改进评级用户level #44
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@ -7,6 +7,7 @@
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import pickle
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import math
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from nltk.stem import WordNetLemmatizer # using WordNetLemmatizer for better performance
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from wordfreqCMD import remove_punctuation, freq, sort_in_descending_order, sort_in_ascending_order
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@ -75,12 +76,21 @@ def revert_dict(d):
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return d2
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def stem_words(list_of_words): # It reduces words to the root word (eg. ate, eaten -> eat; leaves, leaf -> leaf)
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wnl = WordNetLemmatizer()
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lst1 = [wnl.lemmatize(w) for w in list_of_words]
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return [wnl.lemmatize(w, pos='v') for w in lst1] # stem by verb: 'v' represents verb
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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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count = 0
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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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#print(lst)
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lst = stem_words(lst) # this call returns a list of words reduced to root word
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#print(lst)
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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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@ -91,7 +101,7 @@ def user_difficulty_level(d_user, d):
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for t in lst3:
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word = t[0]
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hard = t[1]
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#print('WORD %s HARD %4.2f' % (word, hard))
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print('WORD %s HARD %4.2f' % (word, hard))
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geometric = geometric * (hard)
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count += 1
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if count >= 10:
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@zenovio
Thanks. What if a word is not a verb? Does adding the extra Part of Speech option 'v' affect the outcome?
Hui