Added plagiarism checker script

scripts/Plagiarism-checker/README.md

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+# Plagiarism Checker
+
+This is a simple Python script to check plagiarism between 2 files.
+
+## Using the script
+
+```bash
+# install xlwt
+pip install scikit-learn
+# run script
+python script.py
+```

scripts/Plagiarism-checker/sample1.txt

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+A plagiarism checker helps in preventing duplicacy in two files. This way authenticity of content is maintained.

scripts/Plagiarism-checker/sample2.txt

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+A plagiarism checker helps in preventing duplicacy in two files. This way authenticity of content is maintained.

scripts/Plagiarism-checker/script.py

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