• 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
Georgiy Moiseev
Hierarchical Text Classifier Using Ensemble Learning
Software Engineering
(Bachelor’s programme)
9
2016
The problem of data organization and classification on the Internet is one of the most actual topics in data science nowadays. This area of research is vividly developing due to growing amount of information on the Internet and high demand for its automatic processing. Therefore, a lot has been done in this sphere during the last years, but many problems are still to be solved. A good example of its subtask is the following: hierarchical data classification. Solution to the problem in question can be useful in tackling wide range of issues from creating a knowledge base to marketing research.

The aim of this work is to develop a hierarchical website classification program based on ensemble learning.

This paper provides an overview of existing methods for hierarchical website classification and proposes new algorithms and techniques to improve them. The paper proposes the approach of using weighted markup tags in feature extraction process. As a classifier we use an ensemble of classifiers combining two different hierarchical classification approaches. Performance of proposed algorithms is tested and compared with existing methods through several experiments. The Yandex Catalogue is used as a dataset for learning and testing the system.

Keywords: hierarchical website classification, web mining, ensemble learning, feature extraction

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