A Generic Fuzzy-Based Recommendation Approach (GFBRA)

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dc.contributor.authorBOUACHA Ismail
dc.date.accessioned2025-09-10T07:36:24Z
dc.date.available2025-09-10T07:36:24Z
dc.date.issued2022
dc.descriptionInternational Journal of Fuzzy System Applications Volume 11 .Issue 1 DOI: 10.4018/IJFSA.292461
dc.description.abstractRecommender systems aim to automatically provide users with personalized information in an overloaded search space. To dual withvagueness and imprecision problems inRS, severalresearches have proposed fuzzy- based approaches. Even though these works have incorporatedexperimental evaluation, they were used in differentrecommendations cenarios which makes it difficult to have a fair comparison between them. Also, some of them performed anitems and/or users clustering before generating recommendations. For this reason,they need additional information such as item attributes or trustbetween users which are not always available. Inthispaper, theauthors propose to use fuzzy set techniques to predict the rating of a target user for each unrated item.It uses the target user’shistory in addition with rating of similar users which allows to the target user to contribute in the recommendation process. Experimental results on several datasets seem to be promising in term of MAE (meanaverageerror), RMSE (root mean square error), accuracy, precision, recall, andf-measure
dc.identifier.urihttp://dspace.ensti-annaba.dz:4000/handle/123456789/747
dc.language.isoen
dc.publisherInternational Journal of Fuzzy System Applications
dc.titleA Generic Fuzzy-Based Recommendation Approach (GFBRA)
dc.typeArticle
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