Faceted product search powered by the Semantic Web

Abstract

This paper presents a platform for multifaceted product search using Semantic Web technology. Online shops can use a ping service to submit their RDFa annotated Web pages for processing. The platform is able to process these RDFa annotated (X)HTML pages and aggregate product information coming from different Web stores. We propose solutions for the identification of products and the mapping of the categories in this process. Furthermore, when a loose vocabulary such as the Google RDFa vocabulary is used, the platform deals with the issue of heterogeneous information (e.g., currencies, rating scales, etc.).

Enriching Product Ads with Metadata from HTML Annotations

“…While there are several approaches concerned with products data categorization [12,8,15,13,16], the approach by Meusel at el. [11] is the most recent approach for exploiting Microdata annotations for categorization of products data.…”

“…The XploreProducts.com platform [16] is the first effort to integrate products from different online shops annotated using RDFa annotations. The approach is based on several string similarity functions for product matching.…”

A Product Feature-Based User-Centric Ranking Model for E-Commerce Search

“…Previous works have proposed to integrate several features which might be split into two categories. On one hand, the proposed approaches focus mainly on the product fields, namely its category and its description [4,18]. On the other hand, users' preferences and search intent are emphasized leading to a user-centered search process [9].…”

“…The latter may be characterized by several variations, accessories, and/or complementary products. Combining both approaches (product features [4,18] and user-centered [9]), our model ranks products with respect to their descriptive fields and category as well as their popularity highlighting the user engagement toward the product [14]. We evaluate our model while participating to the product search track of the Living Labs for IR (LL4IR) [17] of CLEF 2015 [11] and present also some analysis aiming at understanding the user engagement factor.…”

“…In fact, product search is becoming more important [18], leading to propose adapted retrieval tools in order to help customers to find their products of interest [5]. One example of product search tools is proposed by Google Shopping for which customers have found the utility with around 100 billions of submitted queries by month 3 .…”