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Comparative Analysis of Clustering Methods for Structured and Unstructured Data Based on Web Service Client Profiles

Student: Darya Shangicheva

Supervisor: Liudmila Zhukova

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2021

The main goal of this project is to compare methods for clustering user profiles of web services described using unstructured and structured data. The result of the study is the optimal clustering method for user data. Econometrics methods and machine learning methods are also compared in terms of classification quality and accuracy. The structure consists of 2 main parts: the first is a description and comparison of the tasks of clustering methods, the second is a comparison of clustering methods for structured and unstructured data, a description of existing clustering quality methods and the implementation of clustering algorithms on the data of web service users.

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