class Divsi:
svd = None
def __init__(self):
self.helper = DivsiHelper()
self.cnet_normalized = conceptnet_2d_from_db('en')
self.affectwn_raw = get_picklecached_thing('data/divsi/affectiveWNmatrix.pickle')
self.affectWN = self.affectwn_raw.normalized()
self.analogySpace = Blend([self.affectWN, self.cnet_normalized]).svd()
self.EN_NL = get_nl('en')
def load_svd(self, k=100):
svd = self.tensor.svd(k=k)
return svd
def concept_similarity(self, universal_word):
similarity = {}
common = {}
for interesting in self.helper.interestingTags(universal_word):
L = interesting[0]
R = interesting[1]
try:
left = self.analogySpace.weighted_u_vec(L)
right = self.analogySpace.weighted_u_vec(R)
similar = left.hat() * right.hat()
common[L] = self.analogySpace.u_dotproducts_with(left).top_items(10)
common[R] = self.analogySpace.u_dotproducts_with(right).top_items(10)
similarity[similar] = [L, R]
except Exception, E:
pass
sorted_similarity = self.helper.sortDictionary(similarity)
return (sorted_similarity, common)
