• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Kirill Demochkin
Development of mobile recommender system based on images analysis using with neural networks
Software Engineering
(Bachelor’s programme)
10
2019
In this study we focus on the problem of user interests’ classification in mobile product recommender systems. We propose a two-stage procedure. At first, the image features are learned by fine-tuning a convolutional neural net-work, e.g., MobileNet. In the second stage, we use learnable pooling techniques such as a neural aggregation network and context gating in order to compute a weighted average of image features. As a result, we can capture the relationships between the images of products purchased by the same user. We provide an experimental study with the Amazon Fashion dataset that shows that our approach achieves an F1-measure of 0.58 for 15 recommendations, which is much higher when compared to 0.29 F1-measure classification of traditional averaging of the feature vector. Moreover, a mobile recommender system application was developed that utilizes the proposed approach as its core algorithm.

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