sun, Jie Yang, Jie Zhang, and Alessandro Bozzon. “Exploiting Both Vertical and Horizontal Dimensions of Feature Hierarchy for Effective Recommendation.” In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI 2017). AAAI, 2017. Bibtex
  5. Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Chi Xu, and Yu Chen. “MRLR: Multi-Level Representation Learning for Personalized Ranking in Recommendation.” In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), 2017. Bibtex
  6. Wenjie Pei, Jie Yang, Zhu Sun, Jie Zhang, Alessandro Bozzon, and David MJ Tax. “Interacting Attention-Gated Recurrent Networks for Recommendation.” In Proceedings of the 26th ACM Conference on Information and Knowledge Management (CIKM 2017). ACM, 2017. Bibtex
  7. Arkka Dhiratara, Jie Yang, Alessandro Bozzon, and Geert-Jan Houben. “Social Media Data Analytics for Tourism - A Preliminary Study.” In Proceedings of the 2nd Knowledge Discovery on the Web (KDWeb 2016), 2016. Bibtex
  8. Jie Yang, and Alessandro Bozzon. “On the Improvement of Quality and Reliability of Trust Cues in Micro-Task Crowdsourcing.” In Weaving Relations of Trust in Crowd Work: Transparency and Reputation across Platforms. Workshop at WebScience, 2016. Bibtex
  9. Deniz Iren, Cynthia Liem, Jie Yang, and Alessandro Bozzon. “Using Social Media to Reveal Social and Collective Perspectives on Music.” In Proceedings of the 8th ACM Conference on Web Science (WebSci 2016). ACM, 2016. Bibtex
  10. Jie Yang, Claudia Hauff, Geert-Jan Houben, and Christiaan Titos Bolivar. “Diversity in Urban Social Media Analytics.” In International Conference on Web Engineering (ICWE 2016). Springer, 2016. Bibtex
  11. Jie Yang, Judith Redi, Gianluca Demartini, and Alessandro Bozzon. “Modeling Task Complexity in Crowdsourcing.” In Proceedings of the 4th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2016). AAAI, 2016. Bibtex
  12. Jie Yang, Zhu Sun, Alessandro Bozzon, and Jie Zhang. “Learning Hierarchical Feature Influence for Recommendation by Recursive Regularization.” In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys 2016). ACM, 2016. Bibtex
  13. Giuseppe Silvestri, Jie Yang, Alessandro Bozzon, and Andrea Tagarelli. “Linking Accounts across Social Networks: the Case of StackOverflow, Github and Twitter..” In Proceedings of the 2nd Knowledge Discovery on the Web (KDWeb 2015), 2015. Bibtex
  14. Jasper Oosterman, Jie Yang, Alessandro Bozzon, Lora Aroyo, and Geert-Jan Houben. “On the Impact of Knowledge Extraction and Aggregation on Crowdsourced Annotation of Visual Artworks.” Computer Networks 90 (2015). Bibtex
  15. Jie Yang, Alessandro Bozzon, and Geert-Jan Houben. “E-WISE: An Expertise-Driven Recommendation Platform for Web Question Answering Systems.” In International Conference on Web Engineering (ICWE 2015). Springer, 2015. Bibtex
  16. Jie Yang, Alessandro Bozzon, and Geert-Jan Houben. “Knowledge Crowdsourcing Acceleration.” In Proceedings of the 15th International Conference on Web Engineering (ICWE 2015). Springer, 2015. Bibtex
  17. Jie Yang, Alessandro Bozzon, and Geert-Jan Houben. “Harnessing Engagement for Knowledge Creation Acceleration in Collaborative Q&A Systems.” In Proceedings of the 23rd International Conference on User Modeling, Adaptation, and Personalization (UMAP 2015). Springer, 2015. Bibtex
  18. Xi Long, Jie Yang, Tim Weysen, Reinder Haakma, Jérôme Foussier, Pedro Fonseca, and Ronald M Aarts. “Measuring Dissimilarity between Respiratory Effort Signals Based on Uniform Scaling for Sleep Staging.” Physiological Measurement 35, no. 12 (2014): 2529. Bibtex
  19. Jie Yang, Ke Tao, Alessandro Bozzon, and Geert-Jan Houben. “Sparrows and Owls: Characterisation of Expert Behaviour in StackOverflow.” In Proceedings of the 22nd International Conference on User Modeling, Adaptation, and Personalization (UMAP 2014). Springer, 2014. Bibtex
  20. Jie Yang, Claudia Hauff, Alessandro Bozzon, and Geert-Jan Houben. “Asking the Right Question in Collaborative Q&A Systems.” In Proceedings of the 25th ACM Conference on Hypertext and Social Media (HyperText 2014). ACM, 2014. Bibtex
  21. Hoang Thanh Lam, Toon Calders, Jie Yang, Fabian Mörchen, and Dmitriy Fradkin. “Zips: Mining Compressing Sequential Patterns in Streams.” In Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics ([email protected] 2013). ACM, 2013. Bibtex