Towards Improving the Search Quality on the Trading Platforms
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Дата
2018
ORCID
DOI
doi.org/10.1007/978-3-030-00060-8_2
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
Springer International Publishing AG
Анотація
In this paper, the problem of the search quality on the trading platforms, such AliExpress, eBay and others is explored, the major types of problems that arise in product search by customers are considered. The usage of the classical clusterization algorithms for grouping similar products according to their descriptions is studied. A data set for experimenting consists of different items (smartphones) from e-shop eBay is developed. Each entity in this corpus photos and a product description are given. These texts are used for item comparing in order to perform similar groups or similar items. The results show that the k-means algorithm is good for preliminary grouping but for detailed processing, other methods and approaches are required.
Опис
Ключові слова
trading platform, recommendation system, product search, information technology, product classification
Бібліографічний опис
Towards Improving the Search Quality on the Trading Platforms / O. Cherednichenko [et al.] // Lecture Notes in Business Information Processing (LNBIP). – 2018. – Vol. 333 : proc. 11th SIGSAND/PLAIS: EuroSymposium on Systems Analysis and Design: "Information Systems: Research, Development, Applications, Education", Gdansk, Poland, September 20, 2018 / eds. S. Wrycza, J. Maslankowsky. – Cham : Springer International Publishing, 2018. – P. 21-30.