analyser.java

Classifier4J是一个很好的基于java的分类器,里面有Native bayes和KNN等方法的文本分类.另外还 提供了分词和自动摘要等功能

/*
 * ====================================================================
 * 
 * The Apache Software License, Version 1.1
 *
 * Copyright (c) 2003 Nick Lothian. All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *
 * 1. Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer. 
 *
 * 2. Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in
 *    the documentation and/or other materials provided with the
 *    distribution.
 *
 * 3. The end-user documentation included with the redistribution, if
 *    any, must include the following acknowlegement:  
 *       "This product includes software developed by the 
 *        developers of Classifier4J (http://classifier4j.sf.net/)."
 *    Alternately, this acknowlegement may appear in the software itself,
 *    if and wherever such third-party acknowlegements normally appear.
 *
 * 4. The name "Classifier4J" must not be used to endorse or promote 
 *    products derived from this software without prior written 
 *    permission. For written permission, please contact   
 *    http://sourceforge.net/users/nicklothian/.
 *
 * 5. Products derived from this software may not be called 
 *    "Classifier4J", nor may "Classifier4J" appear in their names 
 *    without prior written permission. For written permission, please 
 *    contact http://sourceforge.net/users/nicklothian/.
 *
 * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
 * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
 * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED.  IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
 * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
 * USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
 * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
 * SUCH DAMAGE.
 * ====================================================================
 */
package net.sf.classifier4J.demo;

import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.sql.SQLException;

import net.sf.classifier4J.ClassifierException;
import net.sf.classifier4J.DefaultTokenizer;
import net.sf.classifier4J.IClassifier;
import net.sf.classifier4J.ITokenizer;
import net.sf.classifier4J.Utilities;
import net.sf.classifier4J.bayesian.BayesianClassifier;
import net.sf.classifier4J.bayesian.JDBMWordsDataSource;

/**
 * @author Nick Lothian
 * @author Peter Leschev
 */
public class Analyser {

	public static String connectionString = Trainer.connectionString;
	public static String username = Trainer.username;
	public static String password = Trainer.password;
	
	static JDBMWordsDataSource wds;
	
	private static IClassifier setupClassifier(ITokenizer tokenizer, String connString, String user, String pw) throws SQLException, IOException {
		/*
		DriverMangerJDBCConnectionManager cm = new DriverMangerJDBCConnectionManager(connString, user, pw);
		JDBCWordsDataSource wds = new JDBCWordsDataSource(cm);
		wds.createTable();
		*/
		wds = new JDBMWordsDataSource("./database/");
		wds.open();
		return new BayesianClassifier(wds, tokenizer);							
	}
        
    /**
     * @returns Words Per Second 
     */        
    public static double useClassifier(ITokenizer tokenizer,
                                       IClassifier classifier, 
                                       InputStream inputStream) throws IOException, ClassifierException {
            
//        System.out.println("Using Classifier4J with " + classifier + " and " +
//                           tokenizer);

        String contents = Utilities.getString(inputStream);
        int length = tokenizer.tokenize(contents).length;

//        System.out.println("Analysing " + length + " words. This may take a while.");
        
        long startTime = System.currentTimeMillis();
        
        double matchProb = classifier.classify(contents);
        
        long endTime = System.currentTimeMillis();
        
        double time = (double)(endTime - startTime) / (double)1000;
        
        if (Double.compare(time, 0) == 0) {
            time = 1;
        }
        
        double wordsPerSecond = length / time;
        
//        System.out.println("Done. Took " + time + " seconds, which is " + 
//                           wordsPerSecond + " words per second.");
        
//        System.out.println("Match Probability = " + matchProb);
//        System.out.println("Is considered a match: " + classifier.isMatch(matchProb));
        
        return wordsPerSecond;
    }

	public static void main(String[] args) throws Exception {		
		System.out.println("This program reads in a single file and classifies it as a match or not.");
		System.out.println("It should be run after the Trainer program.");


		String filename = "./demodata/toanalyse.txt";
                
                
		InputStream input = new FileInputStream(filename);	
                ITokenizer tokenizer = new DefaultTokenizer();
		IClassifier classifier = setupClassifier(tokenizer, connectionString, username, password);
                
                useClassifier(tokenizer, classifier, input);

		wds.close();
	}
	/*
	static {
		try {
			Class.forName("org.hsqldb.jdbcDriver");
			//Class.forName("org.gjt.mm.mysql.Driver");
		} catch (ClassNotFoundException e) {			
			e.printStackTrace();
		}		
	}
	*/	
}