=Paper=
{{Paper
|id=None
|storemode=property
|title=Crowd Sourcing Literature Review in SUNFLOWER
|pdfUrl=https://ceur-ws.org/Vol-842/crowdsearch-ameryahia.pdf
|volume=Vol-842
|dblpUrl=https://dblp.org/rec/conf/www/Amer-Yahia12
}}
==Crowd Sourcing Literature Review in SUNFLOWER==
<pdf width="1500px">https://ceur-ws.org/Vol-842/crowdsearch-ameryahia.pdf</pdf>
<pre>
        Crowd-Sourcing Literature Review in SUNFLOWER

                                                    Sihem Amer-Yahia
                                                 Qatar Computing Research
                                                      Institute (QCRI)
                                                     syahia@qf.org.qa



1.   ABSTRACT OF THE INVITED TALK                                2.   SPEAKER BIOGRAPHY
Reviewing literature is painful albeit intellectually reward-    Sihem Amer-Yahia is Principal Research Scientist at Qatar
ing. I will describe SUNFLOWER, a system we developed in         Computing Research Center (QCRI) where she leads the
collaboration with Bloomsbury, a publisher of scientific ma-     Social Computing group. She is also DR1 CNRS at LIG
terial, member of Qatar Foundation. SUNFLOWER com-               in France. Her interests are at the intersection of large-
bines the power of search and collaborative editing to review    scale data management and analytics. She works on devel-
and summarize a large number of articles around a topic. It      oping scalable algorithms for organizing, mining and man-
works in three steps. The first step performs a composite re-    aging large volumes of social breadcrumbs left by millions
trieval of related articles where k bundles of complementary     of users online. One of the key projects is a collaboration
articles are built using article metadata such as authors and    with Al Jazeera and MIT to help news consumers and jour-
citations. The second step associates a summary to each          nalists organize and understand user-generated input in the
bundle by extracting key phrases from their constituent ar-      form of comments on articles, tweets, Facebook likes and
ticles. The last step involves humans that collaboratively       shares. Sihem has over 80 publications in major Web data
edit extracted summaries into a coherent literature review       management and social conferences. Prior to her current
on the topic. We report our experiments on scientific articles   position, she worked as Senior Scientist at Yahoo! Research
from qscience.com                                                for 5 years on revisiting relevance models and top-k process-
                                                                 ing algorithms on datasets from Delicious, Yahoo! Personals
                                                                 and Flickr. Before that, she spent 7 years at AT&T Labs in
                                                                 NJ, working on XML query optimization and XML full-text
                                                                 search. Sihem is editor of the W3C XML full-text standard.
                                                                 She is a member of the VLDB Endowment and the ACM
                                                                 SIGMOD executive committee. She serves on the editorial
                                                                 boards of ACM TODS, the VLDB Journal and the Informa-
                                                                 tion Systems Journal. Sihem received her Ph.D. in CS from
                                                                 Univ. Paris-Orsay and INRIA in 1999, and her Diplome
                                                                 dŠIngenieur from INI, Algeria in 1994.

</pre>