Code and Data Repository for pyJedAI: A Library with Resolution-Related Structures and Procedures for Products
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 (Papadakis et al. 2021a), the tool offers a plethora of important tasks required for processing product data collections. It be can easily used by researchers and practitioners for creating algorithms analyzing products, such as real-time ads bidding, sponsored search, or pricing determination. In essence, it allows 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.
Authors
- George Papadakis (ORCID: https://orcid.org/0000-0002-7298-9431)
- Ekaterini Ioannou (ORCID: https://orcid.org/0000-0002-4922-6639)
- Konstantinos Nikoletos (ORCID: https://orcid.org/0000-0003-3465-1197)
Publication Details
- Journal
- INFORMS journal on computing
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1287/ijoc.2023.0410.cd
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00