Decision tree induction for identifying trends in line graphs

Authors:
Peng Wu;Sandra Carberry;Daniel Chester;Stephanie Elzer
Affiliations:
Dept. of Computer Science, University of Delaware, Newark, DE;Dept. of Computer Science, University of Delaware, Newark, DE;Dept. of Computer Science, University of Delaware, Newark, DE;Dept. of Computer Science, University of Delaware, Newark, DE
Venue:
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Year:
2008

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Abstract

Information graphics (such as bar charts and line graphs) in popular media generally convey a message. This paper presents our approach to a significant problem in extending our message recognition system to line graphs - namely, the segmentation of the graph into a sequence of visually distinguishable trends. We use decision tree induction on attributes derived from statistical tests and features of the graphic. This work is part of a long-term project to summarize multimodal documents and to make them accessible to blind individuals.