Consumer behavior analysis by graph mining technique

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3214, Issue , 2004, Pages 800-806

  Yada, Katsutoshi ^a   Motoda, Hiroshi ^b   Washio, Takashi ^a   Miyawaki, Asuka ^b  

^a KANSAI UNIVERSITY   (Japan)

^b OSAKA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIORAL RESEARCH; DATA MINING; DIRECTED GRAPHS; KNOWLEDGE BASED SYSTEMS; OILS AND FATS; SALES;

COOKING OIL; GRAPH MINING; PURCHASE SEQUENCES; TEMPORAL INFORMATION; TRANSACTION DATA;

CONSUMER BEHAVIOR;

EID: 35048882066     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30133-2_105     Document Type: Article

References (4)

1. Hamuro, Y., Kawata, H., Katoh, N., Yada, K.: A Machine Learning Algorithm for Analyzing String Patterns Helps to Discover Simple and Interpretable Business Rules from Purchase History. Progress in Discovery Science. LNAI Vol.2281. Springer-verlag, Berlin Heidelberg New York (2002) 565-575.
2. Hamuro, Y., H., Katoh, N., Ip, E. H., Cheung, S. L., Yada, K.: Combining Information Fusion with String Pattern Analysis: A New Method for Predicting Future Purchase Behavior. V. Torra(ed.): Information Fusion in Data Mining. Studies in Fuzziness and Soft Computting. Vol.123, Springer-verlag, Berlin Heidelberg New York (2003) 161-187.
3. th European Conference on Principles and Practice of Knowledge Discovery in Databases. (2000) 13-23.
4. Inokuchi, A., Washio, T., Nishimura, Y., Motoda, H.: General Framework for Mining Frequent Structures in Graphs. Proc. of the International Workshop on Active Mining. (2002) 23-30.