Category: DBLab

Evimaria Terzi wins NSF Early Career Award

February 20th, 2013 in DBLab, Recent News

Evimaria Terzi has won an NSF Faculty Early Career Development Award to
support her research and teaching efforts in data mining, in particular
her project “On the identification of collections with complex
objectives.”

Evimaria’s Project Abstract:
“In the classical COLLECTION problem, arising in recommendation systems
for products, services and people, the input consists of a pool of
entities (e.g., movies, books, experts) and an objective function and the
goal is to identify a collection (i.e., a subset) of entities from the
pool that optimizes the objective function. For example, in
movie-recommendation systems (e.g., Netflix) the goal is to identify
subsets of movies to recommend to registered users. Similarly,
review-management systems (e.g., Amazon, Yelp) process thousands of
reviews about a product and need to identify a small subset of them, which
the users can read in order to make purchase decisions. Analogous problems
arise in social networks and social media (e.g., Twitter, Facebook), where
advertisers need to identify a small set of target nodes for their
campaigns so that their product spreads as much as possible. Finally,
Human Resources (HR) departments of companies often use
expertise-management systems (e.g., LinkedIn, odesk) in order to identify
the subset of experts that are the most appropriate to complete a specific
project.

Despite their usefulness, existing instantiations of the COLLECTION
problem have the following two shortcomings: (a) they fail to take into
consideration the need for sequential collections and (b) they do not
consider the rationality of the entities that are called upon to form the
collections. This project addresses these two shortcomings by designing
methods that (a)identify sequences of collections, rather than a single
collection and (b) identify collections of rational entities with personal
objectives. This research provides to formal definitions of such
sequential and rationality-aware recommendations and focuses on the design
algorithms for such problems, as they arise in applications like
recommendation systems, social networks or expertise-management systems.
Apart from algorithm design it also builds domain-specific testbed
applications, which implement these methods and make them accessible to
the general public. The models and methods produced by this research
provide new direction in the areas of recommendation systems with
applications to online applications including social-network sites (e.g.,
LinkedIn, Facebook, etc.), online recommendation systems (e.g., Amazon,
Netflix, etc.) and daily-deal sites (e.g., Groupon, LivingSocial, etc.).”

About the award, according to the NSF website:
“The Faculty Early Career Development (CAREER) Program is a
Foundation-wide activity that offers the National Science Foundation’s
most prestigious awards in support of the early career-development
activities of those teacher-scholars who most effectively integrate
research and education within the context of the mission of their
organization. Such activities should build a firm foundation for a
lifetime of integrated contributions to research and education.”

Congratulations to Evimaria!

Gonca Gursun, et al. win a 2013 IRTF/IETF Applied Networking Research Prize

January 15th, 2013 in DBLab, Recent News

Gonca Gürsun, Natali Ruchansky, Evimaria Terzi and Mark Crovella have won an IRTF/IETF Applied Networking Research Prize, for their paper “Routing State Distance: A Path-based Metric for Network Analysis.”  This work was presented at the 2012 Internet Measurement Conference, and will be a featured presentation at an upcoming IETF meeting.

36 papers were considered in this cycle, out of which only 4 were chosen for the Applied Networking Research Prize in 2013. Each submission was reviewed by eight members of the selection committee according to a diverse set of criteria, including scientific excellence and substance, timeliness, relevance, and potential impact on the Internet.

Summary of their paper

Our group had 3 papers in KDD 2012!

December 12th, 2012 in DBLab

Our group had 4 papers in VLDB 2012!

December 12th, 2012 in DBLab

Evimaria Terzi receives NSF grant for data-mining research

August 27th, 2012 in DBLab, Recent News

The $500K grant will support research on ”Entity Selection and Ranking for Data Mining Applications.” <a href=”http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1218437″>Read more.</a>