A content-boosted collaborative filtering approach for movie recommendation based on local and global similarity and missing data prediction /

QR koda

A content-boosted collaborative filtering approach for movie recommendation based on local and global similarity and missing data prediction /

Shranjeno v:

Bibliografske podrobnosti
Glavni avtor:	Ozbal, Gozde.
Drugi avtorji:	Alpaslan, Ferda N., Karaman, Hilal.
Format:	Bài viết
Jezik:	English
Teme:	Collaborative filtering Floyd-Warshall algorithm Pearson correlation coefficient Recommender systems Sparsity User modelling
Oznake:	Označite Brez oznak, prvi označite!

Thư viện lưu trữ:	Thư viện Trường Đại học Đà Lạt

Podobne knjige/članki

Implementing Efficient Memory-Based Collaborative Filtering Recommendation Systems: Methods for Improving Scalability in Training Phase
od: Ho, Thi Hoang Vy, et al.
Izdano: (2024)

Build an E-commerce website with integrated purchase recommendations using Collaborative Filtering Technology
od: Nguyen, Duy Quang
Izdano: (2024)

Accuracy of the parallel analysis procedure with polychoric correlations /
od: Cho, Sun-Joo.

Featured Hybrid Recommendation System Using Stochastic Gradient Descent
od: Nguyen, Si Thin, et al.
Izdano: (2021)

Partitioning nonlinear filters for non-Gaussian initial conditions and correlated noises /
od: Giannakopoulos, P. K.

Research and Application of Objectives to Movie Recommendation
od: Tran, Thi Huong Ngan
Izdano: (2023)

Recommendation and Search in Social Networks
od: Ulusoy, Özgür, et al.
Izdano: (2015)

Dynamic matrix factorization-based collaborative filtering in movie recommendation services
od: Luong, Nguyen Vuong, et al.
Izdano: (2025)

Hybrid knowledge-infused collaborative filtering for enhanced movie clustering and recommendation
od: Thi, Thu Phan Hong, et al.
Izdano: (2025)

An Approach Based on Deep Learning that Recommends Fertilizers and Pesticides for Agriculture Recommendation
od: Nguyen, Ha Huy Cuong, et al.
Izdano: (2023)

Collaborative Decision Making: Perspectives and Challenges
od: Zaraté, Pascale, et al.
Izdano: (2013)

Item-based collaborative filtering recommendation model based on similarity matrix of items

Wikinomics How Mass Collaboration Changes Everything ( Expanded Edition)
od: Don, Tapscott, et al.
Izdano: (2025)

Building an online movie watching application that combines a recommendation system to improve user experience
od: Le, Hoang Tuong Vi
Izdano: (2024)

Collaborative brokerage, generative creativity, creative success Chen /
od: Fleming, Lee.

Enhancement in thermoelectric figure of merit in nanostructured Bi2Te3 with semimetal nanoinclusions /

Students' perceptions and practices of efl collaborative learning at university of foreign language studies - the university of danang
od: Vo Thi Hai Yen
Izdano: (2025)

Decision making operations: arithmetic mean, geometric mean, harmonic mean in user-based collaborative filtering of multi-criteria recommender systems
od: Huynh, Minh Tri, et al.
Izdano: (2018)

Practical Recommender Systems
od: Kim, Falk
Izdano: (2025)

Recommender Systems: The Textbook
od: Charu, C. Aggarwal
Izdano: (2025)

Building a social network integrated with content-based recommendation system
od: Le, Xuan Huong
Izdano: (2024)

Creative collaboration
od: Steiner, Vera John
Izdano: (2000)

Job Recommendation System
od: Le, Thi Thanh Ha
Izdano: (2023)

Building a Course platform combined with a Recommendation System
od: Hoang, Xuan Nam
Izdano: (2024)

Bookstore Integrated Recommender System
od: Dinh, Quang Linh
Izdano: (2023)

Building Diet suggestion application based on Recommendation System
od: Tran, Thi Thanh Xuan
Izdano: (2024)

Research on Product Recommendation System on E-Commerce Website System
od: Hoang, Phan Tuan Kiet
Izdano: (2025)

Build E-commerce with Recommendation Systems
od: Ngo, Van Thang
Izdano: (2024)

Research and Build a Commercial Website Integrated with Product Recommendation System
od: Vo, Minh Quan
Izdano: (2025)

Charles Heckscher, Paul S. Adler, eds. : The firm as a collaborative community : Reconstructing trust in the knowledge economy : book review /
od: Barker, James R.

Developing a Recommendation System for Electronic Components
od: Pham, Duy
Izdano: (2023)

Research And Implementation Of Recommendation Systems In Social Networks
od: Nguyen, Tien Dat
Izdano: (2025)

Building a Music Recommendation Application System
od: Nguyen, Quang Hoang Vu, et al.
Izdano: (2023)

Project Website Fashion using Recommender System
od: Luong, Thi Uyen Nhi
Izdano: (2023)

Developing a Recommendation System for Electronic Components
od: Tran, Thi Tu Oanh, et al.
Izdano: (2024)

Develop an E-commerce site with Recommendation System
od: Huynh, Thi Yen Linh
Izdano: (2024)

Tetrachoric correlation : A permutation alternative /
od: Long, Michael A.

On non-linear filtering problems for discrete time stochastic processes /
od: Matsuura, Masaya.

Research and Build a Music Recommendation Web Application
od: Dinh, Thanh Huy, et al.
Izdano: (2023)

Applying product Recommendation System in building a Bookstore website
od: Le, Thi My Lan
Izdano: (2024)

Notice: fwrite(): write of 697 bytes failed with errno=28 No space left on device in C:\vufind\module\VuFind\src\VuFind\Session\File.php on line 152
Cannot write session to C:\Windows\TEMP\vufind_sessions/sess_166appirm4r24gahqo0rn6k5m0
Warning: session_write_close(): Failed to write session data using user defined save handler. (session.save_path: \xampp\tmp) in C:\vufind\vendor\laminas\laminas-session\src\SessionManager.php on line 235