public static SequenceDatabase load(List<List<Integer>>[] aryListDB) {
SequenceDatabase db = new SequenceDatabase();
Sequence seq;
for (int i = 0; i < aryListDB.length; i++) {
if (aryListDB[i] != null) {
seq = new Sequence(i);
for (List<Integer> itemset : aryListDB[i]) {
seq.addItemset(itemset);
}
db.addSequence(seq);
}
}
return db;
}
public static void main(String[] arg) throws IOException {
// Load a sequence database
SequenceDatabase sequenceDatabase = new SequenceDatabase();
sequenceDatabase.loadFile(fileToPath("contextPrefixSpan.txt"));
sequenceDatabase.print();
int minsup = 2; // we use a minsup of 2 sequences (50 % of the database size)
AlgoBIDEPlus algo = new AlgoBIDEPlus(); //
// execute the algorithm
algo.runAlgorithm(sequenceDatabase, "C://patterns//closed_sequential_patterns.txt", minsup);
algo.printStatistics(sequenceDatabase.size());
}
/**
* 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;
}
public static void main(String[] arg) throws IOException {
String outputPath = ".//output.txt";
// Load a sequence database
SequenceDatabase sequenceDatabase = new SequenceDatabase();
sequenceDatabase.loadFile(fileToPath("contextPrefixSpan.txt"));
// print the database to console
sequenceDatabase.print();
// Create an instance of the algorithm with minsup = 50 %
AlgoPrefixSpan algo = new AlgoPrefixSpan();
int minsup = 2; // we use a minimum support of 2 sequences.
// execute the algorithm
algo.runAlgorithm(sequenceDatabase, outputPath, minsup);
algo.printStatistics(sequenceDatabase.size());
}
public static void main(String[] arg) throws IOException {
// Load a sequence database
SequenceDatabase sequenceDatabase = new SequenceDatabase();
sequenceDatabase.loadFile(fileToPath("contextPrefixSpan.txt"));
sequenceDatabase.print();
// Create an instance of the algorithm
AlgoMaxSP algo = new AlgoMaxSP();
// if you set the following parameter to true, the sequence ids of the sequences where
// each pattern appears will be shown in the result
boolean showSequenceIdentifiers = false;
// execute the algorithm
SequentialPatterns patterns = algo.runAlgorithm(sequenceDatabase, null, 2);
algo.printStatistics(sequenceDatabase.size());
patterns.printFrequentPatterns(sequenceDatabase.size(), showSequenceIdentifiers);
}
public static void main(String[] arg) throws IOException {
// Load a sequence database
SequenceDatabase sequenceDatabase = new SequenceDatabase();
sequenceDatabase.loadFile(fileToPath("contextPrefixSpan.txt"));
// sequenceDatabase.print();
int minsup = 2; // we use a minsup of 2 sequences (50 % of the database size)
AlgoMaxSP algo = new AlgoMaxSP(); //
// if you set the following parameter to true, the sequence ids of the sequences where
// each pattern appears will be shown in the result
algo.setShowSequenceIdentifiers(false);
// execute the algorithm
algo.runAlgorithm(sequenceDatabase, ".//output.txt", minsup);
algo.printStatistics(sequenceDatabase.size());
}
public static void main(String[] arg) throws IOException {
// Load a sequence database
SequenceDatabase sequenceDatabase = new SequenceDatabase();
sequenceDatabase.loadFile(fileToPath("contextPrefixSpan.txt"));
// print the database to console
sequenceDatabase.print();
// Create an instance of the algorithm
AlgoFSGP algo = new AlgoFSGP();
// algo.setMaximumPatternLength(3);
// execute the algorithm with minsup = 50 %
boolean performPruning = true; // to activate pruning of search space
List<SequentialPattern> patterns = algo.runAlgorithm(sequenceDatabase, 0.5, performPruning);
algo.printStatistics(sequenceDatabase.size());
System.out.println(" == PATTERNS ==");
for (SequentialPattern pattern : patterns) {
System.out.println(pattern + " support : " + pattern.getAbsoluteSupport());
}
}
public static SequenceDatabase load(String strDB) {
SequenceDatabase db = new SequenceDatabase();
Sequence seq;
List<Integer> iset;
String[] sequences = strDB.split("\\n");
String[] itemsets;
String[] items;
for (String seqStr : sequences) {
itemsets = seqStr.trim().split("\\s*\\|\\s*");
seq = new Sequence(Integer.valueOf(itemsets[0]));
for (int i = 1; i < itemsets.length; i++) {
items = itemsets[i].split("\\s+");
iset = new ArrayList<Integer>();
for (String itemStr : items) {
iset.add(Integer.valueOf(itemStr));
}
seq.addItemset(iset);
}
db.addSequence(seq);
}
return db;
}
/**
* This is the main method for the BIDE+ algorithm.
*
* @param database a sequence database
* @throws IOException exception if some error occurs while writing the output file.
*/
private void bide(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.
// OPTIMIZATION Create COOC MAP
// coocMapBefore = new HashMap<Integer, Map<Integer,
// Integer>>(mapSequenceID.entrySet().size());
// we create a database
initialDatabase = new ArrayList<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.add(new PseudoSequenceBIDE(optimizedSequence, 0, 0));
}
// // update COOC map
// HashSet<Integer> alreadySeen = new HashSet<Integer>();
// for(List<Integer> itemset : optimizedSequence.getItemsets()) {
// for(Integer item : itemset) {
// Map<Integer, Integer> mapCoocItem = coocMapBefore.get(item);
// if(mapCoocItem == null) {
// mapCoocItem = new HashMap<Integer, Integer>();
// coocMapBefore.put(item, mapCoocItem);
// }
// for(Integer itemSeen : alreadySeen) {
// if(itemSeen != item) {
// Integer frequency = mapCoocItem.get(itemSeen);
// if(frequency == null) {
// mapCoocItem.put(itemSeen, 1);
// }else {
// mapCoocItem.put(itemSeen, frequency+1);
// }
// }
// }
// alreadySeen.add(item);
// }
// }
}
// For each frequent item
loop1:
for (Entry<Integer, Set<Integer>> entry : mapSequenceID.entrySet()) {
// if the item is frequent
if (entry.getValue().size() >= minsuppAbsolute) {
// Map<Integer, Integer> mapCoocItem = coocMapBefore.get(entry.getKey());
// if(mapCoocItem != null) {
// for(Integer supportCoocBefore : mapCoocItem.values()) {
// if(supportCoocBefore >= entry.getValue().size()) {
// continue loop1;
// }
// }
// }
// 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;
}
// 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 != entry.getValue().size()) { // ######### 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();
}