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Handling Incomplete Data Problem in Collaborative Filtering System
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Hyunju Noh (Graduate School of Management, KAIST)
Minjung Kwak (Department of Information Statistics, Pyongtaek University)
Ingoo Han (Graduate School of Management, KAIST)
Vol. 9, No. 2, Page: 51 ~ 63
Keywords
Multiple Imputation, Collaborative Filtering, Incomplete data
Abstract
Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. There are several treatments to deal with the incomplete data problem such as case deletion and single imputation. Those approaches are simple and easy to implement but they may provide biased results. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.
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Handling Incomplete Data Problem in Collaborative Filtering System
노현주 (KAIST 테크노경영대학원)
곽민정 (평택대학교 정보통계학과)
한인구 (KAIST 테크노경영대학원)
Cite this article
JIIS Style
Noh, H., M. Kwak, and I. Han, "Handling Incomplete Data Problem in Collaborative Filtering System", Journal of Intelligence and Information Systems, Vol. 9, No. 2 (2003), 51~63.

IEEE Style
Hyunju Noh, Minjung Kwak, and Ingoo Han, "Handling Incomplete Data Problem in Collaborative Filtering System", Journal of Intelligence and Information Systems, vol. 9, no. 2, pp. 51~63, 2003.

ACM Style
Noh, H., Kwak, M., and Han, I., 2003. Handling Incomplete Data Problem in Collaborative Filtering System. Journal of Intelligence and Information Systems. 9, 2, 51--63.
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@article{Noh:JIIS:2003:165,
author = {Noh, Hyunju and Kwak, Minjung and Han, Ingoo},
title = {Handling Incomplete Data Problem in Collaborative Filtering System},
journal = {Journal of Intelligence and Information Systems},
issue_date = {November 2003},
volume = {9},
number = {2},
month = Nov,
year = {2003},
issn = {2288-4866},
pages = {51--63},
url = {},
doi = {},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Multiple Imputation, Collaborative Filtering and Incomplete data },
}
%0 Journal Article
%1 165
%A Hyunju Noh
%A Minjung Kwak
%A Ingoo Han
%T Handling Incomplete Data Problem in Collaborative Filtering System
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 9
%N 2
%P 51-63
%D 2003
%R
%I Korea Intelligent Information System Society