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Helpdesk databases are used to store past interactions between customers and companies to improve customer service quality. One common scenario of using helpdesk database is to find whether recommendations exist given a new problem from a customer. However, customers often provide incomplete or even inaccurate information. Manually preparing a list of clarification questions does not work for large databases. This paper investigates the problem of automatic generation of a minimal number of questions to reach an appropriate recommendation.
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