/*
* THIS IS NOT LONGER USED was just implemented in the first VERSION
* Implementation of the inefficient algorithm given in the paper
* Searches for matches of size l for string S, whose minmum overlap of ngrams is min_overlap, in the dictionary d
* @param s string we are looking for
* @param min_overlap min number of matching ngrams between s and Y, for Y to be a match for S
* @param d dictionary
* @param l size of Y, given that Y is a match for S
* @return the list of Ids which are matches to S of size L and whose min number of common ngrams with S is min_overlap
*/
private static ArrayList<Integer> overlap(
String s, int min_overlap, DictionaryGenerator d, int l) {
// list of matches to return at the end
ArrayList<Integer> listOfMatches = new ArrayList<Integer>();
// list of ngrams of the string S
ArrayList<String> ngramList = Ngram.splitIntoNGrams(s, d.getNgramSize());
// count of how many times a string has matched, in order to make sure the overlap is higher
// than min_overlap
HashMap<Integer, Integer> m = new HashMap<Integer, Integer>();
for (int i = 0; i < ngramList.size(); i++) {
String ngram = ngramList.get(i);
ArrayList<Integer> matches_ = d.searchTerm(l, ngram);
System.err.println(
"looking for matches of ngram: "
+ ngramList.get(i)
+ " in strings of size: "
+ l
+ " --Matches:"
+ matches_.size());
HashSet<Integer> matches = new HashSet<Integer>();
for (int j = 0; j < matches_.size(); j++) {
matches.add(matches_.get(j));
}
Iterator it = matches.iterator();
while (it.hasNext()) {
Integer currentMatch = (Integer) it.next();
int currentCount = 0;
if (m.containsKey(currentMatch)) {
currentCount = m.get(currentMatch);
} else {
m.put(currentMatch, 0);
}
int newValue = currentCount + 1;
m.put(currentMatch, newValue);
if (min_overlap <= newValue) {
System.err.println("match:" + currentMatch + "--" + newValue);
listOfMatches.add(currentMatch);
}
}
}
return listOfMatches;
}
public static void search(DictionaryGenerator d, Measure m, String s) {
// preprocessing S(adding extra characters as described in the paper)
s = Ngram.preprocessTerm(s, d.getNgramSize());
// looking for the range in which strings have to be looked up
int max = m.max(s, d.getNgramSize());
int min = m.min(s, d.getNgramSize());
// just debugging
System.err.println("------------- ");
System.err.println("searching: " + s);
System.err.println("range: [" + min + "," + max + "]");
// set of matches
HashSet<Integer> solutions = new HashSet<Integer>();
// iterate through all the posible sizes
for (int l = min; l <= max; l++) {
// min overlap called t in the paper
int min_overlap = m.t(s, d.getNgramSize(), l);
System.err.println("min_overlap:" + min_overlap);
// look for solutions for strings with size l
ArrayList<Integer> matches = overlap_nonnaive(s, min_overlap, d, l);
// add the found solutions to the set of solutions
for (int i = 0; i < matches.size(); i++) {
solutions.add(matches.get(i));
}
}
// decode solutions, since they are used with id's a translation to strings have to be done :)
System.err.println("Result:");
Iterator sol = solutions.iterator();
while (sol.hasNext()) {
int id = (Integer) sol.next();
System.err.println("\t " + d.getTerm(id));
}
}
/*
* Implementation of the efficient algorithm given in the paper
* Searches for matches of size l for string S, whose minmum overlap of ngrams is min_overlap, in the dictionary d
* @param s string we are looking for
* @param min_overlap min number of matching ngrams between s and Y, for Y to be a match for S
* @param d dictionary
* @param l size of Y, given that Y is a match for S
* @return the list of Ids which are matches to S of size L and whose min number of common ngrams with S is min_overlap
*/
private static ArrayList<Integer> overlap_nonnaive(
String s, int min_overlap, DictionaryGenerator d, int l) {
// list of matches to return at the end
ArrayList<Integer> listOfMatches = new ArrayList<Integer>();
// list of ngrams of the string S
ArrayList<String> ngramList = Ngram.splitIntoNGrams(s, d.getNgramSize());
// count of how many times a string has matched, in order to make sure the overlap is higher
// than min_overlap
HashMap<Integer, Integer> m = new HashMap<Integer, Integer>();
// order listOfNgrams increnmentally to the least common ngram to the most common
PriorityQueue queueEntitiesPerNgram = new PriorityQueue();
for (int i = 0; i < ngramList.size(); i++) {
ArrayList<Integer> tempListOfTermsForNgramI = d.searchTerm(l, ngramList.get(i));
Orderable<ArrayList<Integer>> orderable_temp =
new Orderable<ArrayList<Integer>>(
tempListOfTermsForNgramI, i, tempListOfTermsForNgramI.size());
queueEntitiesPerNgram.add(orderable_temp);
}
List<Orderable<ArrayList<Integer>>> queueIntoList =
new LinkedList<Orderable<ArrayList<Integer>>>(queueEntitiesPerNgram);
ArrayList<Orderable<ArrayList<Integer>>> listOfEntitiesPerNgram =
new ArrayList<Orderable<ArrayList<Integer>>>(queueIntoList);
int numberOfNgramsForS = Ngram.getNumberOfNgrams(s, d.getNgramSize());
for (int k = 0; k <= numberOfNgramsForS - min_overlap; k++) {
for (int z = 0; z < listOfEntitiesPerNgram.get(k).getObject().size(); z++) {
int currentMatch = listOfEntitiesPerNgram.get(k).getObject().get(z);
int currentCount = 0;
if (m.containsKey(currentMatch)) {
currentCount = m.get(currentMatch);
} else {
m.put(currentMatch, 0);
}
int newValue = currentCount + 1;
m.put(currentMatch, newValue);
}
}
List<Integer> listOfM_ = new LinkedList<Integer>(m.keySet());
ArrayList<Integer> listOfM = new ArrayList<Integer>(listOfM_);
for (int k = numberOfNgramsForS - min_overlap + 1; k < listOfEntitiesPerNgram.size(); k++) {
for (int z = 0; z < listOfM.size(); z++) {
int currentZ = listOfM.get(z);
// if z is found in the list K
if (find(currentZ, listOfEntitiesPerNgram.get(k).getObject())) {
m.put(currentZ, m.get(currentZ) + 1);
}
if (min_overlap <= m.get(currentZ)) {
listOfMatches.add(currentZ);
}
}
}
return listOfMatches;
}
