These datasets originate from PriceRunner, a popular product comparison platform. They contain product-related information including product IDs, titles, and categories. It can be used for numerous tasks, such as classification, clustering, record linkage, etc.
Column description:
* Product ID
* Product Title as it appears in the respective product comparison platform (lower case and with punctuation removed)
* Vendor ID: the ID of the electronic store that provides the product.
* Cluster ID: the ID of the cluster that the product belongs to. Useful for entity matching and clustering tasks.
* Cluster Label: The title of the aforementioned cluster.
* Category ID: the ID of the category that the product belongs to. Useful for classification and categorization tasks.
* Category Label: The title of the aforementioned category.
Citations:
* L. Akritidis, A. Fevgas, P. Bozanis, C. Makris, "A Self-Verifying Clustering Approach to Unsupervised Matching of Product Titles", Artificial Intelligence Review (Springer), pp. 1-44, 2020.
* L. Akritidis, P. Bozanis, "Effective Unsupervised Matching of Product Titles with k-Combinations and Permutations", In Proceedings of the 14th IEEE International Conference on Innovations in Intelligent Systems and Applications (INISTA), pp. 1-10, 2018.
* L. Akritidis, A. Fevgas, P. Bozanis, "Effective Product Categorization with Importance Scores and Morphological Analysis of the Titles", In Proceedings of the 30th IEEE International Conference on Tools with Artificial Intelligence IICTAI), pp. 213-220, 2018.