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Jones, G.; Robertson, A.M.; Willett, P.: ¬An introduction to genetic algorithms and to their use in information retrieval (1994)
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- Abstract
- This paper provides an introduction to genetic algorithms, a new approach to the investigation of computationally-intensive problems that may be insoluble using conventional, deterministic approaches. A genetic algorithm takes an initial set of possible starting solutions and then iteratively improves theses solutions using operators that are analogous to those involved in Darwinian evolution. The approach is illusrated by reference to several problems in information retrieval
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Robertson, A.M.; Willett, P.: Use of genetic algorithms in information retrieval (1995)
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- Abstract
- Reviews the basic techniques involving genetic algorithms and their application to 2 problems in information retrieval: the generation of equifrequent groups of index terms; and the identification of optimal query and term weights. The algorithm developed for the generation of equifrequent groupings proved to be effective in operation, achieving results comparable with those obtained using a good deterministic algorithm. The algorithm developed for the identification of optimal query and term weighting involves fitness function that is based on full relevance information
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Robertson, A.M.; Willett, P.: Generation of equifrequent groups of words using a genetic algorithm (1994)
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- Abstract
- Genetic algorithms are a class of non-deterministic algorithms that derive from Darwinian evolution and that provide good, though not necessarily optimal, solutions to combinatorial problems. We describe their application to the identification of characteristics that occur approximately equifrequently in a database, using two different methods for the creation of the chromosome data structures that lie at the heart of a genetic algortihm. Experiments with files of English and Turkish text suggest that the genetic algorithm developed here can produce results superior to those produced by existing non-deterministic algorithms; however, the results are inferior to those produced by an existing deterministic algorithm
