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Draft for supporting DBLP KG#4

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Reham-Osama wants to merge 1 commit into
aorogat:mainfrom
CoDS-GCS:main
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Draft for supporting DBLP KG#4
Reham-Osama wants to merge 1 commit into
aorogat:mainfrom
CoDS-GCS:main

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@Reham-Osama
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I added an explanation for why I made my changes within the code.

I have a couple of questions related to these changes

  1. When I ran the system on DBPedia KG it took around 13 hours to finish, but with the code here DBLP took only 7 mins, is that variance in the processing time expected ?
  2. The output files contain a lot of generated boolean questions, is there a way to include boolean questions but limit their number?
  3. I understood that there are two offsets that controls the node types to use and the seed nodes, what is the range of these values, and What are their expected effect?
    1. RandomSeedGenerator.addBranchesFromList (Line 102): Is this offset for choosing which node types to include
    2. RandomSeedGenerator.addBranchs (Line 125): Is this offset for choosing nodes that belongs to one node type.

predicate.setPredicateContext(new PredicateContext(result.getString("Context_Subject"), result.getString("Context_Object"), 0));
predicate.setWeight(result.getLong("ContextWeight"));
if (!predicate.getPredicateURI().contains("#")) {
// if (!predicate.getPredicateURI().contains("#")) {
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I made this change because most of the dblp predicates contains #, Do you think that this will affect the overall performance?

int benchmarkNumber = 37;

for (int j = 480; j < 10000; j = j + 10) {
for (int j = 0; j < 10000; j = j + 10) {
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I changed this to be able to have some results on DBLP. Without it, I was receiving no output files
Will this affect the performance or the output ?

}
}

private ArrayList<VariableSet> filterResult( ArrayList<VariableSet> result) {
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I added this method because querying the RDF engine using the unwantedPropertiesString returned no results at all, so I returned all predicates and removed the unneeded using this method
I called it from getPredicateList_EntityObjects

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