A Comprehensive Performance Evaluation in Collaborative Filtering (협업필터링에서 포괄적 성능평가 모델 )

Seok-Jong Yu (유석종)

A Comprehensive Performance Evaluation in Collaborative Filtering

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2012, 17(4), pp.83-90
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

Seok-Jong Yu ¹

¹숙명여자대학교

Accredited

ABSTRACT

In e-commerce systems that deal with a large number of items, the function of personalized recommendation is essential. Collaborative filtering that is a successful recommendation algorithm, suffers from the sparsity, cold-start, and scalability restrictions. Additionally, this work raises a new flaw of the algorithm, inconsistent performance of recommendation. This is also not measurable by the current MAE-based evaluation that does not consider the deviation of prediction error, and furthermore is performed independently of precision and recall measurement. To evaluate the collaborative filtering comprehensively, this work proposes an extended evaluation model that includes the current criteria such as MAE, Precision, Recall, deviation, and applies it to cluster-based combined collaborative filtering.

KEYWORDS

Recommender System, Collaborative Filtering, Performance Evaluation, MAE Reduction

Citation status

* References for papers published after 2023 are currently being built.

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Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65