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Authors: Oliver Strauß 1 ; Ahmad Almheidat 2 and Holger Kett 1

Affiliations: 1 Fraunhofer-Institute for Industrial Engineering IAO, Nobelstraße 12, 73760 Stuttgart and Germany ; 2 Institute of Human Factors and Technology Management, University of Stuttgart, Nobelstraße 12, 73760 Stuttgart and Germany

Keyword(s): Product Resolution, Duplicate Detection, Machine Learning, Classification Web and Social Media Analytics.

Abstract: In order to analyze product data obtained from different web shops a process is needed to determine which product descriptions refer to the same product (product resolution). Based on string similarity metrics and existing product resolution approaches a new approach is presented with the following components: a) extraction of information from the unstructured product title extracted from the e-shops, b) inclusion of additional information in the matching process, c) a method to compute a product similarity metric from the available data, d) optimization and adaption of model parameters to the characteristics of the underlying data via a genetic algorithm and e) a framework to automatically evaluate the matching method on the basis of realistic test data. The approach achieved a precision of 0.946 and a recall of 0.673.

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Paper citation in several formats:
Strauß, O.; Almheidat, A. and Kett, H. (2019). Applying Heuristic and Machine Learning Strategies to Product Resolution. In Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-386-5; ISSN 2184-3252, SciTePress, pages 242-249. DOI: 10.5220/0008069402420249

@conference{webist19,
author={Oliver Strauß. and Ahmad Almheidat. and Holger Kett.},
title={Applying Heuristic and Machine Learning Strategies to Product Resolution},
booktitle={Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST},
year={2019},
pages={242-249},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008069402420249},
isbn={978-989-758-386-5},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST
TI - Applying Heuristic and Machine Learning Strategies to Product Resolution
SN - 978-989-758-386-5
IS - 2184-3252
AU - Strauß, O.
AU - Almheidat, A.
AU - Kett, H.
PY - 2019
SP - 242
EP - 249
DO - 10.5220/0008069402420249
PB - SciTePress