• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
For visually-impairedUser profile (HSE staff only)SearchMenu

Mathematical Modeling for Classification of Appointments in a Corporate Calendar Based on Unstructured Data

Student: Ekaterina Shestakova

Supervisor: Liudmila Zhukova

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

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2021

In the modern management systems, automation of event planning and meeting coordination is beginning to be actively implemented as a time management tool. The author of this work reaches the goal of creating an algorithm for classifying meetings from the corporate calendar of employees of a large company by analyzing unstructured data, as well as other features. In the course of the work, methods of processing text information, such as tokenization, normalization and vectorization, methods of extracting features from text and enriching it with the help of Named Entity Recognition, Latent Semantic Analysis and Latent Dirichlet Allocation were studied and implemented, method of enriching texts with contextual information with the help of Contextual Search Phrases fit for the Russian language was studied and applied, such classification models as the Naive Bayesian Classifier, the Support vector machines and random forest were also studied and applied. As a result, a meeting classification model for the corporate calendar was built. It was successfully implemented in the company's corporate calendar application, where it is used to increase the efficiency of employees' work, as one of the time management tools.

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