✦ LIBER ✦

Improved collaborative filtering algorithm based on heat conduction

✍ Scribed by Guo, Qiang ;Liu, Jianguo ;Wang, Binghong

Book ID: 107475628
Publisher: Higher Education Press and Springer
Year: 2009
Tongue: English
Weight: 308 KB
Volume: 3
Category: Article
ISSN: 1673-7350
DOI: 10.1007/s11704-009-0050-2

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Information filtering via weighted heat

Information filtering via weighted heat conduction algorithm

✍ Jian-Guo Liu; Qiang Guo; Yi-Cheng Zhang 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 494 KB

Empirical assessment of a collaborative

Empirical assessment of a collaborative filtering algorithm based on OWA operators

✍ Miguel-Angel Sicilia; Elena García-Barriocanal; Salvador Sánchez-Alonso 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 129 KB

Classical collaborative filtering algorithms generate recommendations on the basis of ratings provided by users that express their subjective preference on concrete items. The correlation of ratings is used in such schemes as an implicit measure of common interest between users, that is used to pred

A collaborative filtering recommendation

A collaborative filtering recommendation algorithm based on item and cloud model

✍ Shuliang Wang; Yuan Xie; Meng Fang 📂 Article 📅 2011 🏛 Wuhan University 🌐 English ⚖ 278 KB

Collaborative filtering based on multi-c

Collaborative filtering based on multi-channel diffusion

✍ Ming-Sheng Shang; Ci-Hang Jin; Tao Zhou; Yi-Cheng Zhang 📂 Article 📅 2009 🏛 Elsevier Science 🌐 English ⚖ 373 KB

Collaborative filtering algorithms based

Collaborative filtering algorithms based on Kendall correlation in recommender systems

✍ Yao Yu; Zhu Shanfeng; Chen Xinmeng 📂 Article 📅 2006 🏛 Wuhan University 🌐 English ⚖ 488 KB

An improved particle filtering algorithm

An improved particle filtering algorithm based on observation inversion optimal sampling

✍ Hu, Zhen-tao ;Pan, Quan ;Yang, Feng ;Cheng, Yong-mei 📂 Article 📅 2009 🏛 Chinese Electronic Periodical Services 🌐 English ⚖ 326 KB