查找输入字符串与 Python 中的元组列表的所有可能匹配项（在任何 order/sequence 中）

Question

我想将输入字符串与元组列表进行匹配，并从元组列表中找出前 N 个接近的匹配项。元组列表有大约 2000 个项目。我面临的问题是我使用了 fuzzywuzzy process.extract method 但它 returns 大量具有相同置信度分数的元组。比赛质量也不好。我想做的是根据我的输入获取所有匹配项（顺序不重要）

Example: 
input string: 'fruit apple'
    
List of tuples = [('apple fruit', 91), ('the fruit is an apple', 34), ('banana apple', 78), ('guava tree', 11), ('delicious apple', 88)]

从这里我想从包含单词 'fruit apple' 的字符串列表中以任意顺序查找所有字符串。

Expected output:
[('apple fruit', 91), ('the fruit is an apple', 34)]

我知道 fuzzywuzzy，它只有 1 行代码，但问题是当要检查的元组列表的大小非常大时，fuzzywuzzy 会为不相关的项目分配相同的置信度分数。

附上目前试过的代码供参考：

def preprocessing(fruit):
    stop_words = stopwords.words('english')
    fruit_string = re.sub(r'[a-z][/][a-z][/]*[a-z]{0,1}', '', fruit_string)
    fruit_string = re.sub(r'[^A-Za-z0-9\s]+', '', fruit_string)
    return ' '.join(each_word for each_word in fruit_string.split() if each_word not in stop_words and len(each_word) > 2)
    

#All possible fruit combination list
nrows=[]
with open("D:/fruits.csv", 'r') as csvfile: 
    csvreader = csv.reader(csvfile)
    fields = next(csvreader)
    for row in csvreader: 
        nrows.append(row)
        
flat_list = [item for items in nrows for item in items]        



def get_matching_fruits(input_raw_text):
    preprocessed_synonym = preprocessing(input_raw_text)
    text = nltk.word_tokenize(preprocessed_synonym)
    pos_tagged = nltk.pos_tag(text)
    nn = filter(lambda x:x[1]=='NN',pos_tagged)
    list_nn = list(nn)
    nnp = filter(lambda x:x[1]=='NNP',pos_tagged)
    list_nnp = list(nnp)
    nns = filter(lambda x:x[1]=='NNS',pos_tagged)
    list_nns = list(nns)
    comb_nouns = list_nn + list_nnp + list_nns
    input_nouns = [i[0] for i in comb_nouns]
    input_nouns= ' '.join(input_nouns)
    ratios = process.extract(input_nouns, flat_list, limit=1000)
    result = []    
    for i in ratios:
        if input_nouns in i[0]:
            result.append(i)
    return result    

get_matching_fruits('blue shaped pear was found today')

因此，在我的代码中，我希望 result list 包含给定任何相关输入的所有可能匹配项。非常欢迎对此提供任何帮助。

Answer 1

对我来说最简单的解决方案是这个。

foo = 'fruit apple'
bar = [('apple fruit', 91), 
       ('the fruit is an apple', 34), 
       ('banana apple', 78), 
       ('guava tree', 11), 
       ('delicious apple', 88)]

matches = []
for entry in bar:
    for word in foo.split():
        # break if we meet a point where the word isn't found
        if word not in entry[0]:
            break
    # the else is met if we didn't break from the for loop
    else:
        matches.append(entry)

print(matches)

Answer 2

抱歉，如果我有点不理解这个问题，但为什么你甚至需要一个 NLTK 库来做这个..这是一个简单的列表理解问题

In [1]: tup = [('apple fruit', 91), ('the fruit is an apple', 34), ('banana apple', 78), ('guava tree', 11), ('delicious apple', 88)]

In [2]: input_string = 'fruit apple'

In [3]: input_string_set =  set(input_string.split(' '))

In [4]: input_string_set
Out[4]: {'apple', 'fruit'}

In [10]: [t for t in tup if input_string_set.issubset(set(t[0].split(' ')))]
Out[10]: [('apple fruit', 91), ('the fruit is an apple', 34)]

In [11]:

查找输入字符串与 Python 中的元组列表的所有可能匹配项（在任何 order/sequence 中）

Find all possible matches (in any order/sequence) of an input string to a list of tuples in Python

python

python-3.x

regex

string-matching

fuzzywuzzy