A Framework for Multilingual Text Refining in Web Mining

Abstract

newline Text mining, also known as text data mining or knowledge discovery from textual databases, refers generally to the process of extracting interesting and non-trivial patterns or knowledge from unstructured text documents. It can be viewed as an extension of data mining or knowledge discovery from (structured) databases. newlineIn search, the user is typically looking for something that is already known and has been written by someone else. The problem is pushing aside all the material that currently is not relevant to your needs in order to find the relevant information. newlineIn our thesis entitled A Framework for Multilingual Text Refining in Web Mining we have developed a Novel framework in which multilingual search content text (Hindi and English) is inserted in the form data. This input data is the base of text mining which has been performed in any web search engine. This framework process multilingual text documents and produce language-independent intermediate forms. Through this framework multilingual searching in Hindi and English ispossible newlineIn the development process of our framework we have collected data from whatsapp, twitter and line. These collected data were preprocessed and index is developed. The tool used for algorithm implementation is Weka 3.2. K-mean algorithm of Clustering is used and high page ranking is our main parameter to judge the performance. Beside high page ranking we have used response time and micro precision are our parameters of judgment. We have deployed our framework namely Novel framework in the form of search engine and compared its performance with Google, msn, ask and seekport. newline