Asia pacific journal of information systems

The Korea Society of Management Information Systems (한국경영정보학회)
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An Exploratory Study of Collaborative Filtering Techniques to Analyze the Effect of Information Amount

  • Received : 2017.05.06
  • Accepted : 2017.06.28
  • Published : 2017.06.30
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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.

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Acknowledgement

This work was supported by a grant from Kyung Hee University in 2013.(KHU-20130544)

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