inception-recommender
External recommender implemented with DKPro Text Classification.
Setup & Run
How to build the external recommender project
Change directory into the recommender-server subproject. The project is build via Maven3 by using the following command:
mvn clean install
You should find in the target folder a .jar file named recommender-server.jar.
Running the recommender-server.jar
The server requires three parameters to run, which should be placed in a file that is provided at start up.
logging.file=logfile.txt
repositoryRoot=modelRoot
server.port=30500
repositoryRoot is the path to the folder in which the models will be stored. The folder will be created if it does not exist yet.
server.port is the port on which the server listens for requests.
This file is provided as parameter when the sever is started:
java
-jar target/recommender-server.jar
--spring.config.location=/path/to/file/with/parameters.properties
Please make sure to use the file ending .properties for the configuration file. If you run into RAM issues, assign a suited amount of RAM by providing additionally the -Xmx=4g flag right after the -jar command for assinging more RAM to the Java Virtual Machine.
Requests for training new models and requests for prediction
Once the server runs, requests are served under /train for training and /predict for prediction, i.e.
# Train requests
http://yourIp:serverPort/train
# Prediction requests
http://yourIp:serverPort/predict
Data format of train/predict requests
The data format for training and prediction requests is described in the INCEpTION developer documentation .