Faculty of Computer Science and Engineering

Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5

The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest faculties in that field in the region. The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.

Browse

Settings

Author: search.filters.author.Dobreva, JovanaSubject: search.filters.subject.Named entity recognition

Search Results

Now showing 1 - 1 of 1
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Improving NER Performance by Applying Text Summarization on Pharmaceutical Articles
    (Springer International Publishing, 2020-10-30)
    Dobreva, Jovana
    ;
    Jofche, Nasi
    ;
    ;
    Analyzing long text articles in the pharmaceutical domain, for the purpose of knowledge extraction and recognizing entities of interest, is a tedious task. In our previous research efforts, we were able to develop a platform which successfully extracts entities and facts from pharmaceutical texts and populates a knowledge graph with the extracted knowledge. However, one drawback of our approach was the processing time; the analysis of a single text source was not interactive enough, and the batch processing of entire article datasets took too long. In this paper, we propose a modified pipeline where the texts are summarized before the analysis begins. With this, the source articles is reduced significantly, to a compact version which contains only the most commonly encountered entities. We show that by reducing the text size, we get knowledge extraction results comparable to the full text analysis approach and, at the same time, we significantly reduce the processing time, which is essential for getting both real-time results on single text sources, and faster results when analyzing entire batches of collected articles from the domain.