def score(query, profile, data=None):
if not len(profile.description):
return [-1]
vectorspace = VectorSpace([])
tokenized_description = LowerTokenizer.tokenize(profile.description)
description_vector = vectorspace.vector_for_document(
tokenized_document=tokenized_description,
update=True)
ddg_description = DuckDuckDescription.query(query.lower())
ddg_vector = []
if ddg_description:
ddg_text = ddg_description['description']['text']
ddg_tokenized = LowerTokenizer.tokenize(ddg_text)
ddg_vector = vectorspace.vector_for_document(
tokenized_document=ddg_tokenized,
update=True)
if not len(ddg_vector):
return [-1]
return [cossim(description_vector, ddg_vector)]
def score(query, profile, data=None):
if not len(profile.description):
return [-1]
vectorspace = VectorSpace([])
tokenized_query = LowerTokenizer.tokenize(query)
tokenized_description = LowerTokenizer.tokenize(profile.description)
query_vector = vectorspace.vector_for_document(
tokenized_document=tokenized_query,
update=True)
description_vector = vectorspace.vector_for_document(
tokenized_document=tokenized_description,
update=True)
return [cossim(description_vector, query_vector)]