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Lucie Skorkovská and Zbyněk Zajíc and Luděk Müller : Comparison of Score Normalization Methods Applied to Multi-label Classification . IEEE International Symposium on Signal Processing and Information Technology, Institute of Electrical and Electronics Engineers ( IEEE ), Noida, India, 2014.

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Abstrakt

Our paper deals with the multi-label text classification of the newspaper articles, where the classifier must decide if a document does or does not belong to each topic from the predefined topic set. A generative classifier is used to tackle this task and the problem with finding a threshold for the positive classification is mainly addressed. This threshold can vary for each document depending on the content of the document (words used, length of the document, etc.). An extensive comparison of the score normalization methods, primary proposed in the speaker identification/verification task, for robustly finding the threshold defining the boundary between the "correct'' and the "incorrect'' topics of a document is presented. Score normalization methods (based on World Model and Unconstrained Cohort Normalization) applied to the topic identification task has shown an improvement of results in our former experiments, therefore in this paper an in-depth experiments with more score normalization techniques applied to the multi-label classification were performed. Thorough analysis of the effects of the various parameters setting is presented.

Detail publikace

Název: Comparison of Score Normalization Methods Applied to Multi-label Classification
Autor: Lucie Skorkovská ; Zbyněk Zajíc ; Luděk Müller
Název - česky: Porovnání metod pro normalizaci skóre aplikovaných na úlohu multi-label klasifikace
Jazyk publikace: anglicky
Datum vydání: 15.12.2014
Rok vydání: 2014
Typ publikace: Stať ve sborníku
Název časopisu / knihy: IEEE International Symposium on Signal Processing and Information Technology
Nakladatel: Institute of Electrical and Electronics Engineers ( IEEE )
Místo vydání: Noida, India
Datum: 15.12.2014 - 17.12.2014
/ 2015-09-01 12:11:43 /

Klíčová slova

multi-label text classification, topic identification, Naive Bayes classification, score normalization

BibTeX

@INPROCEEDINGS{LucieSkorkovska_2014_ComparisonofScore,
 author = {Lucie Skorkovsk\'{a} and Zbyn\v{e}k Zaj\'{i}c and Lud\v{e}k M\"{u}ller},
 title = {Comparison of Score Normalization Methods Applied to Multi-label Classification},
 year = {2014},
 publisher = {Institute of Electrical and Electronics Engineers ( IEEE )},
 journal = {IEEE International Symposium on Signal Processing and Information Technology},
 address = {Noida, India},
 url = {http://www.kky.zcu.cz/en/publications/LucieSkorkovska_2014_ComparisonofScore},
}