Document (#30156)

Author
López-Pujalte, C.
Guerrero-Bote, V.P.
Moya-Anegón, F. de
Title
Order-based fitness functions for genetic algorithms applied to relevance feedback
Source
Journal of the American Society for Information Science and technology. 54(2003) no.2, S.152-160
Year
2003
Abstract
Lopez-Pujalte and Guerrero-Bote test a relevance feedback genetic algorithm while varying its order based fitness functions and generating a function based upon the Ide dec-hi method as a base line. Using the non-zero weighted term types assigned to the query, and to the initially retrieved set of documents, as genes, a chromosome of equal length is created for each. The algorithm is provided with the chromosomes for judged relevant documents, for judged irrelevant documents, and for the irrelevant documents with their terms negated. The algorithm uses random selection of all possible genes, but gives greater likelihood to those with higher fitness values. When the fittest chromosome of a previous population is eliminated it is restored while the least fittest of the new population is eliminated in its stead. A crossover probability of .8 and a mutation probability of .2 were used with 20 generations. Three fitness functions were utilized; the Horng and Yeh function which takes into account the position of relevant documents, and two new functions, one based on accumulating the cosine similarity for retrieved documents, the other on stored fixed-recall-interval precessions. The Cranfield collection was used with the first 15 documents retrieved from 33 queries chosen to have at least 3 relevant documents in the first 15 and at least 5 relevant documents not initially retrieved. Precision was calculated at fixed recall levels using the residual collection method which removes viewed documents. One of the three functions improved the original retrieval by127 percent, while the Ide dec-hi method provided a 120 percent improvement.
Theme
Retrievalstudien
Retrievalalgorithmen

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  3. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.27
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  4. Smith, M.P.; Smith, M.: ¬The use of genetic programming to build Boolean queries for text retrieval through relevance feedback (1997) 0.26
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