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Prediction of Customer Purchase Probablity for Online Recommendation Systems
- Han, Song-Yi;
- Kim, Jong Woo
초록
Tracking of online customers’ behavior is essential part in online recommendation systems. Specifically, for online recommendation at online stores, it is necessary to understanding customers’ purpose through their real-time activity data. This study suggests state probability methods that predict customers’ purchase probability using their clickstream data. Also, it verifies usefulness of the proposed method by using real clickstream data of an online book store. From experimental results, state probability models show better performance. Also, 2-state model with weight show best performance among proposed methods
키워드
Purchase probability; Clickstream data; Online Recommendation System
- 제목
- Prediction of Customer Purchase Probablity for Online Recommendation Systems
- 저자
- Han, Song-Yi; Kim, Jong Woo
- 발행일
- 2012-02
- 유형
- Proceeding
- 저널명
- International Proceedings of Computer Science and Information Technology
- 권
- 24
- 페이지
- 62 ~ 66