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An Automated Approach to Product Taxonomy Mapping in E-Commerce

  • Lennart Nederstigt
  • Damir Vandic
  • Flavius Frasincar
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 171)

Abstract

Due to the ever-growing amount of information available on Web shops, it has become increasingly difficult to get an overview of Web-based product information. There are clear indications that better search capabilities, such as the exploitation of annotated data, are needed to keep online shopping transparent for the user. For example, annotations can help present information from multiple sources in a uniform manner. This paper proposes an algorithm that can autonomously map heterogeneous product taxonomies forWeb shop data integration purposes. The proposed approach uses word sense disambiguation techniques, approximate lexical matching, and a mechanism that deals with composite categories. Our algorithm’s performance on three real-life datasets was compared favourably against two other state-of-the-art taxonomy mapping algorithms. The experiments show that our algorithm performs at least twice as good compared to the other algorithms w.r.t. precision and F-measure.

Keywords

e-commerce taxonomy mapping word sense disambiguation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Lennart Nederstigt
    • 1
  • Damir Vandic
    • 1
  • Flavius Frasincar
    • 1
  1. 1.Econometric InstituteErasmus University RotterdamRotterdamThe Netherlands

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