Linked taxonomies to capture usersʼ subjective assessments of items to facilitate accurate collaborative filtering-Reference-Cited by-同舟云学术

Linked taxonomies to capture usersʼ subjective assessments of items to facilitate accurate collaborative filtering

Published:2014-02 Issue: Volume:207 Page:52-68
ISSN:0004-3702
Container-title:Artificial Intelligence
language:en
Short-container-title:Artificial Intelligence

Author:

Nakatsuji Makoto,Fujiwara Yasuhiro

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference39 articles.

1. Categorising social tags to improve folksonomy-based recommendations;Cantador;J. Web Semant.,2011

2. K.H.L. Tso-Sutter, L.B. Marinho, S.-T. Lars, Tag-aware recommender systems by fusion of collaborative filtering algorithms, in: Proc. SACʼ08, pp. 1995–1999.

3. Y. Zhen, W.-J. Li, D.-Y. Yeung, TagiCoFi: tag informed collaborative filtering, in: Proc. RecSysʼ09, pp. 69–76.

4. I. Konstas, V. Stathopoulos, J.M. Jose, On social networks and collaborative recommendation, in: Proc. SIGIRʼ09, pp. 195–202.

5. The task-dependent effect of tags and ratings on social media access;Clements;ACM Trans. Inf. Syst.,2010

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Knowledge-aware response selection with semantics underlying multi-turn open-domain conversations;World Wide Web;2023-07-27

2. A systematic literature review of sparsity issues in recommender systems;Social Network Analysis and Mining;2020-02-11

3. Intelligent Agents System for Adaptive Assessment;Advances in Intelligent Systems and Computing;2019-06-25

4. A survey on data mining techniques in recommender systems;Soft Computing;2017-11-07

5. Scaling Locally Linear Embedding;Proceedings of the 2017 ACM International Conference on Management of Data;2017-05-09