document: Mining open answers in questionnaire data Surveys are important tools for marketing and for managing customer relationships ; the answers to open-ended questions , in particular , often contain valuable information and provide an important basis for business decisions . The summaries that human analysts make of these open answers , however , tend to rely too much on intuition and so are n't satisfactorily reliable . Moreover , because the Web makes it so easy to take surveys and solicit comments , companies are finding themselves inundated with data from questionnaires and other sources . Handling it all manually would be not only cumbersome but also costly . Thus , devising a computer system that can automatically mine useful information from open answers has become an important issue . We have developed a survey analysis system that works on these principles . The system mines open answers through two statistical learning techniques : rule learning -LRB- which we call rule analysis -RRB- and correspondence analysis
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