def results_relevant_documents_to_one_query(self, query):
print("results_relevant_documents_to_one_query")
if (self.final_dic):
dictionary_parser = Parse.parse_text(query)
dictionary_stemm = Stemmer.stemming(dictionary_parser,
self.stemm_mode)
final_dictionary_query = {}
for term, details in dictionary_stemm.items():
freq = details[0]
final_dictionary_query[term] = freq
result_rank = self.ranker.rank(self.stemm_mode, self.all_document,
self.final_dic, self.path_folder,
final_dictionary_query,
self.semantic_mode)
else:
return []
print("finish")
self.ranker.reset_rank()
return list(result_rank.keys())
def results_relevant_documents(self, queries_dictionary):
print("results_relevant_documents")
results = []
if (self.final_dic):
for number, value in queries_dictionary.items():
# this is the dictionary of all terms in this query
query_dictionary_description = {}
query_title = value[0]
query_description = value[1]
query_narrative = value[2]
# title
parse_title = Parse.parse_text(query_title)
stemm_title = Stemmer.stemming(parse_title, self.stemm_mode)
# narrative - break down sentences and remove not relevant
query_narrative = Parse.parse_query_narrative(query_narrative)
# description + narrative
query_description_narrative = query_narrative + ' ' + query_description
parse_description_narrative = Parse.parse_text(
query_description_narrative)
stemm_description_narrative = Stemmer.stemming(
parse_description_narrative, self.stemm_mode)
# Normalize the number of occurrences of the term
for term, details in stemm_description_narrative.items():
freq = details[0]
if term in self.final_dic:
idf = self.final_dic[term][1]
# new freq with idf
query_dictionary_description[term] = (
self.weight_idf * idf) + (self.weight_df * freq)
number_of_term_in_query = len(query_dictionary_description)
normalized_number_of_results = number_of_term_in_query / self.denominator
normalized_number_of_results = int(
normalized_number_of_results)
# Dictionary with the normalized_number_of_results most common terms
query_dictionary_description_most_common = dict(
Counter(query_dictionary_description).most_common(
normalized_number_of_results))
query_dictionary_description.clear()
# chang dictionary
final_dictionary_query = {}
for term, details in stemm_title.items():
freq = details[0]
final_dictionary_query[term] = freq
# merge dictionary_rank_title and query_dictionary_description_most_common to final_dictionary_query
for term, val in query_dictionary_description_most_common.items(
):
if term in final_dictionary_query:
final_dictionary_query[
term] = final_dictionary_query[term] + val
else:
final_dictionary_query[term] = val
# send the number of occurrences of a word in a document to the ranker
# The ranker return dictionary with [term] = [(d1,tf1),(d2,tf2)...]
result_rank = self.ranker.rank(self.stemm_mode,
self.all_document,
self.final_dic,
self.path_folder,
final_dictionary_query,
self.semantic_mode)
# [ query1 , {term1: [(d1,tf1),(d2,tf2)...] , term2: [(d1,tf1),(d2,tf2)...]} ]
results.append((number, list(result_rank.keys())))
print("finish")
self.ranker.reset_rank()
return results