CAREER: Future of Search: User, Social Networks and Language

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How to retrieve relevant information for a specific user under a specific set of circumstances is a challenging research problem. The goal of this research project is to tackle this challenge and lay the foundation for the next generation of search engines. Instead of simply matching a query to documents that contain query words, the approach developed here is a unified user-centric retrieval framework that consists of: (1) personalization: learning a user model that takes into consideration the content, context and decision criteria of a user; (2) language processing: learning better text representation for retrieval from heterogeneous corpus and linguistic resources; and (3) social networks: further improving the user model based on social norms and a user's social networks. To evaluate the framework, a personalized social search engine will be developed. The result of this project will be a unified retrieval framework with a set of novel techniques applicable across a wide range of information retrieval (IR) tasks, including: search engines, recommender systems and adaptive filtering systems. Through the PI's industry collaboration, the results of this project are expected to be incorporated in commercial systems, and thus benefit millions of users. K-12 students, undergraduate, graduate students, and engineers in Silicon Valley will be involved and benefit from the project. The project will lead to research-based educational materials (lecture slides, video lectures, book chapters and course projects). Project results, including publications, open source software, annotated data sets, demos and course materials, will be disseminated via the project website (http://www.soe.ucsc.edu/~yiz/futureofsearch).