Discovering Opinions from Customers' Unstructured Textual Reviews Written in Different Natural Languages

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F15%3A43917471" target="_blank" >RIV/62156489:43110/15:43917471 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.4018/978-1-4666-6543-9.ch049" target="_blank" >https://doi.org/10.4018/978-1-4666-6543-9.ch049</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.4018/978-1-4666-6543-9.ch049" target="_blank" >10.4018/978-1-4666-6543-9.ch049</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Discovering Opinions from Customers' Unstructured Textual Reviews Written in Different Natural Languages

Popis výsledku v původním jazyce

Gaining new and keeping existing clients or customers can be well-supported by creating and monitoring feedbacks: &quot;Are the customers satisfied? Can we improve our services?&quot; One of possible feedbacks is allowing the customers to freely write their reviews using a simple textual form. The more reviews that are available, the better knowledge can be acquired and applied to improving the service. However, very large data generated by collecting the reviews has to be processed automatically as humans usually cannot manage it within an acceptable time. The main question is &quot;Can a computer reveal an opinion core hidden in text reviews?&quot; It is a challenging task because the text is written in a natural language. This chapter presents a method based on the automatic extraction of expressions that are significant for specifying a review attitude to a given topic. The significant expressions are composed using significant words revealed in the documents. The significant words are selected by a decision-tree generator based on the entropy minimization. Words included in branches represent kernels of the significant expressions. The full expressions are composed of the significant words and words surrounding them in the original documents. The results are here demonstrated using large real-world multilingual data representing customers&apos; opinions concerning hotel accommodation booked on-line, and Internet shopping. Knowledge discovered in the reviews may subsequently serve for various marketing tasks.

Název v anglickém jazyce

Discovering Opinions from Customers' Unstructured Textual Reviews Written in Different Natural Languages

Popis výsledku anglicky

Gaining new and keeping existing clients or customers can be well-supported by creating and monitoring feedbacks: &quot;Are the customers satisfied? Can we improve our services?&quot; One of possible feedbacks is allowing the customers to freely write their reviews using a simple textual form. The more reviews that are available, the better knowledge can be acquired and applied to improving the service. However, very large data generated by collecting the reviews has to be processed automatically as humans usually cannot manage it within an acceptable time. The main question is &quot;Can a computer reveal an opinion core hidden in text reviews?&quot; It is a challenging task because the text is written in a natural language. This chapter presents a method based on the automatic extraction of expressions that are significant for specifying a review attitude to a given topic. The significant expressions are composed using significant words revealed in the documents. The significant words are selected by a decision-tree generator based on the entropy minimization. Words included in branches represent kernels of the significant expressions. The full expressions are composed of the significant words and words surrounding them in the original documents. The results are here demonstrated using large real-world multilingual data representing customers&apos; opinions concerning hotel accommodation booked on-line, and Internet shopping. Knowledge discovered in the reviews may subsequently serve for various marketing tasks.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

50901 - Other social sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Hospitality, Travel, and Tourism: Concepts, Methodologies, Tools, and Applications

ISBN

978-1-4666-6543-9

Počet stran výsledku

26

Strana od-do

834-859

Počet stran knihy

1623

Název nakladatele

IGI Global

Místo vydání

Hershey

Kód UT WoS kapitoly

000489991200050