A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps

Kawtrakul, Asanee; Yingsaeree, Chaiyakorn; Andres, Frederic

This paper presents a computational framework for information extraction and aggregation which aims to integrate and organize the data/information resources that spread throughout the Internet in the manner that makes them useful for tracking events such as natural disaster, and disease dispersion. We introduce a simple statistical information extraction technique for summarizing the document into a predefined structure. We apply the topic maps approach as a semantic layer in aggregating and organizing the extracted information for smart access. In addition, this paper also carries out a case study on disease dispersion domain using the proposed framework.