| Wang-Chiew Tan |
| Fri 05 Oct 2018, 14:00 - 15:00 |
| MF2, School of Informatics |
If you have a question about this talk, please contact: Heng Guo (hguo)
Today's online shopping systems enable consumers to sift through vast
amount of information by manipulating combinations of predefined
filters. These filters, such as travel dates, price range, and
location, are objective attributes that lead to an indisputable set of
answers. However, we show that users' search criteria are often
subjective and experientially expressed. Hence, to provide consumers
with an enhanced search experience, online shopping systems should
directly support both subjective and objective search. I will
describe how this is done in the experiential search engine that we
are currently developing at Megagon Labs; by harnessing information
"outside the box", in the text of online reviews or social media,
views, and interpreting subjective queries.
Wang-Chiew Tan leads the research efforts at Megagon Labs. Prior to
joining Megagon Labs, she was a professor of Computer Science at
University of California, Santa Cruz. She received her B.Sc. (First
Class) in Computer Science from the National University of Singapore
and her Ph.D. in Computer Science from the University of Pennsylvania
(advised by Peter Buneman and Sanjeev Khanna). Her research interests
include data provenance, data integration, and very recently, natural
language processing.