Mining Significant Words from Customer Opinions Written in Different Natural Languages

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F11%3A00215851" target="_blank" >RIV/62156489:43110/11:00215851 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-642-23538-2_27" target="_blank" >http://dx.doi.org/10.1007/978-3-642-23538-2_27</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-23538-2_27" target="_blank" >10.1007/978-3-642-23538-2_27</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Mining Significant Words from Customer Opinions Written in Different Natural Languages

Popis výsledku v původním jazyce

Opinions expressed by text documents freely written in various natural languages represent a valuable source of knowledge that is hidden in large datasets. The presented research describes a text mining-method how to discover words that are significant for expressing different opinions (positive and negative). The method applies a simple but unified data pre-processing for all languages, providing the bag-of-words with words represented by their frequencies in the data. Then, the frequencies are used bythe algorithm which generates decision trees. The tree decisive nodes contain the words that are significant for expressing the opinions. Positions of these words in the tree represent their significance degree, where the most significant word is in thenode. As a result, a list of relevant words can be used for creating a dictionary containing only relevant information. The described method was tested using very large sets of customers' reviews concerning the on-line hotel room booking

Název v anglickém jazyce

Mining Significant Words from Customer Opinions Written in Different Natural Languages

Popis výsledku anglicky

Opinions expressed by text documents freely written in various natural languages represent a valuable source of knowledge that is hidden in large datasets. The presented research describes a text mining-method how to discover words that are significant for expressing different opinions (positive and negative). The method applies a simple but unified data pre-processing for all languages, providing the bag-of-words with words represented by their frequencies in the data. Then, the frequencies are used bythe algorithm which generates decision trees. The tree decisive nodes contain the words that are significant for expressing the opinions. Positions of these words in the tree represent their significance degree, where the most significant word is in thenode. As a result, a list of relevant words can be used for creating a dictionary containing only relevant information. The described method was tested using very large sets of customers' reviews concerning the on-line hotel room booking

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

Text, Speech and Dialogue

ISBN

978-3-642-23537-5

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

211-218

Název nakladatele

Springer

Místo vydání

Heidelberg Dordrecht London New York

Místo konání akce

Pilsen

Datum konání akce

1. 9. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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