A proposed configurable approach for recommendation systems via data mining techniques
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Date
2018
Journal Title
Journal ISSN
Volume Title
Type
Article
Publisher
TAYLOR & FRANCIS LTD
Series Info
ENTERPRISE INFORMATION SYSTEMS;Volume: 12 Issue: 2 Pages: 196-217
Doi
Scientific Journal Rankings
Abstract
This study presents a configurable approach for recommendations which determines the suitable recommendation method for each field based on the characteristics of its data, the method includes determining the suitable technique for selecting a representative sample of the provided data. Then selecting the suitable feature weighting measure to provide a correct weight for each feature based on its effect on the recommendations. Finally, selecting the suitable algorithm to provide the required recommendations. The proposed configurable approach could be applied on different domains. The experiments have revealed that the approach is able to provide recommendations with only 0.89 error rate percentage.
Description
Accession Number: WOS:000423839700005
Keywords
October University for University for sampling, data mining, features' selection, clustering, Recommendation systems