Abstract
As the engineering world are growing fast, the usage of data for the day to day activity of the engineering industry also growing rapidly. In order to handle and to find the hidden knowledge from huge data storage, data mining is very helpful right now. Text mining, network mining, multimedia mining, trend analysis are few applications of data mining. In text mining, there are variety of methods are proposed by many researchers, even though high precision, better recall are still is a critical issues. In this study, text mining is focused and conceptual mining model is applied for improved clustering in the text mining. The proposed work is termed as Meta data Conceptual Mining Model (MCMM), is validated with few world leading technical digital library data sets such as IEEE, ACM and Scopus. The performance derived as precision, recall are described in terms of Entropy, F-Measure which are calculated and compared with existing term based model and concept based mining model.
Highlights
Which predicts unknown or future values of interest by using some variables or fields in the data set and the
In order to execute these processes in the data mining requires clustering and outlier analysis for reducing as well as identifying useful dataset
These most frequent ctf and tf terms are verified with Step 1: Apply preprocessing stage
Summary
Which predicts unknown or future values of interest by using some variables or fields in the data set and the. In the conceptual analysis stage, the terms which appeared in each STL are searched in the given training documents. This process continues for each training documents and each additional relevant terms identified in the training phase is added in the concern STL. In order to avoid technical person interpretation and manipulation, as it involves more costly job, the concept based mining model proposes concept analysis. These most frequent ctf and tf terms are verified with Step 1: Apply preprocessing (remove di-grams and trithe technical terms which prepared in the preprocessing grams) stage It needs any clerical level staff member to classify the documents. The Meta data Conceptual Mining Model (MCMM), used for effective text
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