Improving Efficiency and Accuracy in String Transformation on Large Data Sets

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Provided by: Creative Commons
Topic: Big Data
Format: PDF
In this paper, the authors discuss the problems in information processing on data mining, information retrieval, and bioinformatics can be put forwarded to string transformation. The k most likely output strings are generated corresponding to the given input string for string transformation. It proposes a probabilistic approach such as log linear model-a training method and algorithm for generating top k candidates to string transformation. 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.
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