Deep Learning Models for Product Mapping
| Název práce v češtině: | Modely hlubokého učení pro úlohu mapování produktů |
|---|---|
| Název v anglickém jazyce: | Deep Learning Models for Product Mapping |
| Klíčová slova: | hluboké učení|mapování produktů|zpracování obrazu|zpracování |
| Klíčová slova anglicky: | deep learning|product mapping|image processing|text processing |
| Akademický rok vypsání: | 2023/2024 |
| Typ práce: | bakalářská práce |
| Jazyk práce: | angličtina |
| Ústav: | Katedra teoretické informatiky a matematické logiky (32-KTIML) |
| Vedoucí / školitel: | RNDr. Kateřina Macková |
| Řešitel: | Mkrtich Hovsepyan - zadáno a potvrzeno stud. odd. |
| Datum přihlášení: | 12.02.2024 |
| Datum zadání: | 27.02.2024 |
| Datum potvrzení stud. oddělením: | 27.02.2024 |
| Zásady pro vypracování |
| Product mapping is the process of identifying matching products from different source e-shops. Each product can be described by several image and textual data with different structures and there is no general identifier of products that would enable their direct matching. Therefore, it becomes a challenging task requiring deep learning techniques that allow thorough text and image processing to correctly identify matching pairs. In the rapidly evolving landscape of e-commerce, such ability has become an invaluable tool for enhancing user experience and streamlining product management.
The student will study relevant literature on product mapping employing advanced deep-learning techniques for image and text processing. He will compare several methods and select the best technique for solving the problem in general. |
| Seznam odborné literatury |
| Peeters, Ralph, and Christian Bizer. "Entity Matching using Large Language Models." arXiv preprint arXiv:2310.11244 (2023).
Rivas-Sánchez, Mario, et al. "Using deep learning for image similarity in product matching." Advances in Computational Intelligence: 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Cadiz, Spain, June 14-16, 2017, Proceedings, Part I 14. Springer International Publishing, 2017. Peeters, Ralph, and Christian Bizer. "Supervised contrastive learning for product matching." Companion Proceedings of the Web Conference 2022. 2022. de Santana, Matheus Alcantara, et al. "Using Machine Learning and NLP for the Product Matching Problem." Intelligent Sustainable Systems: Selected Papers of WorldS4 2022, Volume 2. Singapore: Springer Nature Singapore, 2023. 439-448. |