Using Web data to enhance traffic situation awareness

With the ubiquity of mobile communication devices, people experiencing traffic jams share real-time information and interact with each other on social media sites, which provide new channels to monitor, estimate and manage traffic flows. In this paper, we use natural language processing and data mining technologies to extract traffic jam related information from Tianya.cn, analyze the content of people's talk to discover the “talking point” of people when facing traffic jams, and to provide data support for relevant authorities to make successful and effective decisions for real-time traffic jam response and management.

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