Text Mining-based Formation of Dictionaries Expressing Opinions in Natural Languages

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F11%3A00173333" target="_blank" >RIV/62156489:43110/11:00173333 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Text Mining-based Formation of Dictionaries Expressing Opinions in Natural Languages

Popis výsledku v původním jazyce

Automatic formation of dictionaries containing words significant for expressing different customers' opinions written in natural languages is demonstrated. The research used very large real-world data concerning the hotel accommodation booking via the Internet. The hotel companies could be interested in characteristic words expressing positive and negative opinions because it could help improve the offered service. The suggested method uses unstructured plain text reviews of many customers from different countries. The data is transformed into vectors using the bag-of-words procedure with the word representation by their frequencies in the reviews. Significant words are selected as relevant attributes for the classification to given categories using trained decision trees. Each tree branch leading to a leaf represents a subset of significant words for a category. The individual word importance is weighted by the word frequency in all the branches combined with their occurrence in branc

Název v anglickém jazyce

Text Mining-based Formation of Dictionaries Expressing Opinions in Natural Languages

Popis výsledku anglicky

Automatic formation of dictionaries containing words significant for expressing different customers' opinions written in natural languages is demonstrated. The research used very large real-world data concerning the hotel accommodation booking via the Internet. The hotel companies could be interested in characteristic words expressing positive and negative opinions because it could help improve the offered service. The suggested method uses unstructured plain text reviews of many customers from different countries. The data is transformed into vectors using the bag-of-words procedure with the word representation by their frequencies in the reviews. Significant words are selected as relevant attributes for the classification to given categories using trained decision trees. Each tree branch leading to a leaf represents a subset of significant words for a category. The individual word importance is weighted by the word frequency in all the branches combined with their occurrence in branc

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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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 periodika

Mendel

ISSN

1803-3814

e-ISSN

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Svazek periodika

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Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

374-381

Kód UT WoS článku

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EID výsledku v databázi Scopus

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