2024-03-28T18:36:04Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/4980
2021-12-13T04:09:02Z
1582963302567:1597824273898
user-ucsy
Analysis of User-based and Item-based Prediction Algorithms for Recommender System
Wai, Chit Hnin
Soe, Khin Thanda
Recommender Systems typically use techniquesfrom collaborative filtering which recommend itemsthat users with similar preferences have liked in thepast and, also predict new rating by averagingratings between pairs of similar users or items.Predictions come from three sources: predictionsbased on ratings of the same item by other users,predictions based on different item ratings made bythe same user, and ratings predicted based on datafrom other but similar users rating other but similaritems. In this system, we use prediction algorithms toprovide users with items that match their interestsbased on collaborative filtering (CF) approach. Oursystem use similarity measures between users, andalso between items from a single rating criteria .Weprovide analysis of user-based and item-basedprediction algorithms. The accuracy of thealgorithms is compared by Mean Absolute Error.
2010-12-16
http://hdl.handle.net/20.500.12678/0000004980
https://meral.edu.mm/records/4980