public static ArrayList<TaggedWord> StopWordRemoval(ArrayList<TaggedWord> taggedWords) {
ArrayList<TaggedWord> newList = new ArrayList<TaggedWord>();
try {
String path = "data/nltk_stoplist.txt";
File textFile = new File(path);
BufferedReader br = new BufferedReader(new FileReader(textFile));
String stopwordsLine = br.readLine();
br.close();
String[] stopwords = stopwordsLine.split(",");
HashMap<String, String> stopwordsDict = new HashMap<String, String>();
for (int i = 0; i < stopwords.length; i++) {
stopwordsDict.put(stopwords[i], stopwords[i]);
}
for (int i = 0; i < taggedWords.size(); i++) {
String word = taggedWords.get(i).word();
String posTag = taggedWords.get(i).tag();
if (!stopwordsDict.containsKey(word.toLowerCase())) {
String newWord, newPosTag;
newWord = word;
newPosTag = posTag;
newList.add(new TaggedWord(newWord, newPosTag));
}
}
} catch (Exception ex) {
ex.printStackTrace();
}
return newList;
}
public static ArrayList<ArrayList<TaggedWord>> getPhrasesNaive(
String sentence, LexicalizedParser lp, AbstractSequenceClassifier<CoreLabel> classifier) {
ArrayList<ArrayList<TaggedWord>> newList = new ArrayList<ArrayList<TaggedWord>>();
ArrayList<TaggedWord> taggedWords = StanfordNER.parse(sentence, lp, classifier);
HashMap<String, String> phraseBoundaries = new HashMap<String, String>();
phraseBoundaries.put(",", ",");
phraseBoundaries.put("\"", "\"");
phraseBoundaries.put("''", "''");
phraseBoundaries.put("``", "``");
phraseBoundaries.put("--", "--");
// List<Tree> leaves = parse.getLeaves();
ArrayList<TaggedWord> temp = new ArrayList<TaggedWord>();
int index = 0;
while (index < taggedWords.size()) {
if ((phraseBoundaries.containsKey(taggedWords.get(index).word()))) {
if (temp.size() > 0) {
// System.out.println(temp);
ArrayList<TaggedWord> tempCopy = new ArrayList<TaggedWord>(temp);
newList.add(Preprocess(tempCopy));
}
temp.clear();
} else {
// System.out.println(taggedWords.get(index).toString());
temp.add(taggedWords.get(index));
}
index += 1;
}
if (temp.size() > 0) {
ArrayList<TaggedWord> tempCopy = new ArrayList<TaggedWord>(temp);
newList.add(Preprocess(tempCopy));
}
// System.out.println(newList);
return newList;
}
public static double LexicalSimilarityScoreMin(
ArrayList<TaggedWord> taggedWords1,
ArrayList<TaggedWord> taggedWords2,
DISCOSimilarity discoRAM,
LexicalizedParser lp) {
// System.out.println(taggedWords1.size() + "," + taggedWords2.size());
// array of edge weights with default weight 0
int length1 = taggedWords1.size();
int length2 = taggedWords2.size();
int arrSize = Math.max(length1, length2);
double[][] array = new double[arrSize][arrSize];
for (int i = 0; i < arrSize; i++) {
for (int j = 0; j < arrSize; j++) {
array[i][j] = 0;
}
}
for (int i = 0; i < length1; i++) {
for (int j = 0; j < length2; j++) {
String word1 = taggedWords1.get(i).word();
String word2 = taggedWords2.get(j).word();
double edgeWeight = 0;
// LSA Similarity
// edgeWeight = LSASimilarity.LSAWordSimilarity(word1, word2);
// DISCO Similarity
// DISCOSimilarity discoObj = new DISCOSimilarity();
try {
if (word1.compareToIgnoreCase(word2) == 0) edgeWeight = 1;
else {
edgeWeight = discoRAM.similarity2(word1, word2);
// edgeWeight = LSASimilarity.LSAWordSimilarity(word1, word2);
