/**
* For each item, calculate the sequence id of sequences containing that item
*
* @param database the current sequence database
* @return Map of items to sequence IDs that contains each item
*/
private Map<Integer, Set<Integer>> findSequencesContainingItems(SequenceDatabase database) {
// We use a map to store the sequence IDs where an item appear
// Key : item Value : a set of sequence IDs
Map<Integer, Set<Integer>> mapSequenceID =
new HashMap<
Integer,
Set<
Integer>>(); // pour conserver les ID des séquences: <Id Item, Set d'id de
// séquences>
// for each sequence
for (Sequence sequence : database.getSequences()) {
// for each itemset in that sequence
for (List<Integer> itemset : sequence.getItemsets()) {
// for each item
for (Integer item : itemset) {
// get the set of sequence ids for that item
Set<Integer> sequenceIDs = mapSequenceID.get(item);
if (sequenceIDs == null) {
// if null create a new set
sequenceIDs = new HashSet<Integer>();
mapSequenceID.put(item, sequenceIDs);
}
// add the current sequence id to this set
sequenceIDs.add(sequence.getId());
}
}
}
return mapSequenceID;
}
/**
* This is the main method for the MaxSP algorithm.
*
* @param database a sequence database
* @throws IOException exception if some error occurs while writing the output file.
*/
private void maxSP(SequenceDatabase database, String outputFilePath) throws IOException {
// if the user want to keep the result into memory
if (outputFilePath == null) {
writer = null;
patterns = new SequentialPatterns("FREQUENT SEQUENTIAL PATTERNS");
} else { // if the user want to save the result to a file
patterns = null;
writer = new BufferedWriter(new FileWriter(outputFilePath));
}
// The algorithm first scan the database to find all frequent items
// The algorithm note the sequences in which these items appear.
// This is stored in a map: Key: item Value : IDs of sequences containing the item
Map<Integer, Set<Integer>> mapSequenceID = findSequencesContainingItems(database);
// WE CONVERT THE DATABASE TO A PSEUDO-DATABASE, AND REMOVE
// THE ITEMS OF SIZE 1 THAT ARE NOT FREQUENT, SO THAT THE ALGORITHM
// WILL NOT CONSIDER THEM ANYMORE.
// we create a database
initialDatabase = new HashMap<Integer, PseudoSequenceBIDE>();
// for each sequence of the original database
for (Sequence sequence : database.getSequences()) {
// we make a copy of the sequence while removing infrequent items
Sequence optimizedSequence = sequence.cloneSequenceMinusItems(mapSequenceID, minsuppAbsolute);
if (optimizedSequence.size() != 0) {
// if this sequence has size >0, we add it to the new database
initialDatabase.put(sequence.getId(), new PseudoSequenceBIDE(optimizedSequence, 0, 0));
}
}
// For each frequent item
loop1:
for (Entry<Integer, Set<Integer>> entry : mapSequenceID.entrySet()) {
// if the item is frequent
if (entry.getValue().size() >= minsuppAbsolute) {
// build the projected database with this item
Integer item = entry.getKey();
List<PseudoSequenceBIDE> projectedContext =
buildProjectedContextSingleItem(item, initialDatabase, false, entry.getValue());
// Create the prefix with this item
SequentialPattern prefix = new SequentialPattern();
prefix.addItemset(new Itemset(item));
// set the sequence IDS of this prefix
prefix.setSequenceIDs(entry.getValue());
// variable to store the largest support of patterns
// that will be found starting with this prefix
if (projectedContext.size() >= minsuppAbsolute) {
int successorSupport = 0;
// if(!checkBackScanPruning(prefix, entry.getValue())) {
successorSupport = recursion(prefix, projectedContext); // récursion;
// }
// else
// {
// System.out.println("back scan pruned " + prefix);
// }
// Finally, because this prefix has support > minsup
// and passed the backscan pruning,
// we check if it has no sucessor with support >= minsup
// (a forward extension)
// IF no forward extension
if (successorSupport < minsuppAbsolute) { // ######### MODIFICATION ####
// IF there is also no backward extension
if (!checkBackwardExtension(prefix, entry.getValue())) {
// the pattern is closed and we save it
savePattern(prefix);
}
}
} else {
if (!checkBackwardExtension(prefix, entry.getValue())) {
// the pattern is closed and we save it
savePattern(prefix);
}
}
}
}
// check the memory usage for statistics
MemoryLogger.getInstance().checkMemory();
}