Typology of Personalization in Recommender Systems
Purpose: With the development of science and technology, large volumes of structured, semi-structured, and unstructured data are generated daily at breakneck speeds from various sources. This data generated by different users share many common patterns that can be filtered and analyzed to make recom...
Saved in:
Main Authors: | Marziyeh Nourahmadi, Hojjatollah Sadeqi |
---|---|
Format: | Article |
Language: | fas |
Published: |
Ayandegan Institute of Higher Education, Tonekabon,
2022-05-01
|
Series: | مدیریت نوآوری و راهبردهای عملیاتی |
Subjects: | |
Online Access: | http://www.journal-imos.ir/article_137336_b477c29e386e9d8a9d9c70e359d1544c.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Designing a Stock Recommender System Using the Collaborative Filtering Algorithm for the Tehran Stock Exchange
by: Marziyeh Nourahmadi, et al.
Published: (2024-06-01) -
A Clustering of Investors' Behavior according to Their Financial, Behavioral, and Demographic Characteristics (An Application of K-means Algorithm)
by: Marziyeh Nourahmadi, et al.
Published: (2021-08-01) -
Enhancing Marketing Personalized Shopping Recommendations in the UAE: Leveraging Logic Mining and Advanced Technologies
by: SHWEDEH Fanar, et al.
Published: (2024-12-01) -
Low-frequency spectral graph convolution networks with one-hop connections information for personalized tag recommendation
by: Zhengshun Fei, et al.
Published: (2024-11-01) -
Multimodal Recommendation System Based on Cross Self-Attention Fusion
by: Peishan Li, et al.
Published: (2025-01-01)