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Information Technology Journal
  Year: 2013 | Volume: 12 | Issue: 4 | Page No.: 867-870
DOI: 10.3923/itj.2013.867.870
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Analysis of Bilateral Intelligence (ABI) for Textual Pattern Learning

S. Koteeswaran and E. Kannan

Textual pattern mining is one of the major research areas in the field of data mining. The data mining is a emergent technique which adopts many approaches and methods from other fields of study. The data mining is implemented in other areas to learn hidden knowledge. In this study, Artificial Neural Network (ANN) is used for learning textual pattern in the Metadata conceptual mining model. The proposed learning algorithm is called as, analysis of bilateral intelligence, which is used to identify and classify the synonymy of the sentences. The proposed method provides efficient learning by identifying the patterns which have synonymy. The results of the proposed work show that the convergent of the training algorithm is very fast than existing methodology. From the results, it is concluded that the performance of proposed ABI is optimized. Hence, the proposed Metadata conceptual mining model with ABI learning will provide optimality than existing clustering algorithm.
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  •    Enhanced Neural Networks Model Based on a Single Layer Linear Counterpropagation for Prediction and Function Approximation
  •    Employing Artificial Neural Networks into Achieving Parameter Optimization of Multi-Response Problem with Different Importance Degree Consideration
How to cite this article:

S. Koteeswaran and E. Kannan, 2013. Analysis of Bilateral Intelligence (ABI) for Textual Pattern Learning. Information Technology Journal, 12: 867-870.

DOI: 10.3923/itj.2013.867.870






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