Web Data Commons Training and Test Sets for Large-Scale Product Matching - Version 2.0

Version
V0
Resource Type
Dataset
Creator
  • Peeters, Ralph (University of Mannheim (Germany))
  • Primpeli, Anna (University of Mannheim (Germany))
  • Bizer, Christian (University of Mannheim (Germany))
Publication Date
2020-11-26
Free Keywords
schema.org; product matching; entity matching; identity resolution; record linkage; e-commerce
Description
  • Abstract

    Many e-shops have started to mark-up product data within their HTML pages using the schema.org vocabulary. The Web Data Commons project regularly extracts such data from the Common Crawl, a large public web crawl. The Web Data Commons Training and Test Sets for Large-Scale Product Matching contain product offers from different e-shops in the form of binary product pairs (with corresponding label “match” or “no match”) for four product categories, computers, cameras, watches and shoes. In order to support the evaluation of machine learning-based matching methods, the data is split into training, validation and test sets. For each product category, we provide training sets in four different sizes (2.000-70.000 pairs). Furthermore there are sets of ids for each training set for a possible validation split (stratified random draw) available. The test set for each product category consists of 1.100 product pairs. The labels of the test sets were manually checked while those of the training sets were derived using shared product identifiers from the Web weak supervision. The data stems from the WDC Product Data Corpus for Large-Scale Product Matching - Version 2.0 which consists of 26 million product offers originating from 79 thousand websites. For more information and download links for the corpus itself, please follow the links below.
Availability
Download
This study is freely available to the general public via web download.
Relations
  • Has version
    DOI: 10.3886/E127481V1
Publications
  • Peeters, Ralph, Anna Primpeli, Benedikt Wichtlhuber, and Christian Bizer. “Using Schema.Org Annotations for Training and Maintaining Product Matchers.” Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics. New York, NY, USA: ACM, June 30, 2020. https://doi.org/10.1145/3405962.3405964.
    • ID: 10.1145/3405962.3405964 (DOI)
  • Primpeli, Anna, Ralph Peeters, and Christian Bizer. “The WDC Training Dataset and Gold Standard for Large-Scale Product Matching.” Companion Proceedings of The 2019 World Wide Web Conference. New York, NY, USA: ACM, May 13, 2019. https://doi.org/10.1145/3308560.3316609.
    • ID: 10.1145/3308560.3316609 (DOI)

Update Metadata: 2020-11-26 | Issue Number: 1 | Registration Date: 2020-11-26