Discretization based framework to improve the recommendation quality
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 3 (31 May. 2021), pp.365-371, 7 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-05-31
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Economics & Business Administration
Abstract EN
Recommendation systems are information filtering software that delivers suggestions about relevant stuff from a massive collection of data.
Collaborative filtering approaches are the most popular in recommendations.
The primary concern of any recommender system is to provide favorable recommendations based on the rating prediction of user preferences.
In this article, we propose a novel discretization based framework for collaborative filtering to improve rating prediction.
Our framework includes discretization-based preprocessing, chi-square based attribution selection, and K-Nearest Neighbors (KNN) based similarity computation.
Rating prediction affords some basis for the judgment to decide whether recommendations are generated or not, subject to the ratio of performance of any recommendation system.
Experiments on two datasets MovieLens and BookCrossing, demonstrate the effectiveness of our method.
American Psychological Association (APA)
Ahmad, Bilal& Li, Wang. 2021. Discretization based framework to improve the recommendation quality. The International Arab Journal of Information Technology،Vol. 18, no. 3, pp.365-371.
https://search.emarefa.net/detail/BIM-1432220
Modern Language Association (MLA)
Ahmad, Bilal& Li, Wang. Discretization based framework to improve the recommendation quality. The International Arab Journal of Information Technology Vol. 18, no. 3 (May. 2021), pp.365-371.
https://search.emarefa.net/detail/BIM-1432220
American Medical Association (AMA)
Ahmad, Bilal& Li, Wang. Discretization based framework to improve the recommendation quality. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 3, pp.365-371.
https://search.emarefa.net/detail/BIM-1432220
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 370-371
Record ID
BIM-1432220