Biography: Connie Yuen is a Lecturer at Vocational Training Council in Hong Kong, China. She received her B.Sc. degree in Computer Studies and her M.Phil. degree in Information Technology at City University of Hong Kong and her Ph.D. degree in Computer Science and Engineering at The Chinese University of Hong Kong. Before her appointment as a Lecturer, Dr. Yuen served as a Research Assistant in The Chinese University of Hong Kong and City University of Hong Kong. Dr. Yuen’s research interests include crowdsourcing, human computation, big data application, data mining, machine learning and computer network.
Speech Title: Task Recommendation in Crowdsourcing Systems
Abstract: To ensure the output quality, current crowdsourcing systems highly rely on redundancy of answers provided by multiple workers with varying expertise, however massive redundancy is very expensive and time-consuming. Task recommendation can help requesters to receive good quality output quicker as well as help workers to find their right tasks faster. In this talk, we will present our task recommendation framework based on Probabilistic Matrix Factorization with Active Learning to achieve quality assurance with a very low cost. Complexity analysis shows that our model is efficient and is scalable to large datasets. We carried out experiments on real-world datasets to prove the efficiency of our framework.