This directory contains IPython scripts for analyzing real-world speed observations from sensors.
Traffic Event Extraction From Tweets
This project has two major components: (1) Annotator and (2) Extractor
Annotator
Sequence labeling model trained with declarative knowledge from location and event knowledge base is utilized for annotation of raw tweets. Open Street Maps [1] is used as a location based knowledge specific to a city and 511.org [2] schema of events is used as a knowledge of traffic related events. Each word in a tweet is assigned a tag (one of: B-LOCATION, I-LOCATION, B-EVENT, I-EVENT, OTHER).
Download all the data files from [3] and place it in a directory called "data". Download all the models (from files tab) and place it in a directory called "models". You can invoke the annotator using the command:
java -cp eventannotation.jar org.ccsr.tagging.CreateAnnotatedData models/model-twitter
This code will take a while to run and the output is a file containing all the event terms and locations (this file is named final-training-data.txt). This file is the input for the extraction phase that follows.
Extractor
Extraction algorithms use space, time and theme characteristic of city events to aggregate all the tags for emitting events.
Download extractevents.py and place the output of the annotation phase (final-training-data.txt) in a directory called "data". Invoke the python script for aggregating annotations to emit events using the command:
/usr/bin/python extractevents.py
Citation If you use this work, please cite:
Pramod Anantharam, Payam Barnaghi, Krishnaprasad Thirunarayan, and Amit Sheth. 2015. Extracting City Traffic Events from Social Streams. ACM Trans. Intell. Syst. Technol. 6, 4, Article 43 (July 2015), 27 pages. DOI=http://dx.doi.org/10.1145/2717317
References
[1] Open Street Maps: http://www.openstreetmap.org/
[2] 511.org knowledge of traffic events: http://511.org/docs/TOMSSchema.zip
[3] Dataset used for experiments: https://app.box.com/s/uvws6ztf5jzbc8cxmb9b4r6a1zuei0pt
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
