This is a author age categorizer that leverages the Apache OpenNLP Maximum Entropy Classifier. It takes a text sample and classifies it into the following age categories: xx-18|18-24|25-34|35-49|50-64|65-xx.
Note: The training data should be a line-by-line, with each line starting with the age, or age category, followed by a tab and the text associated with the age.
Usage: bin/authorage AgeClassifyTrainer [-factory factoryName] [-featureGenerators featuregens] [-tokenizer tokenizer] -model modelFile [-params paramsFile] -lang language -data sampleData [-encoding charsetName]
Arguments description:
-factory factoryName
a sub-class of DoccatFactory where to get implementation and resources.
-featureGenerators featuregens
comma separated feature generator classes. Bag of words default.
-tokenizer tokenizer
tokenizer implementation. WhitespaceTokenizer is used if not specified.
-model modelFile
output model file.
-params paramsFile
training parameters file.
-lang language
language which is being processed.
-data sampleData
data to be used, usually a file name.
-encoding charsetName
encoding for reading and writing text, if absent the system default is used.Example Usage:
bin/authorage AgeClassifyTrainer -model model/en-ageClassify.bin -lang en -data data/train.txt -encoding UTF-8Training data format - Age and text seperated by tab in each line like <AGE><Tab><TEXT>
Sample training data-
12 I am just 12 year old
25 I am little bigger
35 I am mature
45 I am getting old
60 I am old like wine
Usage: bin/authorage AgeClassifyEvaluator -model model [-misclassified true|false] -data sampleData [-encoding charsetName]
Arguments description:
-model model
the model file to be evaluated.
-misclassified true|false
if true will print false negatives and false positives.
-data sampleData
data to be used, usually a file name.
-encoding charsetName
encoding for reading and writing text, if absent the system default is used.Example Usage:
bin/authorage AgeClassifyEvaluator -model model/en-ageClassify.bin -data data/test.txt -encoding UTF-8Note: Each document must be followed by an empty line to be detected as a separate case from the others.
Usage: bin/authorage AgeClassify model < documentsUsage: bin/authorage AgePredict ./model/classify-unigram.bin ./model/regression-global.bin data/sample_test.txtFor AgePredict to work you need to download en-pos-maxent.bin, en-sent.bin and en-token.bin from http://opennlp.sourceforge.net/models-1.5/ to model/opennlp/
If you use this work, please cite:
@article{hong2017ensemble,
title={Ensemble Maximum Entropy Classification and Linear Regression for Author Age Prediction},
author={Hong, Joey and Mattmann, Chris and Ramirez, Paul},
booktitle={Information Reuse and Integration (IRI), 2017 IEEE 18th International Conference on},
organization={IEEE}
year={2017}
}
- Chris A. Mattmann, JPL & USC
- Joey Hong, Caltech
- Madhav Sharan, JPL & USC