Find most similar sentence in the file to the input sentence | NLP
In this article, we will find the most similar sentence in the file to the input sentence.
Example:
File content: "This is movie." "This is romantic movie" "This is a girl." Input: "This is a boy" Similar sentence to input: "This is a girl", "This is movie".
Approach:
- Create a list to store all the unique words of the file.
- Convert all the sentences of the file into the binary format by comparing each word with the content of the list, after cleaning(removing stopword, stemming, etc.)
- Convert the input sentence in the binary format.
- Find the number of similar words in the input sentence to each sentence and store the value in the list named similarity index.
- Find the maximum value of similarity index and return the sentence having maximum similar words.
Content of the file:
Code to get a similar sentence:
Python3
from nltk.stem import PorterStemmer from nltk.tokenize import word_tokenize, sent_tokenize import nltk from nltk.corpus import stopwords nltk.download( 'stopwords' ) ps = PorterStemmer() f = open ( 'romyyy.txt' ) a = sent_tokenize(f.read()) # removal of stopwords stop_words = list (stopwords.words( 'english' )) # removal of punctuation signs punc = '''!()-[]{};:'"\, <>./?@#$%^&*_~''' s = [(word_tokenize(a[i])) for i in range ( len (a))] outer_1 = [] for i in range ( len (s)): inner_1 = [] for j in range ( len (s[i])): if s[i][j] not in (punc or stop_words): s[i][j] = ps.stem(s[i][j]) if s[i][j] not in stop_words: inner_1.append(s[i][j].lower()) outer_1.append( set (inner_1)) rvector = outer_1[ 0 ] for i in range ( 1 , len (s)): rvector = rvector.union(outer_1[i]) outer = [] for i in range ( len (outer_1)): inner = [] for w in rvector: if w in outer_1[i]: inner.append( 1 ) else : inner.append( 0 ) outer.append(inner) comparison = input ( "Input: " ) check = (word_tokenize(comparison)) check = [ps.stem(check[i]).lower() for i in range ( len (check))] check1 = [] for w in rvector: if w in check: check1.append( 1 ) # create a vector else : check1.append( 0 ) ds = [] for j in range ( len (outer)): similarity_index = 0 c = 0 if check1 = = outer[j]: ds.append( 0 ) else : for i in range ( len (rvector)): c + = check1[i] * outer[j][i] similarity_index + = c ds.append(similarity_index) ds maximum = max (ds) print () print () print ( "Similar sentences: " ) for i in range ( len (ds)): if ds[i] = = maximum: print (a[i]) |
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Output:
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