Abstract
Just-In-Time Information Retrieval agents proactively retrieve information based on queries that are implicit in, and formulated from, the user’s current context, such as the blogpost she is writing. This paper compares five heuristics by which queries can be extracted from a user’s blogpost or other document. Four of the heuristics use shallow Natural Language Processing techniques, such as tagging and chunking. An experimental evaluation reveals that most of them perform as well as a heuristic based on term weighting. In particular, extracting noun phrases after chunking is one of the more successful heuristics and can have lower costs than term weighting. In a trial with real users, we find that relevant results have higher rank when we use implicit queries produced by this chunking heuristic than when we use explicit user-formulated queries.
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References
Budzik, J., Hammond, K.: Watson: Anticipating and contextualizing information needs. In: Procs. of the 62nd Annual Meeting of the American Society for Information Science, pp. 727–740 (1999)
Budzik, J., Hammond, K.J., Birnbaum, L., Krema, M.: Beyond similarity. In: Working notes of the AAAI Workshop on AI for Web Search (2000)
Henzinger, M., Chang, B.-W., Milch, B., Brin, S.: Query-free news search. In: Procs. of the 12th Intl. World-Wide Web Conference, pp. 1–10 (2003)
Lieberman, H., Fry, C., Weitzman, L.: Exploring the web with reconnaissance agents. CACM 44(8), 69–75 (2001)
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)
Meade, J., Costello, F., Kushmerick, N.: Inferring topic probability for just-in-time information retrieval. In: Bell, D.A., et al. (eds.) Procs. of the 17th Irish Conference on Artificial Intelligence & Cognitive Science, pp. 103–112 (2006)
Rhodes, B.: Using physical context for just-in-time information retrieval. IEEE Trans. on Computers 52(8), 1011–1014 (2003)
Rhodes, B.J.: Just-In-Time Information Retrieval. PhD thesis, Massachusetts Institute of Technology (2000)
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Gao, A., Bridge, D. (2010). Using Shallow Natural Language Processing in a Just-In-Time Information Retrieval Assistant for Bloggers. In: Coyle, L., Freyne, J. (eds) Artificial Intelligence and Cognitive Science. AICS 2009. Lecture Notes in Computer Science(), vol 6206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17080-5_13
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DOI: https://doi.org/10.1007/978-3-642-17080-5_13
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