public static void Main(string[] args)
{
Console.WriteLine("RWR-based Recommendation (" + DateTime.Now.ToString() + ")\n");
Stopwatch stopwatch = Stopwatch.StartNew();
// Program arguments
dirData = @args[0] + Path.DirectorySeparatorChar; // Path of directory that containes SQLite DB files
string[] methodologyList = args[1].Split(','); // The list of methodologies (csv format; for example: 0,1,8,9,10,11,12 )
int nFolds = int.Parse(args[2]); // Number of folds
int nIterations = int.Parse(args[3]); // Number of iterations for RWR
// Load existing experimental results
if (File.Exists(dirData + "result.dat")) {
StreamReader reader = new StreamReader(dirData + "result.dat");
string line;
while ((line = reader.ReadLine()) != null) {
string[] tokens = line.Split('\t');
if (tokens.Length != 7)
continue;
long egouser = long.Parse(tokens[0]);
int experiment = int.Parse(tokens[1]);
if (!existingResults.ContainsKey(egouser))
existingResults.Add(egouser, new List<int>());
existingResults[egouser].Add(experiment);
}
reader.Close();
}
// Run experiments using multi-threading
string[] sqliteDBs = Directory.GetFiles(dirData, "*.sqlite");
List<Thread> threadList = new List<Thread>();
// Methodology list
methodologies = new List<Methodology>();
foreach (string methodology in methodologyList)
methodologies.Add((Methodology) int.Parse(methodology));
foreach (string dbFile in sqliteDBs) {
Thread thread = new Thread(new ParameterizedThreadStart(Experiment.runKFoldCrossValidation));
ThreadParams parameters = new ThreadParams(dbFile, nFolds, nIterations);
thread.Start(parameters);
threadList.Add(thread);
}
foreach (Thread thread in threadList)
thread.Join();
stopwatch.Stop();
Tools.printExecutionTime(stopwatch);
Console.WriteLine("Finished!");
}
private void runKfoldCrossValidation(object parameters)
{
try
{
Program.semaphore.WaitOne(); // Wait until Semaphore released
// Setting environment for experiments
ThreadParams p = (ThreadParams)parameters;
DataLoader loader = p.loader;
Methodology methodology = p.methodology;
int fold = p.fold;
int nIteration = p.nIteration;
// #1 Core Part: 'EgoNetwork DB' --> 'Graph Strctures(Node, Edge)'
loader.setTrainTestSet(fold);
List <Feature> features = loader.getFeaturesOnMethodology(methodology);
loader.setGraphConfiguration(features);
// Graph Elements: Nodes and edges
Dictionary <int, Node> nodes = loader.allNodes;
Dictionary <int, List <ForwardLink> > edges = loader.allLinksFromNodes;
// Incase: Mention Count(O), Friendship(X)
if (methodology == Methodology.INCL_MENTIONCOUNT ||
methodology == Methodology.INCL_AUTHORSHIP_AND_MENTIONCOUNT ||
methodology == Methodology.INCL_FOLLOWSHIP_ON_THIRDPARTY_AND_MENTIONCOUNT ||
methodology == Methodology.EXCL_FRIENDSHIP)
{
foreach (List <ForwardLink> forwardLinks in edges.Values)
{
for (int i = 0; i < forwardLinks.Count; i++)
{
if (forwardLinks[i].type == EdgeType.FRIENDSHIP)
{
ForwardLink revisedForwardLink = forwardLinks[i];
revisedForwardLink.type = EdgeType.UNDEFINED; // FRIENDSHIP --> UNDEFINED
forwardLinks[i] = revisedForwardLink;
}
}
}
}
// #2 Core Part: 'Graph Strcture(Nodes, Edges)' --> 'PageRank Matrix(2D-ragged array)'
Graph graph = new Graph(nodes, edges);
graph.buildGraph();
// #3 Core Part: Recommendation list(Personalized PageRanking Algorithm)
Recommender recommender = new Recommender(graph);
var recommendation = recommender.Recommendation(0, 0.30f, nIteration); // '0': Ego Node's Index, '0.15f': Damping Factor
// #4 Core Part: Validation - AP(Average Precision)
DataSet testSet = loader.getTestSet();
HashSet <long> egoLikedTweets = testSet.getEgoLikedTweets();
int hit = 0, like = 0;
double AP = 0.0, recall = 0.0; // Average Precision
for (int i = 0; i < recommendation.Count; i++)
{
if (egoLikedTweets.Contains(((Tweet)recommendation[i]).ID))
{
hit += 1;
AP += (double)hit / (i + 1);
}
}
// LIKE
like = (int)egoLikedTweets.Count;
// Average Precision & Recall
if (hit != 0)
{
AP /= hit;
recall = (double)hit / like;
}
else
{
AP = 0.0;
recall = 0.0;
}
// Add current result to final one
lock (Program.locker)
{
foreach (EvaluationMetric metric in this.metrics)
{
switch (metric)
{
case EvaluationMetric.MAP:
this.finalResult[metric] += AP;
break;
case EvaluationMetric.RECALL:
this.finalResult[metric] += recall;
break;
case EvaluationMetric.LIKE:
this.finalResult[metric] += like;
break;
case EvaluationMetric.HIT:
this.finalResult[metric] += hit;
break;
}
}
}
}
catch (FileNotFoundException e)
{
Console.WriteLine(e);
}
finally
{
Program.semaphore.Release();
}
}
/*******************************************************************************/
/***************************** Primary Methods *********************************/
/*******************************************************************************/
public bool startPersonalizedPageRank(int nFold, int nIteration)
{
try
{
// Do experiments for each methodology
foreach (Methodology methodology in Program.methodologies)
{
// Get ego user's ID and his like count
long egoUser = long.Parse(Path.GetFileNameWithoutExtension(this.dbPath));
// Check if this experiment has ever been performed earlier
int m = (int)methodology;
