Topic detection and tracking in news articles

Abstract

We have presented an idea in this paper for detecting and tracking topics from news articles. Topic detection and tracking are used in text mining process. From data which are unstructured in text mining we pluck out information which are previously unknown. The objective of this paper is to recognize tasks occurred in different news sources. We are going to use agglomerative clustering based on average linkage for detecting the topics, calculate the similarity of topics using cosine similarity and KNN classifier for tracking the topics.