Improving the learning of Boolean queries by means of
a multiobjective IQBE evolutionary algorithm
Information Processing and Management, 42 (3):
615--632 (May 2006)DOI: doi:10.1016/j.ipm.2005.02.006
Abstract
The Inductive Query By Example (IQBE) paradigm allows
a system to automatically derive queries for a specific
Information Retrieval System (IRS). Classic IRSs based
on this paradigm Smith, M., & Smith, M. (1997). The
use of genetic programming to build Boolean queries for
text retrieval through relevance feedback. Journal of
Information Science, 23(6), 423-431
MartinPSmith:1997:JIS generate a single
solution (Boolean query) in each run, that with the
best fitness value, which is usually based on a
weighted combination of the basic performance criteria,
precision and recall. A desirable aspect of IRSs,
especially of those based on the IQBE paradigm, is to
be able to get more than one query for the same
information needs, with high precision arid recall
values or with different trade-offs between both.
IQBE process is proposed combining a previous basic
algorithm to automatically derive Boolean queries for
Boolean IRSs Smith, M., & Smith, M. (1997). The use of
genetic programming to build Boolean queries for text
retrieval through relevance feedback. Journal of
Information Science, 23(6), 423-431 and an advanced
evolutionary multiobjective approach Coello, C. A.,
Van Veldhuizen, D. A., & Lamant, G. B. (2002).
Evolutionary algorithms for solving multiobjective
problems. Kluwer Academic Publishers, which obtains
several queries with a different precision recall
trade-off in a single run. The performance of the new
proposal will be tested on the Cranfield and CACM
collections and compared to the well-known Smith and
Smith's algorithm, showing how it improves the learning
of queries and thus it could better assist the user in
the query formulation process.