1. Build a Fourth-gram language model Each student needs to collect an Arabic corpus of at least 100,000 words, but the more is better. A bonus will be given if the corpus contains Arabic dialects. Students cannot use the same corpus, fully or partially. Write a program to tokenize the corpus into tokens/words, then build a 4-gram model for this corpus. That is, your language model is a table that contains: the token, the token counts, and the token probability. The language model should be saved in CSV format. 2. Develop a plagiarism detection interface Develop a program (in JAVA) that uses your language model to compute a plagiarism score for a given sentence. In other words, the user can write a sentence in Arabic, and when clicking "Go", the program will compute the probability of this sentence using the language mode. This probability should be tuned to reflect a plagiarism score. The more similar a given sentence (fully or partially) to sentences in the corpus the higher the plagiarism score. Example: Submission: corpus language model.csv, source code, and all files used to run the project. During the discussion, students will be also asked theoretical questions related NLP