Intelligent Online Store: User Behavior Analysis based Recommender System
Recommender systems provide personalised recommendations to users, helping them find their ideal items, also play a key role in encouraging users to make their purchases through websites thus leading to the success of online stores. The collaborative filtering method is one of the most successful te...
Saved in:
| Main Authors: | Mohamadreza Karimi Alavije, Shiva Askari, Sirvan Parasite |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Tehran
2015-06-01
|
| Series: | Journal of Information Technology Management |
| Subjects: | |
| Online Access: | https://jitm.ut.ac.ir/article_53884_4a365079a618ddd9ac5aa8c933f8ce05.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Advanced Clustering Techniques with Bio-Inspired for Collaborative Filtering Recommendation Systems
by: Luong Vuong Nguyen
Published: (2025-02-01) -
Empowering Education: Leveraging Clustering and Recommendations for Enhanced Student Insights
by: Kheira Ouassif, et al.
Published: (2025-06-01) -
Advancing Diversity in Recommendation Systems Through Collaborative Filtering: A Focus on Media Content
by: Chandro Pardede, et al.
Published: (2025-03-01) -
Efficient Machine Learning Algorithms in Hybrid Filtering Based Recommendation System
by: . Ruchika, et al.
Published: (2023-08-01) -
From Rating Predictions to Reliable Recommendations in Collaborative Filtering: The Concept of Recommendation Reliability Classes
by: Dionisis Margaris, et al.
Published: (2025-04-01)