DocumentCode :
2787208
Title :
Mining Customer Feedbacks for Actionable Intelligence
Author :
Dey, Lipika ; Haque, Sk Mirajul ; Raj, Nidhi
Author_Institution :
TCS Innovation Labs. Delhi, Delhi, India
Volume :
3
fYear :
2010
fDate :
Aug. 31 2010-Sept. 3 2010
Firstpage :
239
Lastpage :
242
Abstract :
Mining consumer-generated text can provide business intelligence to organizations by extracting important knowledge trapped in the form of opinions, thoughts, and ideas expressed by their employees and customers on various aspects relevant to business. The key challenge here is to extract and organize relevant information from noisy text in order to effectively transform it to actionable intelligence. However, there is no formal framework to guide this analytical task. In this work, we present a system that is suitable for purpose-driven mining of free-text customer feedback to convert the knowledge gained to actionable intelligence.
Keywords :
Internet; competitive intelligence; customer satisfaction; knowledge acquisition; organisational aspects; text analysis; actionable intelligence; business intelligence; consumer generated text Mining; free text customer feedback mining; knowledge extraction; purpose driven mining; Accuracy; Business; Feature extraction; Noise measurement; Ontologies; Text mining; Actionable intelligence; Fuzzy clustering; Noisy text; Ontology; Opinion mining; Text mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-8482-9
Electronic_ISBN :
978-0-7695-4191-4
Type :
conf
DOI :
10.1109/WI-IAT.2010.196
Filename :
5617332
Link To Document :
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