CIF: Small: A Theoretical Framework for Dynamic Collaborative Online Information Searching

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The Internet today has been transformed from a network providing connectivity, to a massive repository of human and machine knowledge, with information relevant to nearly every aspect of human life stored in some corner. Search engines allow keyword-based search of this knowledge, and while natural language queries are increasingly useful, searching for complex information often requires human thinking (augmented with the capabilities of search engines) to obtain useful search results. Routine problems require individuals to search the Internet for relevant ideas, a task which may be hindered by lack of expertise in the appropriate subject matters. With pervasive online connectivity, there are potentially unlimited ‘experts’ (or just helpers) available online to contribute their knowledge to problems related to their expertise. This project envisions tapping such potential experts (or helpers) to handle a large number of requests for information, leveraging the power of online collaboration. The relevance of this project should be increasingly apparent as the world moves towards a knowledge-based economy where the Internet is used for collaborative work, a significant part of which involves searching for information. The project will train students who will understand and extend the proposed approach. This project proposes a novel theoretical framework to analyze the dynamics of information searching. It includes information searching to handle multiple requests, collaboration of multiple experts from different fields, exploration of the concepts of expertise mismatch with the population of generated requests, and of diversity of expertise to allow faster searches for multi-disciplinary requests. While the issues to be studied bear similarity with multi-class queuing and scheduling, information searching uniquely uses information-theoretic ideas. These research activities require an interesting interplay between the fields of information theory, queuing theory, scheduling, and social network concepts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.