Conceptual Search Engine using Non-Negative Matrix Factorizationand Brush Structure Model

Search for web pages of personwith given name constitutes notable fraction of queries to web search engines. Such a query would normally return Web Pages related to several namesakes. This list is counterproductive because the user finds it extremely difficult to scroll through many entries to find the desired information. So here we propose a new formulation of the conceptual problem where the goal is to explicitly output a collection of simple and meaningful conjunctions of attributes that defines the conceptual clusteringof brush structure model. This research work is mainly focused on affording a knowledge mining tool in the form of brush model that results in spite of web page URLS. The primary goal is to develop conceptual clustering web pagesusing Non-Negative Matrix Factorisation(NMF). The secondary goal to maintain that web pages using Brush structure model. In future, this Conceptual Clustering search engine using Brush structure model may be played as a powerful tool in the search engine.