Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
ROC Performance Evaluation of Web-Based Bibliographic Navigator using Extended Association Rules
ICSC '99 Proceedings of the 5th International Computer Science Conference on Internet Applications
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mondou: Information Navigator with Visual Interface
DaWaK 2000 Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery
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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.