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Recent years have seen significant use of semantic annotations in the e-commerce domain, where online shops (e-shops) are increasingly adopting semantic markup languages to describe their products in order to improve their visibility. Statistics from the Web Data Commons project show that 37% of the websites covered by a large web crawl provide semantic annotations. 849,000 of these websites annotate product data using the schema.org classes product and offer. However, fully utilising such a gigantic data source still faces significant challenges. This is because the adoption of semantic markup practice has been generally shallow and to a certain extent inconsistent. For example, less than 10% of product instances are annotated with a category; categorisation systems used by different e-shops are highly inconsistent; the same products are offered on different websites, often presenting complementary and sometimes even conflicting information.
Addressing these challenges requires an orchestra of semantic technologies tailored to the product domain, such as product classification, product offer matching, and product taxonomy matching. Such tasks are also crucial elements for the construction of product knowledge graphs, which are used by large, cross-sectoral e-commerce vendors.
This challenge aims to benchmark methods and systems dealing with two fundamental tasks in e-commerce data integration: (1) product matching (task one) and (2) product classification (task two) . We develop datasets and resources to share with the community, in order to encourage and facilitate research in these directions. Participating teams may choose to take part in either, or both tasks. Teams successfully beating the baseline of the respective task, will be invited to write a paper describing their method and system and present the method as a poster (and potentially also a short talk) at the ISWC2020 conference. Winners of each task will also be awarded 500 euro.
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Organizing committee
- Dr Ziqi Zhang (Information School, The University of Sheffield)
- Prof. Christian Bizer (Institute of Computer Science and Business Informatics, The Mannheim University)
- Dr Haiping Lu (Department of Computer Science, The University of Sheffield)
- Dr Jun Ma (Amazon Inc. Seattle, US)
- Prof. Paul Clough (Information School, The University of Sheffield & Peak Indicators)
- Ms Anna Primpeli (Institute of Computer Science and Business Informatics, The Mannheim University)
- Mr Ralph Peeters (Institute of Computer Science and Business Informatics, The Mannheim University)
- Mr. Abdulkareem Alqusair (Information School, The University of Sheffield)