id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-016556-tdwwu43v	Kawtrakul, Asanee	Semantic Tracking in Peer-to-Peer Topic Maps Management	2007		.txt	text/plain	4351	247	43	This paper presents a collaborative semantic tracking framework based on topic maps 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 present the architecture we defined in order to support highly relevant semantic management and to provide adaptive services such as statistical information extraction technique for document summarization. The proposed model for extracting information from unstructured documents consists of three main components, namely Entity Recognition, Relation Extraction, and Output Generation, as illustrate in Fig. 3 . The difference between our framework and those systems is that we also emphasize on generating the semantic relations among the collected resources and organizing those information by using topic map model. A Framework of NLP based Information Tracking and related Knowledge Organizing with Topic Maps	./cache/cord-016556-tdwwu43v.txt	./txt/cord-016556-tdwwu43v.txt