Narrowing Categories in Yandex.Market Search Using YaGPT

Student: Nikolay Kossa

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2024

E-commerce is a fast-growing industry, and more accurate search relevance can significantly increase conversions and sales, as well as improve user interaction and satisfaction. Ensuring the accuracy and relevance of the search allows customers to find what they are looking for faster, saving time and increasing the likelihood of a purchase. This work represents a unique approach to improving relevance of Yandex.Market search by narrowing its categories. We are considering a strategy for creating product filtering based on frequent user search queries using a few-shot approach with YaGPT model.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses