This article presents a comprehensive approach to understanding and extracting eCommerce data by distinguishing between item representations (product descriptions) and user-item interactions (reviews). Utilizing the Amazon recommendation dataset, the authors retain a focused subset of data for effective analysis. The Ducho framework facilitates extraction processes, highlighting the importance of treating these two types of data separately in order to enhance data representation and user experience insights within an eCommerce context.
In this article, we distinguish user interactions from product descriptions in the context of eCommerce platforms to facilitate better extraction and representation of data.
We adopt the Amazon recommendation dataset for our analysis, choosing a small subset that includes 100 reviews along with corresponding product descriptions for context.
Ducho enables the extraction of product descriptions and user interactions from structured data, enhancing the understanding of user experiences and product performance.
The methodology emphasizes the significance of treating item descriptions and user-item interactions as separate yet interconnected data representations.
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