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Author | SHA1 | Date |
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包月琳 | 4da4ec415f |
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@ -7,6 +7,9 @@
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import pickle
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import math
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from nltk import word_tokenize,pos_tag
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from nltk.corpus import wordnet
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from nltk.stem import WordNetLemmatizer
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from wordfreqCMD import remove_punctuation, freq, sort_in_descending_order, sort_in_ascending_order
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@ -74,6 +77,34 @@ def revert_dict(d):
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d2[date].append(k)
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return d2
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def get_wordnet_pos(tag):
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if tag.startswith('J'):
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return wordnet.ADJ
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elif tag.startswith('V'):
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return wordnet.VERB
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elif tag.startswith('N'):
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return wordnet.NOUN
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elif tag.startswith('R'):
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return wordnet.ADV
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else:
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return None
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def combine_words_through_grammar(lst,d): #通过语法合并同一单词的不同形式
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lst1=lst
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tagged_sent = pos_tag(lst) # 获取单词词性
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print(tagged_sent)
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wnl = WordNetLemmatizer()
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lemmas_sent = []
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for tag in tagged_sent:
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wordnet_pos = get_wordnet_pos(tag[1]) or wordnet.NOUN
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lemmas_sent.append(wnl.lemmatize(tag[0], pos=wordnet_pos)) # 词形还原
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for index,change_word in enumerate(lemmas_sent):
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for word2 in d:
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if change_word==word2:
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lst1[index]=change_word
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return lst1
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def user_difficulty_level(d_user, d):
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d_user2 = revert_dict(d_user) # key is date, and value is a list of words added in that date
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@ -81,6 +112,7 @@ def user_difficulty_level(d_user, d):
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geometric = 1
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for date in sorted(d_user2.keys(), reverse=True): # most recently added words are more important while determining user's level
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lst = d_user2[date] # a list of words
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lst=combine_words_through_grammar(lst,d) #合并单词的不同形式
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lst2 = [] # a list of tuples, (word, difficulty level)
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for word in lst:
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if word in d:
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