Top Search Technology Proposals in the Yahoo! Key Scientific Challenges
- Posted April 21st, 2009 at 8:00 am by Yahoo! Search
- Categories: News/Announcements
This week, Yahoo! Labs announced the winners of our inaugural Key Scientific Challenges Program, where we provide seed funding and support for a handful of top Ph.D students who submitted proposals in Yahoo! Labs core research areas. Yahoo!’s senior research scientist Evgeniy Gabrilovich, who helped review the contest entries along with Ravi Kumar, Belle Tseng and Raghu Ramakrishnan, called out these winning proposals in the search technology category:
• Vertical Selection by Jaime Arguello of Carnegie Mellon University. Arguello’s proposal addresses vertical selection in search, the problem of selecting the verticals relevant to a user’s query. Arguello proposed research for better ways to acquire useful representations of vertical content and the need to model vertical search engine effectiveness on a query. His goal is to set up a framework for vertical selection by a search engine.
• Attention Routing by Polo Chau of Carnegie Mellon University’s Machine Learning Department. Chau conducts research on integrating data mining and human-computer interaction (HCI) to create an umbrella system for interactive mining of large graphs. Chau’s system provides fast, scalable tools to help analysts explore, visualize, and understand large graphs, like social networks, and pinpoint patterns, anomalies, and interesting properties among them.
• Detecting Searcher Frustration by Henry Feild of University of Massachusetts, Amherst. Feild’s proposal uses query logs to explore session boundary, task categorization, and ultimately detect when a search user has trouble finding the information they want. Through what Feild calls, “frustration detection and intervention,” he will build models to analyze the different causes of user frustration and develop new methods to address these issues.
• Object Search by Kim Cuong Pham of University of Illinois at Urbana-Champagne. Pham approached the idea of a semantic Web from a new angle. Instead of semantic Web’s original vision of embedding semantic data, he wants to use “computer technologies to search, read, analyze, and understand the Web, given its unstructured and somewhat chaotic format.” By understanding structured information on the Web, Pham says, “We are able to answer questions like “what are the homepages of all professors working in the database field,” or “what are all the shopping pages that sell digital cameras of at least 6MP but not less than $300.”
Winners receive funding and exclusive access to Yahoo! research scientists and data sets. You can see a list of all the winners on the Yahoo! Key Scientific Challenges Program Website.
- 1 Comment