def common_relations(concept_strs):
concepts = [Concept.get(concept_str,'en') for concept_str in concept_strs]
set_relations = [set([ast.concept2.text for ast in concept.get_assertions_forward()[:20] \
if ast.relation.name == "IsA"]) for concept in concepts]
all_sets = []
for set_relation in set_relations:
concepts = []
for concept in set_relation:
concepts += concept.split(" ")
all_sets.append(set(concepts))
# common = set.intersection(*all_sets)
count_relations = Counter(set_to_all_list(set_relations))
print count_relations
commonality = count_relations.most_common(1)[0][1]/float(len(set_relations))
print "attr, common values: ", count_relations.most_common(1)[0][0], ", ", commonality
# If noun concepts worked reliability in NLTK:
# noun_concepts = [set([getNoun(concept) for concept in set_relation]) for set_relation in set_relations]
# print noun_concepts
return commonality
def doBFS(inpC1str,inpC2str,q): # Convert strings to concepts in ConceptNet inpC1 = Concept.get(inpC1str,'en') inpC2 = Concept.get(inpC2str,'en') exp = [inpC1] print "added inpc1 to exp" q += [exp] print "exp enqueued" while q!=[]: tmp = q[0] q = q[1:] last_node = tmp[len(tmp)-1] print tmp # print "last node ", last_node # print "lasr node text", last_node.text # print "inp2 text", inpC2.text if last_node.text == inpC2.text or last_node.text in inpC2.text: print "valid path done, found ", tmp print "length of path is ", len(tmp)-1 return len(tmp[1:]) for ast in last_node.get_assertions()[:10]: print "assertion is ", ast print "corresponding relation name is ", ast.relation.name searchC21 = Concept.get(ast.concept1.text, 'en') searchC22 = Concept.get(ast.concept2.text, 'en') if searchC21.text == last_node.text: searchC2 = searchC22 else: searchC2 = searchC21 # print "searchc2 is ", searchC2 if searchC2 not in tmp: # print "searched c2" new = [] new = tmp + [searchC2] q += [new]
def common_noun_relations(concept_strs):
concepts = [Concept.get(concept_str,'en') for concept_str in concept_strs]
print concepts
set_relations = [set([ast.concept2.text for ast in concept.get_assertions_forward()[:20] \
if ast.relation.name == "IsA"]) for concept in concepts]
print set_relations
all_nouns = []
for set_relation in set_relations:
noun_concepts = []
for concept in set_relation:
noun_concept = getNoun(concept)
if noun_concept != []:
noun_concepts += noun_concept
all_nouns += [noun_concepts]
print all_nouns
import sys
from Queue import PriorityQueue
from conceptnet.models import Concept
# Take input from user for quick searches
sys.stderr.write("\x1b[2J\x1b[H")
for arg in sys.argv[1:]:
argConcept = Concept.get(arg,'en')
print "concept ", arg
for ass in argConcept.get_assertions():
print ass
print len(argConcept.get_assertions())
# Testing
testC1 = Concept.get('bond', 'en')
for ass in testC1.get_assertions():
print ass
print len(testC1.get_assertions())
print "------------------------------"
testC2 = Concept.get('bark', 'en')
for ass in testC2.get_assertions()[:10]:
print ass
# do BFS
def doBFS(inpC1str,inpC2str,q):
# Convert strings to concepts in ConceptNet
inpC1 = Concept.get(inpC1str,'en')
inpC2 = Concept.get(inpC2str,'en')
def getConcept(arg, lang='en'):
try:
argConcept = Concept.get(arg,'en')
except:
argConcept = None
return argConcept
from conceptnet.models import Concept
dog = Concept.get('dog', 'en')
for fwd in dog.get_assertions_forward()[:20]:
print fwd
from conceptnet.models import Concept
import os
objectsList = [
"cylinder"
] #["office","room","corridor","toilet","door","window","exit","table","chair","fire extinguisher","socket","power","printer","emergency exit","closet","book","chair","bench","trash bin","plant","hydrant","printer","professor"]
if (os.path.exists("conceptnetPropertyList.txt")):
os.remove("conceptnetPropertyList.txt")
file_name = open('conceptnetPropertyList.txt', 'a')
for i in xrange(len(objectsList)):
print "retrieving predicates of %s from concpetNet" % objectsList[i]
file_name.write("#### OBJECT %s: %s\n" % (i + 1, objectsList[i]))
try:
obj = Concept.get('%s' % objectsList[i], 'en')
for fwd in obj.get_assertions():
#if "Property" in "%s"%fwd:
file_name.write("%s\n" % fwd)
file_name.write("\n")
except:
print "could not retrieve anything for %s from conceptNet" % objectsList[
i]
from conceptnet.models import Concept
import os
objectsList = ["cylinder"]#["office","room","corridor","toilet","door","window","exit","table","chair","fire extinguisher","socket","power","printer","emergency exit","closet","book","chair","bench","trash bin","plant","hydrant","printer","professor"]
if(os.path.exists("conceptnetPropertyList.txt")):
os.remove("conceptnetPropertyList.txt")
file_name = open('conceptnetPropertyList.txt', 'a')
for i in xrange(len(objectsList)):
print "retrieving predicates of %s from concpetNet"%objectsList[i]
file_name.write("#### OBJECT %s: %s\n"%(i+1,objectsList[i]))
try:
obj = Concept.get('%s'%objectsList[i], 'en')
for fwd in obj.get_assertions():
#if "Property" in "%s"%fwd:
file_name.write("%s\n"%fwd)
file_name.write("\n")
except:
print "could not retrieve anything for %s from conceptNet"%objectsList[i]
self.reload()
print "Loading Tensor"
fl = file(self.file_name, 'rb')
tensor = pickle.load(fl)
fl.close()
return tensor
if __name__ == '__main__':
#--------Some example concepts to use
#print "Getting test concepts"
dog = Concept.get('dog', 'en').text
leash = Concept.get('leash', 'en').text
umb = Concept.get('umbrella', 'en').text
cat = Concept.get('cat', 'en').text
#pets = [dog, cat]
#temple = Concept.get('temple', 'en').text
# hindu = Concept.get('hindu', 'en').text
# asia = Concept.get('asia', 'en').text
# nepal = Concept.get('Nepal', 'en').text
# spain = Concept.get('Spain', 'en').text
#test = [temple, asia, nepal]
#----------Load Tensor
tensor = LoadTensor().load()
#Checks to see if the pickle file already exists
if (os.path.exists(self.file_name) == False):
#If not, reloads pickle
self.reload()
print "Loading Tensor"
fl = file(self.file_name, 'rb')
tensor = pickle.load(fl)
fl.close()
return tensor
if __name__ == '__main__':
#--------Some example concepts to use
#print "Getting test concepts"
dog = Concept.get('dog', 'en').text
leash = Concept.get('leash', 'en').text
umb = Concept.get('umbrella', 'en').text
cat = Concept.get('cat', 'en').text
#pets = [dog, cat]
#temple = Concept.get('temple', 'en').text
# hindu = Concept.get('hindu', 'en').text
# asia = Concept.get('asia', 'en').text
# nepal = Concept.get('Nepal', 'en').text
# spain = Concept.get('Spain', 'en').text
#test = [temple, asia, nepal]
#----------Load Tensor
tensor = LoadTensor().load()