Creation of topic map with shallow parsing in Chinese

XML topic maps enable multiple, concurrent views of sets of information objects and can be used to different applications. However, to enrich the information or metadata of a topic map or to connect with some document's URI is very labor-intensive and time-consuming. To solve this problem, we propose an approach based on natural language processing techniques to identify and extract useful information in raw Chinese text. Unlike most approaches to parsing sentences based on the integration of complex linguistic information and domain knowledge, we use shallow parsing instead of complex parsing to analyze the constituents and their relationship in discourse. After a document is processed, we may assign this document into a topic node and add the information extracted from the raw text into a topic map.