Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Pavel Barsukov
Development of HSE News Aggregator for Telegram Messenger
Information Science and Computation Technology
(Bachelor’s programme)
9
2017
The object of development in this project is a news chat bot. The aim of this project was to develop a service that aggregates information from different sources: VK social networks’ public pages related to the National Research University Higher School of Economics and from the official University website. This chat-bot analyzes and categorizes incoming news articles. Developed chat bot provides users with personalized mailings both in time of news publication and once in every evening with selection of the most popular news in a day.
This chat bot developed for Telegram messenger. Telegram messenger has more than 100 million users all over the world, which means that this solution is easily accessible for the end user and does not require additional software to run developed service. Telegram messenger is available for all modern mobile and desktop platforms: iOS, Android, Windows Phone, masOS, Windows, Linux. Besides this Telegram messenger can be accessed via web-browsers.
Chat-bot was developed using Python 3 programming language; VK social network requests are made using official VK API, RSS request are made using third-party extension. The report has 35 pages, 3 tables, 16 illustrations, 34 reference sources.
This chat bot developed for Telegram messenger. Telegram messenger has more than 100 million users all over the world, which means that this solution is easily accessible for the end user and does not require additional software to run developed service. Telegram messenger is available for all modern mobile and desktop platforms: iOS, Android, Windows Phone, masOS, Windows, Linux. Besides this Telegram messenger can be accessed via web-browsers.
Chat-bot was developed using Python 3 programming language; VK social network requests are made using official VK API, RSS request are made using third-party extension. The report has 35 pages, 3 tables, 16 illustrations, 34 reference sources.
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