Impact Transformation: Effective and Efficient Web Retrieval
Vo Ngoc Anh
Department of Computer Science and Software Engineering,
The University of Melbourne,
Victoria 3010, Australia.
Alistair Moffat
Department of Computer Science and Software Engineering,
The University of Melbourne,
Victoria 3010, Australia.
Status
Proc. 25th Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval,
Tampere, Finland, August 2002, pages 3-10.
Abstract
We extend the applicability of impact transformation, which is a
technique for adjusting the term weights assigned to documents so as
to boost the effectiveness of retrieval when short queries are
applied to large document collections.
In conjunction with techniques called quantization and thresholding,
impact transformation allows improved query execution rates compared
to traditional vector-space similarity computations, as the number of
arithmetic operations can be reduced.
The transformation also facilitates a new dynamic query pruning
heuristic.
We give results based upon the TREC web data that show the
combination of these various techniques to yield highly competitive
retrieval, in terms of both effectiveness and efficiency, for
both short and long queries.