Pregled bibliografske jedinice broj: 926296
Keyword Extraction from Parallel Abstracts of Scientific Publications
Keyword Extraction from Parallel Abstracts of Scientific Publications // 3rd COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources (IKC 2017) / Szymański, Julian ; Velegrakis, Yannis (ur.).
Cham: Springer, 2018. str. 44-55 doi:10.1007/978-3-319-74497-1_5 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 926296 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Keyword Extraction from Parallel Abstracts of
Scientific Publications
Autori
Beliga, Slobodan ; Kitanović, Olivera ; Stanković, Ranka ; Martinčić-Ipšić, Sanda
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
ISBN
978-3-319-74496-4
Skup
3rd COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources (IKC 2017)
Mjesto i datum
Gdańsk, Poljska, 11.09.2017. - 12.09.2017
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Graph-based keyword extraction ; Bilingual keyword extraction ; SBKE method ; Parallel abstracts
Sažetak
In this paper, we study the keyword extraction from parallel abstracts of scientific publication in the Serbian and English languages. The keywords are extracted by a selectivity-based keyword extraction method. The method is based on the structural and statistical properties of text represented as a complex network. The constructed parallel corpus of scientific abstracts with annotated keywords allows a better comparison of the performance of the method across languages since we have the controlled experimental environment and data. The achieved keyword extraction results measured with an F1 score are 49.57% for English and 46.73% for the Serbian language, if we disregard keywords that are not present in the abstracts. In case that we evaluate against the whole keyword set, the F1 scores are 40.08% and 45.71% respectively. This work shows that SBKE can be easily ported to new a language, domain and type of text in the sense of its structure. Still, there are drawbacks – the method can extract only the words that appear in the text.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Ustanove:
Fakultet informatike i digitalnih tehnologija, Rijeka
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Conference Proceedings Citation Index - Science (CPCI-S)
- Scopus