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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Kawtrakul, A., Yingsaeree, C., & Andres, F. (2007). A framework of NLP based information tracking and related knowledge organizing with topic maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4592 LNCS, pp. 272–283). Springer Verlag. https://doi.org/10.1007/978-3-540-73351-5_24
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