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36 lines
1.4 KiB
Python
36 lines
1.4 KiB
Python
# Plagiarism detector using cosine similarity
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.metrics.pairwise import cosine_similarity
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def Plagiarism_Checker(files, student):
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results = set()
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# converting text from the text file and storing into an array
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v = lambda Text: TfidfVectorizer().fit_transform(Text).toarray()
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# comparing of two data from two text files
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similarity = lambda doc1, doc2: cosine_similarity([doc1, doc2])
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vectors = list(zip(files, v(student)))
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for stud, text_vector_a in vectors:
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n_vectors = vectors.copy()
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i = n_vectors.index((stud, text_vector_a))
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del n_vectors[i]
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for stud2, vector2 in n_vectors:
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# matching similairty score by comparing elements present
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# in an array
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sim_score = similarity(text_vector_a, vector2)[0][1]
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stud_pair = sorted((stud, stud2))
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match_per = (stud_pair[0], stud_pair[1],sim_score)
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results.add(match_per)
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#returns the score for matching between 2 files. percent match = score*100 %
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return results
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student_files = ["sample1.txt", "sample2.txt"]
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student_notes = []
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for file in student_files:
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# opening the file present in the current directory
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with open(file, "r") as f:
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student_notes.append(f.read())
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results = Plagiarism_Checker(student_files, student_notes)
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for result in results:
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print("Result: ", result) |