pyJedAI: A Library with resolution-related structures and procedures for products

Ekaterini Ioannou, Konstantinos Nikoletos, George Papadakis

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This work presents an open-source Python library, named pyJedAI, which provides functionalities supporting the creation of algorithms related to product entity resolution. Building over existing state-of-the-art resolution algorithms, the tool offers a plethora of important tasks required for processing product data collections. It can be easily used by researchers and practitioners for creating algorithms analyzing products, such as real-time ad bidding, sponsored search, or pricing determination. In essence, it allows users to easily import product data from the possible sources, compare products in order to detect either similar or identical products, generate a graph representation using the products and desired relationships, and either visualize or export the outcome in various forms. Our experimental evaluation on data from well-known online retailers illustrates high accuracy and low execution time for the supported tasks. To the best of our knowledge, this is the first Python package to focus on product entities and provide this range of product entity resolution functionalities.
Original languageEnglish
JournalINFORMS Journal on Computing
DOIs
Publication statusE-pub ahead of print - Sept 2024

Keywords

  • product entity resolution
  • integration
  • similarity
  • resolution open-source software
  • product-related structures/procedures

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