The Study and Review of Paraphrase Detection Techniques in Machine Learning

ABSTARCT: Paraphrase is a process of computing the semantic similarity between sentences, which are not lexicographically similar. Though a number of metrics for English language have been proposed in literature, to quantify textual similarity; it addresses the problem for detection of monolingual text-text lexical similarity. Existing system for Indian Language paraphrase detection uses lexical similarity, based on supervised as it requires large scale training paraphrase corpus. The proposed method employs machine learning metrics, based on lexicography similarity with producing output as +1 for paraphrased, -1 for not paraphrased that means it takes a sentence as input and produces another sentence without changing its semantic. The Results are promising as they are independent to the latent variable and produce output even in missing input condition. This approach may also be used to identify Plagiarism of documents and to eliminate duplicates in a text repository.