}
} catch (Exception ex) {
ex.printStackTrace();
}
array[i][j] = edgeWeight;
}
}
// System.out.println("Hungarian starts " + arrSize);
double finalScore;
String sumType = "max";
int minLength = Math.min(length1, length2);
finalScore = HungarianAlgorithm.hgAlgorithm(array, sumType) / minLength * 5;
// finalScore = HungarianAlgorithm.hgAlgorithm(array, sumType)/arrSize * 5;
return finalScore;
}
public static ArrayList<TaggedWord> PreprocessPhrase(ArrayList<TaggedWord> taggedWords) {
ArrayList<TaggedWord> newList = new ArrayList<TaggedWord>();
taggedWords = Preprocess(taggedWords);
for (int i = 0; i < taggedWords.size(); i++) {
String posTag = taggedWords.get(i).tag();
if (posTag.length() >= 2) {
String reducedTag = posTag.substring(0, 2);
if (reducedTag.equals("CD") || reducedTag.equals("NN") || reducedTag.equals("VB")) {
newList.add(taggedWords.get(i));
}
}
}
return newList;
}
public static double BestWordMatchEdgeWeight(
ArrayList<TaggedWord> taggedWords1,
ArrayList<TaggedWord> taggedWords2,
DISCOSimilarity discoRAM) {
double bestMatchScore = 0;
for (int i = 0; i < taggedWords1.size(); i++) {
String word1 = taggedWords1.get(i).word();
for (int j = 0; j < taggedWords2.size(); j++) {
String word2 = taggedWords2.get(j).word();
double currentScore;
if (word1.equals(word2)) currentScore = 1;
else currentScore = discoRAM.similarity2(word1, word2);
if (currentScore > bestMatchScore) bestMatchScore = currentScore;
}
}
return bestMatchScore;
}
@SuppressWarnings("static-access")
@Override
public EventSet createEventSet(Document doc) {
EventSet es = new EventSet(doc.getAuthor());
char[] text = doc.getProcessedText();
String stringText = new String(text);
// use MaxentPOSTagsEventDriver's tagger
// initialize tagger and return empty event set if encountered a problem
if (tagger == null) {
tagger = MaxentPOSTagsEventDriver.initTagger();
if (tagger == null) return es;
}
List<List<HasWord>> sentences =
tagger.tokenizeText(new BufferedReader(new StringReader(stringText)));
ArrayList<TaggedWord> tagged = new ArrayList<TaggedWord>();
for (List<HasWord> sentence : sentences) tagged.addAll(tagger.tagSentence(sentence));
int i, j, n;
try {
n = Integer.parseInt(getParameter("N"));
} catch (NumberFormatException e) {
n = 2;
}
String curr;
for (i = 0; i < tagged.size() - n + 1; i++) {
curr = "(" + tagged.get(i).tag() + ")";
for (j = 1; j < n; j++) {
curr += "-(" + tagged.get(i + j).tag() + ")";
}
es.addEvent(new Event(curr));
}
sentences.clear();
sentences = null;
return es;
}
public static double LexicalSimilarityScoreMax(
ArrayList<TaggedWord> taggedWords1,
ArrayList<TaggedWord> taggedWords2,
DISCOSimilarity discoRAM,
LexicalizedParser lp) {
// System.out.println(taggedWords1.size() + "," + taggedWords2.size());
// array of edge weights with default weight 0
int length1 = taggedWords1.size();
int length2 = taggedWords2.size();
int arrSize = Math.max(length1, length2);
double[][] array = new double[arrSize][arrSize];
for (int i = 0; i < arrSize; i++) {
for (int j = 0; j < arrSize; j++) {
array[i][j] = 0;
}
}
for (int i = 0; i < length1; i++) {
for (int j = 0; j < length2; j++) {
String word1 = taggedWords1.get(i).word();
String posTag1 = taggedWords1.get(i).tag();