if (Program.existingResults.ContainsKey(egoUser) && Program.existingResults[egoUser].Contains(m))
{
lock (Program.locker)
{
Console.WriteLine("Ego network(" + egoUser + "): done on experiment #" + m);
}
return(false);
}
// Final result to put the experimental result per fold together
this.finalResult = new Dictionary <EvaluationMetric, double>(); // <'HIT(0)', double> or <'AVGPRECISION(1)', double>
foreach (EvaluationMetric metric in Enum.GetValues(typeof(EvaluationMetric)))
{
this.finalResult.Add(metric, 0d); // Initialization
}
// Need to avoid the following error: "Collection was modified; enumeration operation may not execute"
metrics = new List <EvaluationMetric>(this.finalResult.Keys);
// K-Fold Cross Validation
List <Thread> threadList = new List <Thread>(); // 'Thread': Standard Library Class
for (int fold = 0; fold < 1; fold++) // // One fold to One thread
{
// Load graph information from database and then configurate the graph
DataLoader loader = new DataLoader(this.dbPath);
loader.setEgoNetwork();
loader.setEgoTimeline();
loader.splitTimelineToKfolds(nFold);
// |Friend|
this.numOfFriend = loader.getNumOfFriend();
Thread thread = new Thread(new ParameterizedThreadStart(runKfoldCrossValidation)); // Core Part
ThreadParams parameters = new ThreadParams(loader, methodology, fold, nIteration); // 'ThreadParams': defined in 'Experiment.cs'
thread.Start(parameters);
threadList.Add(thread);
}
// Synchronization: Wait until threads be terminated
foreach (Thread thread in threadList)
{
thread.Join();
}
// Result: <Ego ID>\t<Experi Code>\t<N-fold>\t<iteration>\t<MAP>\t<Recall>\t<|LIKE|>\t<|HIT|>\t<|Friend|>
Program.logger.Write(egoUser + "\t" + (int)methodology + "\t" + nFold + "\t" + nIteration);
foreach (EvaluationMetric metric in metrics)
{
switch (metric)
{
case EvaluationMetric.MAP:
Program.logger.Write("\t{0:F15}", (finalResult[metric] / 1));
break;
case EvaluationMetric.RECALL:
Program.logger.Write("\t{0:F15}", (finalResult[metric] / 1));
break;
case EvaluationMetric.LIKE:
Program.logger.Write("\t" + (finalResult[metric]));
break;
case EvaluationMetric.HIT:
Program.logger.Write("\t" + (finalResult[metric]));
break;
}
}
Program.logger.Write("\t" + this.numOfFriend);
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
return(true);
}
/*******************************************************************************/
/***************************** Primary Methods *********************************/
/*******************************************************************************/
public bool startPersonalizedPageRank(int nFold, int nIteration)
{
try
{
// Do experiments for each methodology
foreach (Methodology methodology in Program.methodologies)
{
// Get ego user's ID and his like count
long egoUser = long.Parse(Path.GetFileNameWithoutExtension(this.dbPath));
// Check if this experiment has ever been performed earlier
int m = (int)methodology;
if (Program.existingResults.ContainsKey(egoUser) && Program.existingResults[egoUser].Contains(m))
{
lock (Program.locker)
{
Console.WriteLine("Ego network(" + egoUser + "): done on experiment #" + m);
}
return false;
}
// Final result to put the experimental result per fold together
this.finalResult = new Dictionary<EvaluationMetric, double>(); // <'HIT(0)', double> or <'AVGPRECISION(1)', double>
foreach (EvaluationMetric metric in Enum.GetValues(typeof(EvaluationMetric)))
this.finalResult.Add(metric, 0d); // Initialization
// Need to avoid the following error: "Collection was modified; enumeration operation may not execute"
metrics = new List<EvaluationMetric>(this.finalResult.Keys);
// K-Fold Cross Validation
List<Thread> threadList = new List<Thread>(); // 'Thread': Standard Library Class
for (int fold = 0; fold < 1; fold++) // // One fold to One thread
{
// Load graph information from database and then configurate the graph
DataLoader loader = new DataLoader(this.dbPath);
loader.setEgoNetwork();
loader.setEgoTimeline();
loader.splitTimelineToKfolds(nFold);
// |Friend|
this.numOfFriend = loader.getNumOfFriend();
Thread thread = new Thread(new ParameterizedThreadStart(runKfoldCrossValidation)); // Core Part
ThreadParams parameters = new ThreadParams(loader, methodology, fold, nIteration); // 'ThreadParams': defined in 'Experiment.cs'
thread.Start(parameters);
threadList.Add(thread);
}
// Synchronization: Wait until threads be terminated
foreach (Thread thread in threadList)
thread.Join();
// Result: <Ego ID>\t<Experi Code>\t<N-fold>\t<iteration>\t<MAP>\t<Recall>\t<|LIKE|>\t<|HIT|>\t<|Friend|>
Program.logger.Write(egoUser + "\t" + (int)methodology + "\t" + nFold + "\t" + nIteration);
foreach (EvaluationMetric metric in metrics)
{
switch (metric)
{
case EvaluationMetric.MAP:
Program.logger.Write("\t{0:F15}", (finalResult[metric] / 1));
break;
case EvaluationMetric.RECALL:
Program.logger.Write("\t{0:F15}", (finalResult[metric] / 1));
break;
case EvaluationMetric.LIKE:
Program.logger.Write("\t" + (finalResult[metric]));
break;
case EvaluationMetric.HIT:
Program.logger.Write("\t" + (finalResult[metric]));
break;
}
}
Program.logger.Write("\t" + this.numOfFriend);
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
return true;
}
