검색연산자 | 기능 | 검색시 예 |
---|---|---|
() | 우선순위가 가장 높은 연산자 | 예1) (나노 (기계 | machine)) |
공백 | 두 개의 검색어(식)을 모두 포함하고 있는 문서 검색 | 예1) (나노 기계) 예2) 나노 장영실 |
| | 두 개의 검색어(식) 중 하나 이상 포함하고 있는 문서 검색 | 예1) (줄기세포 | 면역) 예2) 줄기세포 | 장영실 |
! | NOT 이후에 있는 검색어가 포함된 문서는 제외 | 예1) (황금 !백금) 예2) !image |
* | 검색어의 *란에 0개 이상의 임의의 문자가 포함된 문서 검색 | 예) semi* |
"" | 따옴표 내의 구문과 완전히 일치하는 문서만 검색 | 예) "Transform and Quantization" |
Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.
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