Кластеризація Текстових Даних для Підвищення Ефективності Інформаційного Пошуку в Мережі

Denys Blokh; Volodymyr Kobziev

Textual Data Clustering to Increase the Effectiveness of Information Search on the Web

Authors

Denys Blokh dept. of Software Engineering, Kharkiv National University of Radio Electronics
Volodymyr Kobziev dept. of Software Engineering, Kharkiv National University of Radio Electronics

Keywords:

internet marketing, content optimization, clustering, Data Mining, k-means algorithm

Abstract

The application of Data Mining methods for the analysis of textual information from databases of Internet resources in order to increase the effectiveness of marketing campaigns is considered. Special attention is paid to the clustering of textual data and the creation of a semantic core, which allows to improve strategies for engaging the audience in the online environment and optimize marketing efforts.