Evaluate and Improve Weight Based Pattern Detection Algorithm for Text Mining

Gagandeep Kaur, Hardeep Singh

Abstract: Semantic text mining is an ion of an acknowledge based on the meaning. Semantic terms are explained, phrases or words. The searching terms concern their weight is computed corresponding to their synonyms, and the term which has maximum weight is at the top. The determined technique will make use of neural technique for clustering the document present to their meaning. If various words which have similar meaning are present in document then it will cluster it in similar cluster. Increment the cluster quality neural network approach, with semantic based analyzer is used popularized.

Keywords: data mining, text mining, text clustering, pattern taxonomy model

How to Cite?: Gagandeep Kaur, Hardeep Singh, "Evaluate and Improve Weight Based Pattern Detection Algorithm for Text Mining", Volume 5 Issue 9, September 2016, International Journal of Science and Research (IJSR), Pages: 272-278, https://www.ijsr.net/getabstract.php?paperid=ART20161468, DOI: https://dx.doi.org/10.21275/ART20161468