The Parliamentary Library of Legislative Yuan website provides a fair and objective channel for the public to track daily activities of the Legislative Yuan and legislators’ inquiries. However the increased information content cause information overloading problem. To mitigate this program, this study proposed an incremental clustering mechanism to renew the information regularly and transform information from text to statics.
This study first initiates a basic categorical structure by two-stage clustering algorithm. Then the incremental clustering method is applied to group related documents corresponding to the same topic into clusters and designates these clusters into existing category or create a new category.
Experimental results show the effectiveness of that the proposed incremental clustering method, which enables the management of hierarchical categorical structure on legislative interpellation. With this results, people can track the legislative activities using the information from the Parliamentary Library of Legislative Yuan to recognize the interpellations in each category.

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