Ontology Based Pivoted normalization using Vector Based Approach for information Retrieval

Research Scholar, Computer Science and Engineering Department, Lingaya’s University, Faridabad Associate Professor, Computer Science and Engineering Department, Lingaya’s University, Faridabad [email protected], [email protected] ABSTRACT An ample amount of documents present on web puts the users in state of dilemma. Users get confused about relevance of documents. Relevance means how closely the given query matches large number of documents. Many information extraction techniques are used for extracting documents but they all are in vain. The paper deals with the problem of classification, analyzing and extraction of web documents by using one of information extraction methods called Ontology Based Web Content Mining Methodology. We have evaluated proposed methodology in two specific domainsweather domain (web pages containing information about weather forecasting and analysis) and Google TM collection (web pages containing news). The proposed methodology is procedural i.e. it follows finite number of steps that extracts relevant documents according to user’s query. It is based on principles of Data Mining for analyzing web data. Data Mining first adapts integration of data to generate warehouse. Then, it extracts useful information with the help of algorithm. The task of representing extracted documents is done by using Vector Based Statistical Approach that represents each document in set of Terms.