JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Effective and Efficient Similarity Measures for Purchase Histories Considering Product Taxonomy |
| 영문제목(English Title) |
Effective and Efficient Similarity Measures for Purchase Histories Considering Product Taxonomy |
| 저자(Author) |
Yu-Jeong Yang
Ki Yong Lee
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| 원문수록처(Citation) |
VOL 17 NO. 01 PP. 0107 ~ 0123 (2021. 02) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
In an online shopping site or offline store, products purchased by each customer over time form the purchase history of the customer. Also, in most retailers, products have a product taxonomy, which represents a hierarchical classification of products. Considering the product taxonomy, the lower the level of the category to which two products both belong, the more similar the two products. However, there has been little work on similarity measures for sequences considering a hierarchical classification of elements. In this paper, we propose new similarity measures for purchase histories considering not only the purchase order of products but also the hierarchical classification of products. Unlike the existing methods, where the similarity between two elements in sequences is only 0 or 1 depending on whether two elements are the same or not, the proposed method can assign any real number between 0 and 1 considering the hierarchical classification of elements. We apply this idea to extend three existing representative similarity measures for sequences. We also propose an efficient computation method for the proposed similarity measures. Through various experiments, we show that the proposed method can measure the similarity between purchase histories very effectively and efficiently.
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| 키워드(Keyword) |
Hierarchical Classification
Purchase History
Sequence Similarity
Similarity Measure
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| 파일첨부 |
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