Pattern discovery for text mining

Abstract

Text mining can be defined as the art of extracting data from large amount of texts. It allows to structure and categorize the text contents which are initially non organized and heterogeneous. Text mining is an important data mining technique which includes the most successful technique to extract the effective patterns. The paper focuses on developing an efficient method for discovering patterns from the document. In text mining field, pattern mining techniques are used to find text patterns, such as frequent item sets, closed frequent item sets, co-occurring terms. This paper presents an innovative and effective pattern discovery technique which includes the process of pattern evolving and pattern deploying, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information.

A Novel Approach for Discovering the Patterns by using PDBD Model in Big Data

“…An algorithm for pattern discovery which includes the process of pattern evolving and pattern deploying, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information (Aswini and Lavanya, 2014).…”