This paper analyzes the case duration of product defects in high-tech product customer support. User inquiries about new defects often increase very rapidly within a few weeks. They continue to increase until corresponding solutions are provided or new versions appear. Typical user inquiries are added into FAQ (frequently-asked questions) case bases using conventional case-based reasoning (CBR) tools by expert engineers later on. However, some additions take too much time. Such knowledge may really be necessary within a few weeks after a problem first appears. This paper describes SignFinder, which analyzes textual user inquiries stored in a database of a call tracking system and extracts remarkably increasing cases between two user-specified time periods. If SignFinder is given a problem description, it displays a list of recently increasing keywords in the cases that include the problem description. These keywords can signal new defects. An empirical experiment shows that such increasing keywords can become salient features for retrieving signs of new defects not yet recognized by expert engineers. SignFinder is not a general-purpose case retriever. It only retrieves frequency-increasing similar-looking cases to a user's problem description. SignFinder fills in the time gap between the first appearing time of a new defect and the time when the defect and its solution are added into a FAQ case base using a conventional CBR system.
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