Comparison of Score Normalization Methods Applied to Multi-label Classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F14%3A43923148" target="_blank" >RIV/49777513:23520/14:43923148 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7300628" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7300628</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISSPIT.2014.7300628" target="_blank" >10.1109/ISSPIT.2014.7300628</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of Score Normalization Methods Applied to Multi-label Classification

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Comparison of Score Normalization Methods Applied to Multi-label Classification

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/DF12P01OVV022" target="_blank" >DF12P01OVV022: Zpřístupnění rozsáhlého video archivu kulturního dědictví pomocí metod automatického rozpoznávání mluvené řeči a strojového překladu. (AMALACH)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Signal Processing and Information Technology (ISSPIT), 2014 IEEE International Symposium on

ISBN

978-1-4799-1811-9

ISSN

—

e-ISSN

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Počet stran výsledku

5

Strana od-do

433-437

Název nakladatele

Institute of Electrical and Electronics Engineers ( IEEE )

Místo vydání

Noida

Místo konání akce

Noida, India

Datum konání akce

15. 12. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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