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Pregled bibliografske jedinice broj: 710547

Developing a text classifier with constrained development and execution time


Budiselić, Ivan; Delač, Goran; Vladimir, Klemo
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, Croatia, 2014. str. 1170-1175 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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, Croatia, 2014, 1170-1175

Skup
37th International Convention on Information and Communication Technology, Electronics and Microelectronics

Mjesto i datum
Opatija, Croatia, 26-30.05.2014.

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


Projekt / tema
036-0362980-1921 - Računalne okoline za sveprisutne raspodijeljene sustave (Siniša Srbljić, )

Ustanove
Fakultet elektrotehnike i računarstva, Zagreb