Asia Pacific Journal of Information Systems (APJIS)

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Current Issue

Date	June 2017
Vol. No.	Vol. 27 No. 2
DOI	https://doi.org/10.14329/apjis.2017.27.2.126
Page	126~138
Title	An Exploratory Study of Collaborative Filtering Techniques to Analyze the Effect of Information Amount
Author	Hyun Sil Moon, Jung Hyun Yoon, Il Young Choi, Jae Kyeong Kim
Keyword	Information Amount, Recommender System, Collaborative Filtering, Personalization Technique, Performance Analysis
Abstract	The proliferation of items increased the difficulty of customers in finding the specific items they want to purchase. To solve this problem, companies adopted recommender systems, such as collaborative filtering systems, to provide personalization services. However, companies use only meaningful and essential data given the explosive growth of data. Some customers are concerned that their private information may be exposed because CF systems necessarily deal with personal information. Based on these concerns, we analyze the effects of the amount of information on recommendation performance. We assume that a customer could choose to provide overall information or partial information. Experimental results indicate that customers who provided overall information generally demonstrated high performance, but differences exist according to the characteristics of products. Our study can provide companies with insights concerning the efficient utilization of data.