public void buildGraph()
{
for (int i = 0; i < nodes.Count; i++)
{
ForwardLink[] forwardLinks = null;
if (edges.ContainsKey(i))
{
// Count the number of explicit(defined) forwardlinks
int nExplicitLinks = 0;
foreach (ForwardLink forwardLink in edges[i]) // edges[i]: all forward links of 'i'th node
{
if (forwardLink.type != EdgeType.UNDEFINED)
{
nExplicitLinks += 1;
}
}
// The graph should consider only explicit forward links
if (nExplicitLinks > 0)
{
// Make ragged array of forward links for a node: To avoid 'Sparse Matrix'
forwardLinks = new ForwardLink[nExplicitLinks];
// Calculate sum of weights of the given source node (entry.Key)
int idx = 0;
double sumWeights = 0;
foreach (ForwardLink link in edges[i]) // edges[i]: all forward links of 'i'th node
{
if (link.type != EdgeType.UNDEFINED)
{
// Add link to array and its weight to summation
forwardLinks[idx++] = link;
sumWeights += link.weight;
}
}
// Adjust weights whose sum is 1
for (int f = 0; f < nExplicitLinks; f++)
{
forwardLinks[f].weight /= sumWeights;
}
}
}
// Dangling node: Add virtual links to all nodes(include itself)
else
{
forwardLinks = new ForwardLink[nodes.Count];
double weight = 1.0 / nodes.Count;
for (int j = 0; j < nodes.Count; j++)
{
ForwardLink virtualLink = new ForwardLink(j, EdgeType.VIRTUAL, weight);
forwardLinks[j] = virtualLink;
}
}
// Add filterd forward links of 'i'th node
matrix.Add(forwardLinks);
}
}
public void buildGraph()
{
for (int i = 0; i < nodes.Count; i++)
{
ForwardLink[] forwardLinks = null;
if (edges.ContainsKey(i))
{
// Count the number of explicit(defined) forwardlinks
int nExplicitLinks = 0;
foreach (ForwardLink forwardLink in edges[i]) // edges[i]: all forward links of 'i'th node
{
if (forwardLink.type != EdgeType.UNDEFINED)
nExplicitLinks += 1;
}
// The graph should consider only explicit forward links
if (nExplicitLinks > 0)
{
// Make ragged array of forward links for a node: To avoid 'Sparse Matrix'
forwardLinks = new ForwardLink[nExplicitLinks];
// Calculate sum of weights of the given source node (entry.Key)
int idx = 0;
double sumWeights = 0;
foreach (ForwardLink link in edges[i]) // edges[i]: all forward links of 'i'th node
{
if (link.type != EdgeType.UNDEFINED)
{
// Add link to array and its weight to summation
forwardLinks[idx++] = link;
sumWeights += link.weight;
}
}
// Adjust weights whose sum is 1
for (int f = 0; f < nExplicitLinks; f++)
forwardLinks[f].weight /= sumWeights;
}
}
// Dangling node: Add virtual links to all nodes(include itself)
else
{
forwardLinks = new ForwardLink[nodes.Count];
double weight = 1.0 / nodes.Count;
for (int j = 0; j < nodes.Count; j++)
{
ForwardLink virtualLink = new ForwardLink(j, EdgeType.VIRTUAL, weight);
forwardLinks[j] = virtualLink;
}
}
// Add filterd forward links of 'i'th node
matrix.Add(forwardLinks);
}
}
public void addLink(int indexSourceNode, int indexNewTargetNode, EdgeType type, double weight)
{
// Create new link structure for source node
if (!allLinksFromNodes.ContainsKey(indexSourceNode))
{
allLinksFromNodes.Add(indexSourceNode, new List <ForwardLink>());
}
// Check already a link(equal type) between source and target nodes
foreach (ForwardLink forwardLink in allLinksFromNodes[indexSourceNode])
{
if (forwardLink.targetNode == indexNewTargetNode && forwardLink.type == type)
{
return;
}
}
// Create a new link between source and target nodes
ForwardLink link = new ForwardLink(indexNewTargetNode, type, weight);
allLinksFromNodes[indexSourceNode].Add(link);
nLinks += 1;
}
private void runKfoldCrossValidation(object parameters)
{
try
{
// Setting environment for experiments
kFoldThreadParameter p = (kFoldThreadParameter)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);
if (Program.isValidTrainSet == false)
{
return;
}
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, 0.15f, 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 (kFoldLocker)
{
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
{
kFoldSemaphore.Release();
}
}
public void addLink(int indexSourceNode, int indexNewTargetNode, EdgeType type, double weight)
{
// Create new link structure for source node
if (!allLinksFromNodes.ContainsKey(indexSourceNode))
allLinksFromNodes.Add(indexSourceNode, new List<ForwardLink>());
// Check already a link(equal type) between source and target nodes
foreach (ForwardLink forwardLink in allLinksFromNodes[indexSourceNode])
{
if (forwardLink.targetNode == indexNewTargetNode && forwardLink.type == type)
return;
}
// Create a new link between source and target nodes
ForwardLink link = new ForwardLink(indexNewTargetNode, type, weight);
allLinksFromNodes[indexSourceNode].Add(link);
nLinks += 1;
}
public void addLink(int idxSourceNode, int idxTargetNode, EdgeType type, double weight)
{
if (!allLinks.ContainsKey(idxSourceNode))
allLinks.Add(idxSourceNode, new List<ForwardLink>());
bool exist = false;
foreach (ForwardLink forwardLink in allLinks[idxSourceNode]) {
if (forwardLink.targetNode == idxTargetNode && forwardLink.type == type) {
exist = true;
break;
}
}
if (exist == false) {
ForwardLink link = new ForwardLink(idxTargetNode, type, weight);
allLinks[idxSourceNode].Add(link);
nLinks += 1;
}
}