Napredna pretraga

Pregled bibliografske jedinice broj: 440555

Comparative Analysis of Automatic Term and Collocation Extraction


Seljan, Sanja; Dalbelo Bašić, Bojana; Šnajder, Jan; Delač, Davor; Šamec-Gjurin, Matija; Crnec, Dina
Comparative Analysis of Automatic Term and Collocation Extraction // 2nd international conference The future of information sciences (INFuture 2009) : Digital resources and knowledge sharing / Stančić, H. ; Seljan, S. ; Bawden, D. ; Lasić-Lazić, J. ; Slavić, A. (ur.).
Zagreb: Department of Information Sciences, Faculty of Humanities and Social Sciences, University of Zagreb, 2009. str. 219-228 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Comparative Analysis of Automatic Term and Collocation Extraction

Autori
Seljan, Sanja ; Dalbelo Bašić, Bojana ; Šnajder, Jan ; Delač, Davor ; Šamec-Gjurin, Matija ; Crnec, Dina

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2nd international conference The future of information sciences (INFuture 2009) : Digital resources and knowledge sharing / Stančić, H. ; Seljan, S. ; Bawden, D. ; Lasić-Lazić, J. ; Slavić, A. - Zagreb : Department of Information Sciences, Faculty of Humanities and Social Sciences, University of Zagreb, 2009, 219-228

ISBN
978-953-175-355-5

Skup
International Conference The Future of Information Sciences (2 ; 2009)

Mjesto i datum
Zagreb, Hrvatska, 04.-06.11.2009

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Automatic extraction; term and collocation base; English language; evaluation metrics

Sažetak
Monolingual and multilingual terminology and collocation bases, covering a specific domain, used independently or integrated with other resources, have become a valuable electronic resource. Building of such resources could be assisted by automatic term extraction tools, combining statistical and linguistic approaches. In this paper, the research on term extraction from monolingual corpus is presented. The corpus consists of publicly accessible English legislative documents. In the paper, results of two hybrid approaches are compared: extraction using the TermeX tool and an automatic statistical extraction procedure followed by linguistic filtering through the open source linguistic engineering tool. The results have been elaborated through statistical measures of precision, recall, and F-measure.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti, Filologija



POVEZANOST RADA


Projekt / tema
036-1300646-1986 - Otkrivanje znanja u tekstnim podacima (Bojana Dalbelo-Bašić, )
130-1300646-0909 - Informacijska tehnologija u prevođenju hrvatskoga i e-učenju jezika (Sanja Seljan, )

Ustanove
Fakultet elektrotehnike i računarstva, Zagreb,
Filozofski fakultet, Zagreb