Name
Title | ||
|---|---|---|
Extended Association Algorithm Based on ROC Analysis for Visual Information Navigator |
Abstract | ||
|---|---|---|
It is very important to derive association rules at high speed from huge volume of databases. However, the typical fast mining algorithms in text databases tend to derive meaningless rules such as stop-words, then many researchers try to remove these noisy rules by using various filters. In our researches, we improve the association algorithm and develop information navigation systems for text data using visual interface, and we also apply a dictionary to remove noisy keywords from derived association rules. In order to remove noisy keywords automatically, we propose an algorithm basedon the true positive rate and the false positive rate in the ROC analysis. Moreover, in order to remove stopwords automatically from raw association rules, we introduce several threshold values of the ROC analysis into our proposedmining algorithm. We evaluate the performance of our proposedmining algorithms in a bibliographic database. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-45884-0_49 | Progress in Discovery Science |
Keywords | Field | DocType |
visual information navigator,raw association rule,noisy keyword,noisy rule,association algorithm,algorithm basedon,roc analysis,typical fast mining algorithm,extended association algorithm,false positive rate,association rule,proposedmining algorithm | Information system,Data mining,False positive rate,Visual interface,Data processing,Bibliographic database,Computer science,Algorithm,Association rule learning,Information extraction,True positive rate | Conference |
ISBN | Citations | PageRank |
3-540-43338-4 | 0 | 0.34 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroyuki Kawano | 1 | 52 | 9.36 |
| Minoru Kawahara | 2 | 17 | 7.06 |