AAAI Publications, Twenty-Second International FLAIRS Conference

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Extracting Meaning from Cell Phone Improvement Ideas
Jenine Turner, Raimondas Lencevicius, Mark Adler

Last modified: 2009-03-17


Companies have recently begun gathering product improvement ideas via web tools. Resulting data collections are too large to be effectively dealt with by human users. But natural language processing and machine learning techniques are well suited for this type of problem. We explore several ways to organize such data in the cell phone domain: supervised classification, unsupervised clustering, and time-based analysis.

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