WebKnowHow Friday, June 2, 2006; 04:31 AM
Microsoft Live Labs announced 12 winners of its Accelerating Search in
Academic Research request for proposals (RFP). The RFP, which generated more
than 180 applications from all over the world, was issued to discover and fund
academic research that will improve Internet search technologies, and data
mining, discovery and analysis.
“As anyone who uses the Internet knows, it’s not really about ‘search’ — it’s
about ‘discover,’” said Gary William Flake, Ph.D., founder and director of Live
Labs and a Technical Fellow at Microsoft. “Through this RFP process, we have
found a wealth of academic talent and ideas for search and algorithm development
that we think will transform our ability to harness the power of the Web in the
years to come, allowing users to focus less on the work of searching and instead
reap the rewards of discovery.”
The Live Labs Search RFP continues a history of cooperation between
Microsoft Research and the academic community to encourage research and
innovation. Each of the RFP winners demonstrated innovative
approaches to advancing the state of the art in the highly competitive Internet
search arena, and each will be awarded between $25,000 and $50,000 (U.S.) to
fund continued efforts. The total funding amount is $500,000. Awardees will also
gain access to extensive data logs from MSN to aid in their research, as well as
an increased quota of queries to the MSN Search software development
kit, which gives them programmatic access to real-world search results from MSN.
“It is very difficult to access large volumes of real data,” said recipient
Amélie Marian of Rutgers University. “Being able to work on a large excerpt of
real search query logs, including per-query search result click-through, will be
a very valuable resource to understand how users search and access
information.”
Recipients of the Live Labs grants, the general categories of their research
and the titles of their RFP proposals are listed here:
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Eytan Adar, Brian Bershad, Steven Gribble, Daniel Weld — University of
Washington (U.S.):
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General research: machine learning, human-computer interaction, data
mining |
• |
Proposal title: “Vinegar: Leading Indicators in Query
Logs” | |
• |
Lada Adamic, Suresh Bhavnani — University of Michigan (U.S.):
• |
General research: natural language processing, human-computer
interaction |
• |
Proposal title: “VISP: Visualizing Information Search
Processes” | |
• |
Soumen Chakrabarti — Indian Institute of Technology, Bombay (India):
• |
General research: machine learning, information retrieval, natural language
processing |
• |
Proposal title: “Entity and Relation Types in Web Search: Annotation Indexing
and Scoring Techniques” | |
• |
Kevin Chang — University of Illinois at Urbana-Champaign (U.S.):
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General research: information retrieval, information integration
|
• |
Proposal title: “Deepening Search: From the Surface to the Deep Web”
| |
• |
Bruce Croft — University of Massachusetts at Amherst (U.S.):
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General research: information retrieval |
• |
Proposal title: “Discovering and Using Meta-Terms”
| |
• |
Brian Davison — Lehigh University (U.S.):
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General research: machine learning, information retrieval |
• |
Proposal title: “Incorporating Trust Into Web Authority”
| |
• |
Zoubin Ghahramani — University of Cambridge (England), Carnegie Mellon
University (U.S.), University College London (England):
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General research: machine learning, information retrieval |
• |
Proposal title: “Statistical Machine Learning for User Modelling”
| |
• |
Anindya Ghose, Panagiotis Ipeirotis— New York University (U.S.):
• |
General research: machine learning, information retrieval,
econometrics |
• |
Proposal title: “Combining Econometric and Text Mining Approaches for
Measuring the Effect of Online Information Exchange”
| |
• |
Amélie Marian — Rutgers University (U.S.):
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General research: information retrieval |
• |
Proposal title: “The Truth Is out There: Aggregating Answers From Multiple
Web Sources” | |
• |
Alistair Moffat — University of Melbourne (Australia):
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General research: information retrieval |
• |
Proposal title: “Predictive Exploitation of Click-Through Knowledge”
| |
• |
Gerd Stumme — University of Kassel (Germany):
• |
General research: machine learning, information retrieval, social
software |
• |
Proposal title: “Social Search: Bringing the Social Component to the Web”
| |
• |
ChengXiang Zhai — University of Illinois at Urbana-Champaign (U.S.):
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General research: machine learning, information retrieval |
• |
Proposal title: “Mining Query/Click Logs for Collaborative Internet Search”
| |
More information about the grant recipients and their projects as well as
other funding opportunities by Microsoft can be found at http://research.microsoft.com/ur .
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