Investigation and Analysis of Efficient Pattern Discovery Method for Text Mining
Asmeeta Mali
Ms. Asmeeta Mali, Information Technology, DYPIET, Pune, India.
Manuscript received on March 22, 2013. | Revised Manuscript received on April 13, 2013. | Manuscript published on April 30, 2013. | PP: 1-6 | Volume-2, Issue-4, April 2013. | Retrieval Number: C1218022313/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The concept of text mining is nothing but the mechanism of extracting non-trivial and interesting data from the unstructured text dataset. Text mining is consisting of many computer science disciplines with highly oriented towards the artificial intelligence in general such as the applications like information retrieval, pattern recognition, machine learning, natural language processing, and neural networks. The main difference between the search and text mining is that, search needs users attentions means based users requirement search action will perform whereas text mining is the internal process which attempts to find out information in the pattern which is not known before. To do the text mining, there are many methods presented still to the date those are having their own advantages and disadvantages. The major problems related to such techniques are efficient use and update of discovered patterns, problems related to the synonymy and polysemy etc. In this paper we are investigating the one such method which is presented to overcome above said problems related to the text mining’s. The method presented here is based on innovative as well as effective pattern discovery technique and this consisting of processes like pattern deploying and pattern evolving in order to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information.
Keywords: Pattern recognition, Text mining, Knowledge discover, KDD.