Database Reference
In-Depth Information
in the form of offsets which can be readily obtained while indexing. The index-based
algorithms are quite different from their counterparts in stream processing.
We are currently working on incremental algorithms where the computation can be
stopped after detecting
k
patterns efficiently without having to use and compute all
patterns. With this it is also possible to consider ranking the results for their utility from
a users' viewpoint.
References
1. Salton, G., Wong, A., Yang, C.: A vector space model for automatic indexing. Communica-
tions of the ACM 18, 613-620 (1975)
2. Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. In: Proc. of
the WWW, Brisbane, Australia, pp. 107-117 (April 1998)
3. Callan, J., Croft, B., Harding, S.: The inquery retrieval system. In: Proc. of the DEXA, pp.
78-83 (1992)
4. Turtle, H., Croft, B.: Evaluation of an inference network-based retrieval model. ACM Trans-
actions on Information Systems 9, 187-222 (1991)
5. Elkhalifa, L., Adaikkalavan, R., Chakravarthy, S.: Infofilter: A system for expressive pattern
specification and detection over text streams. In: Proc. of the ACM SAC, Santa Fe, NM
(March 13-17, 2005)
6. Chakravarthy, S., Elkhalifa, L., Deshpande, N., Adaikkalavan, R., Liuzzi, R.A.: How To
Search for Complex Patterns Over Streaming and Stored Data. In: IC-AI, pp. 17-22 (2006)
7. Mauldin, M.L.: Lycos : Design choices in an internet search service. IEEE Expert (1997),
8. Witten, I., Moffat, A., Bell, T.: Managing Gigabytes: Compressing and Indexing Documents
and Images. Morgan Kauffman, San Francisco (1999)
9. Deshpande, N.: Infosearch : A system for searching and retrieving documents using complex
queries, Master's thesis, University of Texas at Arlington, Arlington (2005),
10. Java wordnet library,
http://sourceforge.net/projects/jwordnet
11. Berkeley db java edition,
