Skip to Main Content
Skip Nav Destination
ASME Press Select Proceedings

International Conference on Electronics, Information and Communication Engineering (EICE 2012)

By
Garry Lee
Garry Lee
Information Engineering Research Institute
Search for other works by this author on:
ISBN:
9780791859971
No. of Pages:
1008
Publisher:
ASME Press
Publication date:
2012

The amount information handled by information systems is growing steadily. This requires the use of recommendation systems for handling all this information. A recommendation system helps to find items of interest, but the development of this kind of systems is complicated due to the existence of a large number of algorithms for recommendation systems. In this context, this paper proposes an analysis of the algorithms used in recommendation systems and its most common application domain. The algorithms to calculate similarity presented in this paper are the algorithm of the cosine and Pearson correlation. The clustering algorithms analyzed are K-nearest neighbors (KNN) and clustering. All these algorithms are used in the collaborative filtering. The algorithms used for content-based filtering and hybrid approaches are Naive Bayes Classifier, Floyd-Warshall algorithm, Demographic recomm

This content is only available via PDF.
You do not currently have access to this chapter.
Close Modal

or Create an Account

Close Modal
Close Modal