String word2 = taggedWords2.get(j).word();
String posTag2 = taggedWords2.get(j).tag();
ArrayList<TaggedWord> newList1 = new ArrayList<TaggedWord>();
if (posTag1.length() >= 3 && posTag1.substring(0, 3).equals("NNP")) {
newList1.add(taggedWords1.get(i));
} else {
String[] words = word1.split(" ");
for (int k = 0; k < words.length; k++) newList1.add(new TaggedWord(words[k], posTag1));
}
ArrayList<TaggedWord> newList2 = new ArrayList<TaggedWord>();
if (posTag2.length() >= 3 && posTag2.substring(0, 3).equals("NNP")) {
newList2.add(taggedWords2.get(j));
} else {
String[] words = word2.split(" ");
for (int k = 0; k < words.length; k++) newList2.add(new TaggedWord(words[k], posTag2));
}
double edgeWeight = LexicalSimilarityScoreMin(newList1, newList2, discoRAM, lp);
array[i][j] = edgeWeight;
}
}
// System.out.println("Hungarian starts " + arrSize);
double finalScore;
String sumType = "max";
// int minLength = Math.min(length1, length2);
// finalScore = HungarianAlgorithm.hgAlgorithm(array, sumType)/minLength * 5;
finalScore = HungarianAlgorithm.hgAlgorithm(array, sumType) / arrSize * 5;
return finalScore;
}
public static ArrayList<TaggedWord> Preprocess(ArrayList<TaggedWord> taggedWords) {
ArrayList<TaggedWord> newList = new ArrayList<TaggedWord>();
String[] punctuationsAndSpecialCharacters = {
",", ".", "?", "!", ":", ";", "\"", "-", "--", "'", "-LRB-", "-RRB-", "''", "``", "&"
}; // , "/", "\\", "<", ">", "#", "&", "*", "(", ")", "{", "}", "[", "]", "~", "|"};
HashMap<String, String> punctuationMarks = new HashMap<String, String>();
for (int i = 0; i < punctuationsAndSpecialCharacters.length; i++) {
punctuationMarks.put(
punctuationsAndSpecialCharacters[i], punctuationsAndSpecialCharacters[i]);
}
for (int i = 0; i < taggedWords.size(); i++) {
String word = taggedWords.get(i).word();
String posTag = taggedWords.get(i).tag();
if (!punctuationMarks.containsKey(word)) {
if (!(posTag.length() > 2 && posTag.substring(0, 3).equals("NNP"))) {
word = Morphology.lemmaStatic(word, posTag, true);
word = word.replace('-', ' ');
}
String newWord, newPosTag;
if (word.equals("n't")) newWord = "not";
else if (word.equals("'s")) newWord = "is";
else if (word.equals("'ll")) newWord = "will";
else if (word.equals("'m") || word.equals("m")) newWord = "am";
else if (word.equals("im")) newWord = "am";
else newWord = word;
newPosTag = posTag;
newList.add(new TaggedWord(newWord, newPosTag));
}
}
newList = StopWordRemoval(newList);
return newList;
}
public static void main(String args[]) {
// String sentence1 = "A large bird standing on a table picks up a plastic glass
// containing liquid and places it in a bowl of something.";
// String sentence2 = "A bird picks up a plastic cup containing a liquid with it's beak
// and puts the cup into a bowl.";
// LexicalizedParser lp = new LexicalizedParser("englishPCFG.ser.gz");
// LeskWSD tm = new LeskWSD(lp);
// WordNetSimilarity ws = new WordNetSimilarity();
//
// System.out.println(LexicalSimilarityScoreWordNet(sentence1, sentence2, tm, lp, ws));
String sentence =
"The broader Standard & Poor's 500 Index <.SPX> shed 2.38 points, or 0.24 percent, at 995.10.";
LexicalizedParser lp = new LexicalizedParser("englishPCFG.ser.gz");
Tree parse = lp.apply(sentence);
