Hi all, We are working on a road traffic extractor from Twitter feed. Here we are extracting useful road traffic information from a public Twitter feed using natural language processing tools and then publishing to WSO2 CEP. Feed was narrowed down to @road_lk Twitter account, popular for posting free crowd sourced traffic alerts. @road_lk feed also was used train NLP models which are utilized for name entity recognition.
In real time scenario, users can view/search for road traffic from a web UI and also can subscribe for a location to receive traffic alerts regularly. To generate traffic information available in feed alerts, Twitter feed is processed in two steps. First each tweet will go through the NLP module and location, traffic level will be extracted from it. Then these extractions will be published to CEP as an input event stream. Custom Siddhi queries will further process streams to generate traffic information according to user request which will be published back to web UI or to alerts. We have currently implemented modules given in the diagram. At our last code review it was suggested to make following changes to our current implementation. 1. Use ESB or CEP as the data publishing server instead of a custom server 2. Use existing NLP toolbox for name entity recognition 3. Use ESB Twitter connector for Twitter interactions 4. Integrate implemented extra UI features to existing geo-dashboard Your valuable feedback and suggestions on above changes will be much appreciated. Thanks and best regards. -- *CD Athuraliya* Software Engineering Intern WSO2, Inc. lean . enterprise . middleware Mobile: +94 716288847 LinkedIn <http://lk.linkedin.com/in/cdathuraliya> | Twitter <https://twitter.com/cdathuraliya> | Blog <http://cdathuraliya.tumblr.com/>
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