Abstract

This study describes how to extract key terms of the micro-blogs messages, using information obtained by analysing the structure and content of online encyclopaedia Wikipedia. The algorithm used for this target is based on the calculation of "keyphraseness" for each term, i.e., assess the probability that it may be chosen as a key term in the text. During assessment, the developed algorithm has shown satisfactory results in terms of this task, significantly outpacing other existing algorithms. As a demonstration of the possible application of the developed algorithm it has been implemented in a system prototype of contextual advertisement. And some options have been also formulated using the information obtained by analysing Twitter messages, for various support services.

Keywords:

Blogs, messages, extracting algorithms, key term extraction, keyphraseness, micro blogging,

References

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.