<prompt> Design an algorithm to detect plagiarism in academic papers.  <response>: There is not a single way to design an algorithm to detect plagiarism in academic papers, but here is one possible approach:1. Preprocessing: - Convert the input text academic paper into machine-readable format, by removing special characters, converting words to lower case, and tokenizing the text by breaking it into individual words or terms. - Normalize the text by removing common stop words like and, or, and the like, and apply lemmatization, reducing terms to their base or root form.2. Extracting Features: - Construct a feature set for the text, by counting the frequency of terms, N-Grams combinations of N consecutive words, and synonyms. - Use Latent Semantic Analysis to identify the main topics and concepts present within a document. - Get information about the citation style to compare it with the recommended one.3. Building the Model: - Use machine learning techniques to train a classification model for detecting plagiarized text. - Test the model using a labeled dataset of both original and plagiarized documents, to evaluate its accuracy and fine-tune it as required.4. Detecting Plagiarism: - Apply the trained model on the input text to determine if it is likely to be plagiarized or not. - Check if there is enough similarity between the original content and the input text. - Look for patterns of unusual phrasing or vocabulary, mismatches in citation style, and inconsistencies in writing style, which may indicate plagiarism.5. Result: - Report the final result, indicating whether the input text is plagiarized or not, along with a confidence score, and highlight sections of the text that are likely to be plagiarized, for further review. 