Title :
Analysis of daily business reports based on sequential text mining method
Author :
Sakurai, Shigeaki ; Ueno, Ken
Author_Institution :
Toshiba Corp., Kawasaki, Japan
Abstract :
This paper proposes a new method that discovers characteristic sequential patterns in textual data. The data are composed of three kinds of information: time information, attributes, and text. The method gathers items of the data with the same attribute values, arranges the gathered items in order of the time, and generates sequences. The method also extracts events from each text by using a text mining method. Finally, the method discovers characteristic sequential patterns, composed of sets of events, from sequences by a sequential mining method. In this paper, we apply the method to business reports collected by our sales force automation system and try to discover characteristic sequential patterns. We verify whether the patterns are valid by investigating texts relating to the patterns.
Keywords :
business data processing; data mining; text analysis; daily business reports; sequential patterns; sequential text mining; Automation; Data analysis; Data mining; Data visualization; Information analysis; Marketing and sales; Natural languages; Text mining;
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Print_ISBN :
0-7803-8566-7
DOI :
10.1109/ICSMC.2004.1400846