Rule-Based Turkish Text Summarizer (RB-TTS)
The volume of data produced has exponentially increased with the digital revolution and it continues to race to the limits of the capacity of our computers and supercomputers. Automatic text summarization is one of efforts to tame the bestial product of our daily data production, which have gener...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Stefan cel Mare University of Suceava
2018-08-01
|
| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2018.03015 |
| Summary: | The volume of data produced has exponentially increased with the digital revolution and it continues
to race to the limits of the capacity of our computers and supercomputers. Automatic text
summarization is one of efforts to tame the bestial product of our daily data production,
which have generated the 90 percent of the data ever produced by humans, in the last two
years. In order to understand what a text is about, a summary is needed which is short
enough not to compromise the understandability, and comprehensive to include the most
important topics of that text. Numerous automatic text summarization software which aimed
at achieving this goal use semantic relations, thesauri, and word frequency lists. In this
paper, development phases and evaluation results of a software tool called Rule Based
Turkish Text Summarizer (RB-TTS) are presented. The average success rate of the RB-TTS
is analyzed both quantitatively using ROUGE-N metrics and qualitatively. In the qualitative
analysis, five summaries, obtained automatically from texts, are evaluated by 10 Ph.D. students
from Dokuz Eylul University Department of Linguistics. The summaries generated by RB-TTS software
are compared with the summaries, which were written by the authors of the corresponding texts,
and marked as close to them. |
|---|---|
| ISSN: | 1582-7445 1844-7600 |