TY  - CHAP
A1  - Schmidts, Oliver
A1  - Kraft, Bodo
A1  - Winkens, Marvin
A1  - Zündorf, Albert
T1  - Catalog integration of low-quality product data by attribute label ranking
T2  - Proceedings of the 9th International Conference on Data Science, Technology and Applications - Volume 1: DATA
Y1  - 2020
SN  - 978-989-758-440-4
U6  - http://dx.doi.org/10.5220/0009831000900101
SP  - 90
EP  - 101
ER  - 
TY  - CHAP
A1  - Schmidts, Oliver
A1  - Kraft, Bodo
A1  - Winkens, Marvin
A1  - Zündorf, Albert
T1  - Catalog integration of heterogeneous and volatile product data
T2  - DATA 2020: Data Management Technologies and Applications
N2  - The integration of frequently changing, volatile product data from different manufacturers into a single catalog is a significant challenge for small and medium-sized e-commerce companies. They rely on timely integrating product data to present them aggregated in an online shop without knowing format specifications, concept understanding of manufacturers, and data quality. Furthermore, format, concepts, and data quality may change at any time. Consequently, integrating product catalogs into a single standardized catalog is often a laborious manual task. Current strategies to streamline or automate catalog integration use techniques based on machine learning, word vectorization, or semantic similarity. However, most approaches struggle with low-quality or real-world data. We propose Attribute Label Ranking (ALR) as a recommendation engine to simplify the integration process of previously unknown, proprietary tabular format into a standardized catalog for practitioners. We evaluate ALR by focusing on the impact of different neural network architectures, language features, and semantic similarity. Additionally, we consider metrics for industrial application and present the impact of ALR in production and its limitations.
Y1  - 2021
SN  - 978-3-030-83013-7
U6  - http://dx.doi.org/10.1007/978-3-030-83014-4_7
N1  - International Conference on Data Management Technologies and Applications, DATA 2020, 7-9 July
SP  - 134
EP  - 153
PB  - Springer
CY  - Cham
ER  -