Pregled bibliografske jedinice broj: 699797
Complex Networks Measures for Differentiation between Normal and Shuffled Croatian Texts
Complex Networks Measures for Differentiation between Normal and Shuffled Croatian Texts // Proceedings MIPRO junior - Student Papers / Biljanović, Petar (ur.).
Opatija: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2014. str. 1819-1823 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Complex Networks Measures for Differentiation between Normal and Shuffled Croatian Texts
Autori
Margan, Domagoj ; Meštrović, Ana ; Martinčić-Ipšić, Sanda
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings MIPRO junior - Student Papers
/ Biljanović, Petar - Opatija : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2014, 1819-1823
ISBN
978-953-233-078-6
Skup
IEEE 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014)
Mjesto i datum
Opatija, Hrvatska, 26.05.2014. - 30.05.2014
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
complex networks; linguistic co-occurrence networks; shuffling
Sažetak
This paper studies the properties of the Croatian texts via complex networks. We present network properties of normal and shuffled Croatian texts for different shuffling principles: on the sentence level and on the text level. In both experiments we preserved the vocabulary size, word and sentence frequency distributions. Additionally, in the first shuffling approach we preserved the sentence structure of the text and the number of words per sentence. Obtained results showed that degree rank distributions exhibit no substantial deviation in shuffled networks, and strength rank distributions are preserved due to the same word frequencies. Therefore, standard approach to study the structure of linguistic co-occurrence networks showed no clear difference among the topologies of normal and shuffled texts. Finally, we showed that the in- and out- selectivity values from shuffled texts are constantly below selectivity values calculated from normal texts. Our results corroborate that the node selectivity measure can capture structural differences between original and shuffled Croatian texts.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Projekti:
UniRi - 13.13.2.2.07
Ustanove:
Fakultet informatike i digitalnih tehnologija, Rijeka