Abstract
E-commerce is a constantly growing and competitive market. Online prices are updated daily or even more frequently, and it is very important for e-shoppers to find the lowest price online. Therefore, e-shop owners need to know the prices of their competitors and must be able to adjust their own prices in order to remain competitive. The manual monitoring of all prices of all products and competitors is too time-consuming; hence, the e-shop owners need software support for that task. For the development of such software tools the developers need a profound comprehension of the structure and design of e-shop websites. Existing software tools for Web data extraction are based on the findings of different website analyzes. The existing tools show: The more specific and detailed the analysis and the analyzed websites, the better the data extraction results. This paper presents the results and the derived findings of a deep analysis of 50 different e-shop websites in order to provide new insights for the development and improvement of software tools for product data extraction from e-shop websites.
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Notes
- 1.
Compound tag path from the root node of the website’s HTML tree to a particular element of the Web page.
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Horch, A., Wohlfrom, A., Weisbecker, A. (2017). An E-Shop Analysis with a Focus on Product Data Extraction. In: Bridge, D., Stuckenschmidt, H. (eds) E-Commerce and Web Technologies. EC-Web 2016. Lecture Notes in Business Information Processing, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-319-53676-7_5
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