AlexTitovWork

 /**
    * Data model generator based on gen_data.txt
    */
	public void makeDataTrainingModel() {

            model = null;
            System.out.println("POS model started");
            InputStream dataIn = null;
            try {
                String currentDir = new File("").getAbsolutePath();

AlexTitovWork

 public ArrayList textAnalisis(String inputdata){
    
 
        System.out.println("-> Nimbler: RestController: current message:\n " + inputdata);
        /**
         * Detector of sentence and divide text on independent sentence.
         */
        String[] sentences = sentenceDetect(inputdata);
        System.out.println(Arrays.toString(sentences));
        /**

AlexTitovWork

    public void makeDataTrainingModel() {

        model = null;
        System.out.println("POS model started");
//        InputStream dataIn = null;
        InputStreamFactory dataIn = null;
        try {
             final String currentDir = new File("").getAbsolutePath();

AlexTitovWork

    public String[] sentenceDetect(String message) {

        System.out.println("-> OpenNLP: sentence detector");
        return sentenceDetector.sentDetect(message);
    }

    public String[] tokenize(String message) {

        System.out.println("-> OpenNLP: token detector");
        return tokenizer.tokenize(message);

AlexTitovWork

import java.io.IOException;

public class NlpProductClassifier {

     public static void main(String[] args) throws IOException {

         NLPClassifier CL = new NLPClassifier();
         /**
          * Sentence detector test
          */

AlexTitovWork

/**
 * Naive Bayes
 */
import weka.classifiers.bayes.NaiveBayesMultinomial;
/**
 * Weka tools
 */
import weka.classifiers.Evaluation;
import weka.classifiers.meta.FilteredClassifier;
import weka.core.Attribute;

AlexTitovWork

 DebitCreditWekaClassifier() {
        /*
         * Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
         */
        classifier = new FilteredClassifier();
        /**
         * Class for building and using a multinomial Naive Bayes classifier. For more information see,
         * Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification.
         * https://weka.sourceforge.io/doc.dev/weka/classifiers/bayes/NaiveBayesMultinomial.html
         */

AlexTitovWork

 private static Logger LOGGER = Logger.getLogger("DebitCreditInternalSystem");

    private FilteredClassifier classifier;
    /**
     * Declare train and test data Instances
     */
    private Instances trainData;
    /**
     * Declare Instance's attributes 
     */

AlexTitovWork

   /**
     * load training data and set feature generators
     */
    public void transform() {
        try {
            trainData = loadDataset(TRAIN_DATA);
            saveArff(trainData, TRAIN_ARFF_ARFF);
            /**
             * create the filter and set the attribute to be transformed from text into a feature vector (the last one)
             */

AlexTitovWork

   /**
     * Build prepared classifier on the training data
     */
    public void fit() {
        try {
            classifier.buildClassifier(trainData);
        } catch (Exception e) {
            LOGGER.warning(e.getMessage());
        }
    }