E-commerce product matching with deep learning
2020
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Danışman: Dr. Öğr. Üyesi Funda Yıldırım
Özet (EN)
As the E-Commerce market grows, more products gets listed everyday. This growth in number of choices generate novel problems that are needed to be solved by businesses like price comparison sites and e-commerce competition analytics platforms. One such problem is matching same products despite the differences in representation. These differences can occur as differently written titles or usage of synonyms of the same product specifications. For matching products despite these different representations, we present two solutions, a metric-learning based solution for search and retrieval of the products and a siamese deep neural network for comparing product representations. Both of these models only needs product titles and are specialized for Turkish language.
Yazar
Cenk Çorapcı
Bu Yayına Nasıl Atıf Yapılır
Cenk Çorapcı (Master Thesis). E-commerce product matching with deep learning, 2020, Yeditepe University.
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