Waqas Ali2019-01-162019-01-162018https://escholar.umt.edu.pk/handle/123456789/3531Dr. Adnan AbidText similarity plays an important role in document clustering, plagiarism detection, automatic student answer grading, information retrieval and language translation systems. Many researchers have studied on string, corpus and knowledge based approaches to resolve the problem of document similarity. In this paper research has been made on full text similarity and context information of a news. Time complexity and follow-ups distribution are main challenges for full text similarity which is computed by using jaccard index. The proposed system in this paper uses context information of news to resolve these issue and to classify the news into three categories i.e. same day follow-ups, different day follow-ups and distinct news. Context is built by using well known Stanford parser which further enriched with factor of severity to reduce the target dataset for similarity computation. Results showed that context aware similarity approach is better than traditional full text similarity approach in efficiency and accuracy.enContext Aware News , news articles, human lossMSThesis