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Proposed Method for String Transformation using Probablistic Approach

Publication Date : 31/12/2014

Author(s) :

Gayatri N. Kotame , Prof.P.N.Kalavadekar.

Volume/Issue :
Volume 1
Issue 6
(12 - 2014)

Abstract :

For this system the string is given as an input to the system generates the k most likely output strings corresponding to the input string. This system proposes both accurate and efficient feature by using a novel and probabilistic approach to string transformation, which is. The approach is includes the use of a log linear model, a method for training the model, and an algorithm for generating the top k candidates, whether there is or is not a predefined dictionary. The log linear model is defined as a conditional probability distribution of an output string and a rule set for the transformation conditioned on an input string. The learning method employs maximum likelihood estimation for parameter estimation. The string generation algorithm based on pruning is guaranteed to generate the optimal top k candidates. The proposed method will apply to correction of spelling errors in queries as well are formulation of queries in web search.

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Proposed Method for String Transformation using Probablistic Approach

December 24, 2014