Abstract
This paper proposes a method that analyzes textual data with time information. The method extracts events from the textual data by using a key concept dictionary which is a kind of thesaurus. The method also generates sequential event data from extracted events based on the time information and attributes of the textual data. Lastly, the method extracts sequential event patterns which are consistent with constraint sub-patterns designated by an analyst. The extracted patterns are used to support analysts' decision making, because the patterns can predict future events or propose events leading to a target. The analyst can use the patterns to his/her decision making. This paper verifies the effect of the method by applying the method to daily business reports collected by a Sales Force Automation system.
