def doc_keywords():
category = request.form['category']
word = request.form['word'].encode('utf-8').strip()
in_type = request.form['type']
f_text = input_doc_str(in_type)
inference_engine_wrapper = InferenceEngineWrapper(get_model_dir(category),
get_lda_conf())
seg_list = inference_engine_wrapper.tokenize(f_text)
items = inference_engine_wrapper.cal_keywords_similarity(
word, ' '.join(seg_list))
return json_format(items)
def doc_keywords_plus():
category = request.form['category']
#word = request.form['word'].encode('utf-8').strip()
in_type = request.form['type']
f_text = input_doc_str(in_type)
inference_engine_wrapper = InferenceEngineWrapper(get_model_dir(category),
get_lda_conf())
seg_list = inference_engine_wrapper.tokenize(f_text)
items = {}
for x, w in jieba.analyse.extract_tags(f_text, withWeight=True):
result = inference_engine_wrapper.cal_keywords_similarity(
x.encode('utf-8').strip(), ' '.join(seg_list))
items.update(result)
return json_format(items)
# found in the LICENSE file.
import sys
from familia_wrapper import InferenceEngineWrapper
if sys.version_info < (3, 0):
input = raw_input
if __name__ == '__main__':
if len(sys.argv) < 3:
sys.stderr.write("Usage:python {} {} {}.\n".format(
sys.argv[0], "model_dir", "conf_file"))
exit(-1)
# 获取参数
model_dir = sys.argv[1]
conf_file = sys.argv[2]
# 创建InferenceEngineWrapper对象
inference_engine_wrapper = InferenceEngineWrapper(model_dir, conf_file)
while True:
# 输入两个长文本
words = input("Enter Keywords: ").strip()
doc = input("Enter Document: ").strip()
seg_list = inference_engine_wrapper.tokenize(doc)
items = inference_engine_wrapper.cal_keywords_similarity(
words, ' '.join(seg_list))
# 打印结果
print('----------------------------')
for item in items:
print(item[0] + '\t' + str(item[1]))
# Copyright (c) 2017, Baidu.com, Inc. All Rights Reserved
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import sys
from familia_wrapper import InferenceEngineWrapper
if sys.version_info < (3, 0):
input = raw_input
if __name__ == '__main__':
if len(sys.argv) < 3:
sys.stderr.write("Usage:python {} {} {}.\n".format(
sys.argv[0], "model_dir", "conf_file"))
exit(-1)
# 获取参数
model_dir = sys.argv[1]
conf_file = sys.argv[2]
# 创建InferenceEngineWrapper对象
inference_engine_wrapper = InferenceEngineWrapper(model_dir, conf_file)
while True:
# 输入两个长文本
words = input("Enter Keywords: ").strip()
doc = input("Enter Document: ").strip()
items = inference_engine_wrapper.cal_keywords_similarity(words, doc)
# 打印结果
print('----------------------------')
for item in items:
print item[0] + '\t' + str(item[1])