Nekogole - Interactive Web Search Engine Using Data-Mining Technology

Abstract

Because of a rapid increase of web-pages, it is getting to be difficult to retrieve a target web-page. For example, when we use a web search engine, such as Google, it often provides too many web-pages which we don't need. In order to address the issue of web search engine, we propose a new algorithm in which we can get only web-pages which we need. We use a data-mining technology to classify web pages into two subsets, the needed and not. We study two approaches the first one is decision tree learning algorithm ``ID3'' and the other is ``Document Frequency''. We propose six algorithms based on the two approaches. In this paper, we show the experimental result of our proposed algorithms in terms of recall and precision.