Susan Davidson - Query Driven Crowd Mining

Organisé par : 
L'équipe SLIDE
Intervenant : 
Susan Davidson
Équipes : 

Information détaillée : 

Bio: Susan B. Davidson received the B.A. degree in Mathematics from Cornell University in 1978, and the M.A. and Ph.D. degrees in Electrical Engineering and Computer Science from Princeton University. Dr. Davidson joined the University of Pennsylvania in 1982, and is now the Weiss Professor of Computer and Information Science (CIS). She is an ACM Fellow, a Fulbright scholar, and formerly served as Department Chair of CIS and Deputy Dean of the School of Engineering and Applied Science. She was also a founding co-Director of the Center for Bioinformatics at UPenn (PCBI). The PCBI is a multi-school center spanning Medicine, Engineering and Applied Sciences, and Arts and Sciences, and is known for its pioneering work in database integration, genomic schema development, visualization tools, and annotation systems.

Dr. Davidson's research interests include database and crowdsourced systems, bioinformatics, and scientific workflow systems. Within bioinformatics she is best known for her work in data integration strategies, with XML as a data exchange and integration strategy, and with provenance for scientific workflows.

Résumé : 
Harnessing the crowd to collect massive amounts of data (crowdsourcing) has become increasingly popular. Examples in our culture include Wikipedia, social tagging systems for images, traffic information aggregators like Waze, and hotel and movie ratings like TripAdvisor and IMDb. In this talk, I give an overview of the challenges inherent in providing declarative, database-style platforms for supporting crowdsourcing. I then discuss how to go one step further and enable users to posed general questions to mine the crowd for potentially relevant data, and to receive concise, relevant answers that represent frequent significant data patterns. I close by discussing the challenges that crowd mining poses for provenance.