Multi-instance genetic programming for web index recommendation.

Dept. of Computer Sciences and Numerical Analysis, University of Córdoba, Campus de Rabanales, edificio Albert Einstein, 14071 Córdoba, Spain; Dept. of Computer Sciences and Artificial Intelligence, University of Granada, Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain; Available online 26 March 2009.
Expert Syst. Appl 01/2009; 36:11470-11479. DOI: 10.1016/j.eswa.2009.03.059
Source: DBLP

ABSTRACT Abstract This article introduces the use of a multi-instance genetic programming algorithm for modelling u ser p referen ces in w eb in d ex reco m m en d atio n sy stem s. T h e d ev el- o p ed alg o rih tm learn s u ser in terest by m ean s o f ru les w h ich ad d co m p reh en sibility an d clarity to th e d iscov ered m o d els an d in crease th e q u ality o f th e reco m m en d a- tio n s. T h is n ew m o d el, called G 3 P -M I alg o rith m , is ev alu ated an d co m p ared w ith o th er av ailable alg o rith m s. C o m p u tatio n al ex p erim en ts sh ow th at o u r m eth o d o lo g y ach iev es co m p etitiv e resu lts an d p rov id e h ig h -q u ality u ser m o d els w h ich im p rov e th e accu racy o f reco m m en d atio n s. Key words:

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