ArrayList<TaggedWord> taggedWords = parse.taggedYield();
taggedWords = Preprocess(taggedWords);
for (int i = 0; i < taggedWords.size(); i++) System.out.println(taggedWords.get(i).word());
}
public static double LexicalSimilarityScoreWordNet(
String sentence1, String sentence2, LeskWSD tm, LexicalizedParser lp, WordNetSimilarity ws) {
ArrayList<TaggedWord> taggedWordsPrev1 = Preprocess(StanfordParse(sentence1, lp));
ArrayList<TaggedWord> taggedWordsPrev2 = Preprocess(StanfordParse(sentence2, lp));
ArrayList<TaggedWord> taggedWords1 = new ArrayList<TaggedWord>();
ArrayList<TaggedWord> taggedWords2 = new ArrayList<TaggedWord>();
WordNetSense[] sensesPrev1 = tm.LeskJWI(sentence1);
WordNetSense[] sensesPrev2 = tm.LeskJWI(sentence2);
// System.out.println("Senses found!");
ArrayList<WordNetSense> senses1 = new ArrayList<WordNetSense>();
ArrayList<WordNetSense> senses2 = new ArrayList<WordNetSense>();
for (int i = 0; i < taggedWordsPrev1.size(); i++) {
String word = taggedWordsPrev1.get(i).word();
String posTag = taggedWordsPrev1.get(i).tag();
if (posTag.length() >= 2 && posTag.substring(0, 2).equals("NN")) {
taggedWords1.add(new TaggedWord(word, "NN"));
senses1.add(sensesPrev1[i]);
} else if (posTag.length() >= 2 && posTag.substring(0, 2).equals("VB")) {
taggedWords1.add(new TaggedWord(word, "VB"));
senses1.add(sensesPrev1[i]);
}
}
for (int i = 0; i < taggedWordsPrev2.size(); i++) {
String word = taggedWordsPrev2.get(i).word();
String posTag = taggedWordsPrev2.get(i).tag();
if (posTag.length() >= 2 && posTag.substring(0, 2).equals("NN")) {
taggedWords2.add(new TaggedWord(word, "NN"));
senses2.add(sensesPrev2[i]);
} else if (posTag.length() >= 2 && posTag.substring(0, 2).equals("VB")) {
taggedWords2.add(new TaggedWord(word, "VB"));
senses2.add(sensesPrev2[i]);
}
}
// System.out.println(taggedWords1.size() + "," + taggedWords2.size());
// array of edge weights with default weight 0
int length1 = taggedWords1.size();
int length2 = taggedWords2.size();
int arrSize = Math.max(length1, length2);
double[][] array = new double[arrSize][arrSize];
for (int i = 0; i < arrSize; i++) {
for (int j = 0; j < arrSize; j++) {
array[i][j] = 0;
}
}
for (int i = 0; i < length1; i++) {
for (int j = 0; j < length2; j++) {
String word1 = taggedWords1.get(i).word();
String posTag1 = taggedWords1.get(i).tag();
String word2 = taggedWords2.get(j).word();
String posTag2 = taggedWords2.get(j).tag();
double edgeWeight = 0;
// LSA Similarity
// edgeWeight = LSASimilarity.LSAWordSimilarity(word1, word2);
// DISCO Similarity
// DISCOSimilarity discoObj = new DISCOSimilarity();
try {
if (word1.compareToIgnoreCase(word2) == 0) edgeWeight = 1;
else {
// edgeWeight = ws.wuPalmerSimilarity(senses1.get(i), senses2.get(j));
edgeWeight = ws.linSimilarity(senses1.get(i), senses2.get(j));
}
} catch (Exception ex) {
ex.printStackTrace();
}
array[i][j] = edgeWeight;
}
}
// System.out.println("Hungarian starts " + arrSize);
double finalScore;
String sumType = "max";
int minLength = Math.min(length1, length2);
// finalScore = HungarianAlgorithm.hgAlgorithm(array, sumType)/minLength * 5;
if (arrSize == 0) finalScore = 0;
else finalScore = HungarianAlgorithm.hgAlgorithm(array, sumType) / arrSize * 5;
return finalScore;
}