Pregled bibliografske jedinice broj: 710547
Developing a text classifier with constrained development and execution time
Developing a text classifier with constrained development and execution time // Proceedings of the 37th International Convention on Information and Communication Technology, Electronics and Microelectronics
Opatija, 2014. str. 1170-1175 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 710547 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Developing a text classifier with constrained development and execution time
Autori
Budiselić, Ivan ; Delač, Goran ; Vladimir, Klemo
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 37th International Convention on Information and Communication Technology, Electronics and Microelectronics
/ - Opatija, 2014, 1170-1175
Skup
37th International Convention on Information and Communication Technology, Electronics and Microelectronics
Mjesto i datum
Opatija, Hrvatska, 26.05.2014. - 30.05.2014
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
text classification; development time constraints
Sažetak
The aim of this paper is to show that an accurate and efficient text classifier for relatively simple problem domains can be created in only a few hours of development time. The motivating example discussed in the paper is a recent HackerRank competition problem that tasked competitors with creating a classifier for questions from the popular question and answer platform StackExchange. The paper describes the key components of one solution to this problem, and briefly overviews the naive Bayes classifier that is the basis of the solution. The discussion is focused on feature selection and example representation which were the key challenges to be addressed during the development of this classifier. We also analyze the effect of the number of features on accuracy, training and classification time and the size of the resulting classifier and the representation of the training examples which were all important characteristics for the competition. The described classifier achieved slightly over 89% accuracy on the hidden question set, while the winning submission achieved around 92%.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
036-0362980-1921 - Računalne okoline za sveprisutne raspodijeljene sustave (Srbljić, Siniša, MZO ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb