Clients' freely written assessment as the source of automatically mined opinions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F14%3A00232199" target="_blank" >RIV/62156489:43110/14:00232199 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/S2212-5671(14)00325-6" target="_blank" >http://dx.doi.org/10.1016/S2212-5671(14)00325-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/S2212-5671(14)00325-6" target="_blank" >10.1016/S2212-5671(14)00325-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Clients' freely written assessment as the source of automatically mined opinions

Popis výsledku v původním jazyce

Measuring the quality of products or services, a challenging task is to reveal clients' satisfaction or sentiment. As people have many opportunities to express their opinions using various on-line channels (e.g., discussions, microblogs, social networks), the question is whether such data might be used for this purpose. Information hidden in the data includes the reasons why people perceive products or services as good or bad, what are the reasons of clients' satisfaction or dissatisfaction, or what affects their sentiment. However, having the needed large amounts of data, it is hardly possible to process it manually. This paper presents a method that aims at automatic discovery of sources of human feelings hidden in textual messages that clients produce. For a demonstration, messages having a form of freely written reviews containing subjective evaluation of medical services were used. During analysis of the data, clusters representing groups of the whole reviews (or individual senten

Název v anglickém jazyce

Clients' freely written assessment as the source of automatically mined opinions

Popis výsledku anglicky

Measuring the quality of products or services, a challenging task is to reveal clients' satisfaction or sentiment. As people have many opportunities to express their opinions using various on-line channels (e.g., discussions, microblogs, social networks), the question is whether such data might be used for this purpose. Information hidden in the data includes the reasons why people perceive products or services as good or bad, what are the reasons of clients' satisfaction or dissatisfaction, or what affects their sentiment. However, having the needed large amounts of data, it is hardly possible to process it manually. This paper presents a method that aims at automatic discovery of sources of human feelings hidden in textual messages that clients produce. For a demonstration, messages having a form of freely written reviews containing subjective evaluation of medical services were used. During analysis of the data, clusters representing groups of the whole reviews (or individual senten

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

17th International Conference Enterprise And Competitive Environment 2014

ISBN

—

ISSN

2212-5671

e-ISSN

—

Počet stran výsledku

8

Strana od-do

103-110

Název nakladatele

Elsevier Science Bv

Místo vydání

Amsterdam, Netherlands

Místo konání akce

Brno, CZECH REPUBLIC

Datum konání akce

6. 3. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

345439100012