| En/De/Fr/It- (first 9 out of 138 sentences)
[pdf] |
Srpski - (prvih 9 od 138 rečenica)
[pdf]
|
| n1 | ABSTRACT: | n1 | SAŽETAK: |
| n2 | This paper is a result of a task presented to attendants of Keyword Search in Big Linked Data summer school, that was organized by Vienna University of Technology, under the Keystone COST action in the summer of 2017. | n2 | Rad je nastao kao odgovor na zadatak klasifikacije medicinskih dokumenata, postavljen tokom letnje škole Keyword Search in Big Linked Data, održane u okviru COST akcije Keystone 2017. godine na Tehnološkom univerzitetu u Beču. |
| n3 | It presents a specific approach to the classification via creation of minimal document surrogates based on the US National medical library’s MeSH ontology, which is derived from the Medical Subject Headings thesaurus. | n3 | U njemu se prikazuju rezultati specifičnog pristupa klasifikaciji zasnovanog na kreiranju minimalnih surogata teksta. Kao osnova klasifikacije uzeta je MeSH ontologija, zasnovana na tezaurusu Medical Subject Headings. |
| n4 | In a series of previously classified medically related texts, which are the bases for the task, all of the significant terms are located and replaced with taxonomical references from the MeSH ontology. | n4 | U tekstovima, prethodno klasifikovanim pomoću taksonomije ove ontologije, najpre se pronalaze pojmovi od važnosti, a potom se zamenjuju taksonomskim referencama. |
| n5 | Extracted references are used for the classification within the ontology using a rather simple algorithm and the results are evaluated in compresence to previous manual classification of the same documents. | n5 | Tako ekstrahovane reference koriste za klasifikaciju unutar MeSH taksonomije pomoću prostog algoritma, a rezultati se evaluiraju u odnosu na ručno klasifikovane dokumente. |
| n6 | KEYWORDS: document classification, MeSH, ontology, information extraction. | n6 | KLjUČNE REČI: klasifikacija dokumenata, MeSH, ontologije, ekstrakcija informacija |
| n7 | This paper describes an attempted solution of an assign given during a one-day hackathon by the lecturers of the summer school Keystone 3rd training school: | n7 | Ovaj rad opisuje rešenje problema koji je zadao predavač na jednodnevnom hakatonu letnje škole Keystone 3rd training school: |
| n8 | Keyword Search in Big Linked Data,1 organized in Vienna from 21– 25 August, 2017 under the COST action IC1302 Keyword search in Big Linked Data. | n8 | Keyword Search in Big Linked Data, održanoj u Beču 21–25. avgusta 2017. u okviru COST akcije IC1302 - Keyword Search in Big Linked Data. |
| n9 | The task was to classify 10.000 given documents originating from the digital collection of the US National medical library (Figure 1), whereas the classification to be used was predefined in the MeSH (Medical Subject Headings) ontology (Dragoni, 2017). | n9 | Problem se sastoji u klasifikovanju 10.000 dokumenata iz digitalne kolekcije Nacionalne medicinske biblioteke Sjedinjenih Američkih Država (slika 1), koje je obezbedio predavač, dok je na učesnicima bilo da te dokumente klasifikuju u klase predefinisane u MeSH (Medical Subject Headings) ontologiji (Dragoni, 2017). |