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Title:
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COMBINIG TEXT MINING AND DATA MINING FOR GAINING VALUABLE KNOWLEDGE FROM ONLINE REVIEWS |
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Author(s):
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Carolin Kaiser |
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ISBN:
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ISSN: 1645-7641 |
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Editors:
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Pedro Isaías |
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Year:
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2009 |
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Edition:
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V VII, 1 |
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Keywords:
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Opinion Mining, Text Mining, Data Mining, Web 2.0, Reviews |
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Type:
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Journal Paper |
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First Page:
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63 |
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Last Page:
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78 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In the course of a social orientation of the Internet there is an increasing number of customers who share
their product experiences. The growing Web 2.0 encompasses a valuable source of knowledge for
companies. However, the manual analysis of customer experience on the Web 2.0 is very time
consuming. This paper proposes a system which allows an automatic analysis of customer experience by
combining methods from text mining and data mining. This system enables the extraction, aggregation
and analyzation of product features and their evaluations. Thus, valuable information for product
development and improvement can be gained. |
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