Java tutorial
/* * Copyright 2008-2011 Grant Ingersoll, Thomas Morton and Drew Farris * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ------------------- * To purchase or learn more about Taming Text, by Grant Ingersoll, Thomas Morton and Drew Farris, visit * http://www.manning.com/ingersoll */ package com.tamingtext.classifier.mlt; import java.io.BufferedReader; import java.io.File; import java.io.FileInputStream; import java.io.InputStreamReader; import java.io.StringReader; import org.apache.commons.cli2.CommandLine; import org.apache.commons.cli2.Group; import org.apache.commons.cli2.Option; import org.apache.commons.cli2.OptionException; import org.apache.commons.cli2.builder.ArgumentBuilder; import org.apache.commons.cli2.builder.DefaultOptionBuilder; import org.apache.commons.cli2.builder.GroupBuilder; import org.apache.commons.cli2.commandline.Parser; import org.apache.lucene.analysis.Analyzer; import org.apache.lucene.analysis.en.EnglishAnalyzer; import org.apache.lucene.index.IndexReader; import org.apache.lucene.store.Directory; import org.apache.lucene.store.FSDirectory; import org.apache.lucene.util.Version; import org.apache.mahout.classifier.ClassifierResult; import org.apache.mahout.classifier.ResultAnalyzer; import org.apache.mahout.common.CommandLineUtil; import org.apache.mahout.common.commandline.DefaultOptionCreator; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import com.tamingtext.classifier.mlt.TrainMoreLikeThis.MatchMode; import com.tamingtext.util.FileUtil; public class TestMoreLikeThis { private static final Logger log = LoggerFactory.getLogger(TestMoreLikeThis.class); public static void main(String[] args) throws Exception { DefaultOptionBuilder obuilder = new DefaultOptionBuilder(); ArgumentBuilder abuilder = new ArgumentBuilder(); GroupBuilder gbuilder = new GroupBuilder(); Option helpOpt = DefaultOptionCreator.helpOption(); Option inputDirOpt = obuilder.withLongName("input").withRequired(true) .withArgument(abuilder.withName("input").withMinimum(1).withMaximum(1).create()) .withDescription("The input directory").withShortName("i").create(); Option modelOpt = obuilder.withLongName("model").withRequired(true) .withArgument(abuilder.withName("index").withMinimum(1).withMaximum(1).create()) .withDescription("The directory containing the index model").withShortName("m").create(); Option categoryFieldOpt = obuilder.withLongName("categoryField").withRequired(true) .withArgument(abuilder.withName("index").withMinimum(1).withMaximum(1).create()) .withDescription("Name of the field containing category information").withShortName("catf") .create(); Option contentFieldOpt = obuilder.withLongName("contentField").withRequired(true) .withArgument(abuilder.withName("index").withMinimum(1).withMaximum(1).create()) .withDescription("Name of the field containing content information").withShortName("contf") .create(); Option maxResultsOpt = obuilder.withLongName("maxResults").withRequired(false) .withArgument(abuilder.withName("gramSize").withMinimum(1).withMaximum(1).create()) .withDescription("Number of results to retrive, default: 10 ").withShortName("r").create(); Option gramSizeOpt = obuilder.withLongName("gramSize").withRequired(false) .withArgument(abuilder.withName("gramSize").withMinimum(1).withMaximum(1).create()) .withDescription("Size of the n-gram. Default Value: 1 ").withShortName("ng").create(); Option typeOpt = obuilder.withLongName("classifierType").withRequired(false) .withArgument(abuilder.withName("classifierType").withMinimum(1).withMaximum(1).create()) .withDescription("Type of classifier: knn|tfidf. Default: bayes").withShortName("type").create(); Group group = gbuilder.withName("Options").withOption(gramSizeOpt).withOption(helpOpt) .withOption(inputDirOpt).withOption(modelOpt).withOption(typeOpt).withOption(contentFieldOpt) .withOption(categoryFieldOpt).withOption(maxResultsOpt).create(); try { Parser parser = new Parser(); parser.setGroup(group); parser.setHelpOption(helpOpt); CommandLine cmdLine = parser.parse(args); if (cmdLine.hasOption(helpOpt)) { CommandLineUtil.printHelp(group); return; } String classifierType = (String) cmdLine.getValue(typeOpt); int gramSize = 1; if (cmdLine.hasOption(gramSizeOpt)) { gramSize = Integer.parseInt((String) cmdLine.getValue(gramSizeOpt)); } int maxResults = 10; if (cmdLine.hasOption(maxResultsOpt)) { maxResults = Integer.parseInt((String) cmdLine.getValue(maxResultsOpt)); } String inputPath = (String) cmdLine.getValue(inputDirOpt); String modelPath = (String) cmdLine.getValue(modelOpt); String categoryField = (String) cmdLine.getValue(categoryFieldOpt); String contentField = (String) cmdLine.getValue(contentFieldOpt); MatchMode mode; if ("knn".equalsIgnoreCase(classifierType)) { mode = MatchMode.KNN; } else if ("tfidf".equalsIgnoreCase(classifierType)) { mode = MatchMode.TFIDF; } else { throw new IllegalArgumentException("Unkown classifierType: " + classifierType); } Directory directory = FSDirectory.open(new File(modelPath)); IndexReader indexReader = IndexReader.open(directory); Analyzer analyzer //<co id="mlt.analyzersetup"/> = new EnglishAnalyzer(Version.LUCENE_36); MoreLikeThisCategorizer categorizer = new MoreLikeThisCategorizer(indexReader, categoryField); categorizer.setAnalyzer(analyzer); categorizer.setMatchMode(mode); categorizer.setFieldNames(new String[] { contentField }); categorizer.setMaxResults(maxResults); categorizer.setNgramSize(gramSize); File f = new File(inputPath); if (!f.isDirectory()) { throw new IllegalArgumentException(f + " is not a directory or does not exit"); } File[] inputFiles = FileUtil.buildFileList(f); String line = null; //<start id="lucene.examples.mlt.test"/> final ClassifierResult UNKNOWN = new ClassifierResult("unknown", 1.0); ResultAnalyzer resultAnalyzer = //<co id="co.mlt.ra"/> new ResultAnalyzer(categorizer.getCategories(), UNKNOWN.getLabel()); for (File ff : inputFiles) { //<co id="co.mlt.read"/> BufferedReader in = new BufferedReader(new InputStreamReader(new FileInputStream(ff), "UTF-8")); while ((line = in.readLine()) != null) { String[] parts = line.split("\t"); if (parts.length != 2) { continue; } CategoryHits[] hits //<co id="co.mlt.cat"/> = categorizer.categorize(new StringReader(parts[1])); ClassifierResult result = hits.length > 0 ? hits[0] : UNKNOWN; resultAnalyzer.addInstance(parts[0], result); //<co id="co.mlt.an"/> } in.close(); } System.out.println(resultAnalyzer.toString());//<co id="co.mlt.print"/> /* <calloutlist> <callout arearefs="co.mlt.ra">Create <classname>ResultAnalyzer</classname></callout> <callout arearefs="co.mlt.read">Read Test data</callout> <callout arearefs="co.mlt.cat">Categorize</callout> <callout arearefs="co.mlt.an">Collect Results</callout> <callout arearefs="co.mlt.print">Display Results</callout> </calloutlist> */ //<end id="lucene.examples.mlt.test"/> } catch (OptionException e) { log.error("Error while parsing options", e); } } }