ikaas/anomaly-detection repository overview

The image do not contains any tweets or sensing data, which should be collected before running the images. The process is as follows (note: information in <> is defined by user):

1. Run docker image with tag copyfiles: $ docker run --name cf anomaly-detection:copyfiles
2. Copy all the files from the running container, i.e. cf, into a volume in the host: $ docker cp cd:/app <volume_path_in_host>
3. Copy pre-collected sensing data and tweets into <volume_path_in_host>
4. Run ad_run.sh: Method 1: run in terminal (require MCR 2017a installed in <mcr_directory>): $ ./ad_run.sh <mcr_directory> <sensing_data_filename> Method 2: run in docker container: $ docker run -v <volume_path_in_host>:/app anomaly-detection:ad <sensing_data_filename> Note: if <sensing_data_filename> is not provided, the program will use a default name: data.csv
5. Run TwiEvent.jar: Method 1: run in terminal: $ java -jar TwiEvent.jar <filename_list_tweets_file_in_each_line> Method 2: run in docker container: $ docker run -v volume_path_in_host:/app anomaly-detection:tx <filename_list_tweets_file_in_each_line> Note: if <filename_list_tweets_file_in_each_line> is not provided, the program will use a default name: tweetslist.txt
6. Run TwitterCorr.jar: Method 1: run in terminal: $ java -jar TwitterCorr.jar Method 2: run in docker container: $ docker run -v volume_path_in_host:/app anomaly-detection:tc