An Electronic Commerce Recommendation Algorithm Joining Case-Based Reasoning and Collaborative Filtering
- DOI
- 10.2991/iiicec-15.2015.263How to use a DOI?
- Keywords
- An Electronic Commerce Recommendation Algorithm Joining Case-Based Reasoning and Collaborative Filtering
- Abstract
With the rapid development of network, information technology has provided an unprecedented amount of information resources. It has also led to the problem of information overload. Electronic commerce personalized recommender systems represent services that aim at predicting a customer’s interest on information products available in the application domain, using customers’ ratings on products. Peoples’ experiences often do not enough to deal with the vast amount of available information. Thus, methods to help find products of electronic commerce have attracted much attention from both researchers and vendors. Collaborative filtering technology has proved to be one of the most effective for its simplicity in both theory and implementation. The paper gives an electronic commerce recommendation algorithm combining case-based reasoning and collaborative filtering. Firstly, it uses case-based reasoning to fill the vacant ratings. Then, it produces prediction collaborative filtering. The presented algorithm combining case-based reasoning and collaborative filtering can alleviate the sparsity issue.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Dongyan Wu PY - 2015/03 DA - 2015/03 TI - An Electronic Commerce Recommendation Algorithm Joining Case-Based Reasoning and Collaborative Filtering BT - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference PB - Atlantis Press SP - 1189 EP - 1192 SN - 2352-538X UR - https://doi.org/10.2991/iiicec-15.2015.263 DO - 10.2991/iiicec-15.2015.263 ID - Wu2015/03 ER -