Download PDF by Breck Baldwin, Krishna Dayanidhi: Natural Language Processing with Java and LingPipe Cookbook

By Breck Baldwin, Krishna Dayanidhi

ISBN-10: 1783284684

ISBN-13: 9781783284689

NLP is on the middle of net seek, clever own assistants, advertising, and masses extra, and LingPipe is a toolkit for processing textual content utilizing computational linguistics.

This booklet starts off with the foundational yet robust ideas of language id, sentiment classifiers, and overview frameworks. It is going directly to element tips to construct a powerful framework to resolve universal NLP difficulties, prior to finishing with complex innovations for complicated heterogeneous NLP systems.

This is a recipe and educational publication for skilled Java builders with NLP wishes. A easy wisdom of NLP terminology could be valuable. This ebook will consultant you thru the method of the way to construct NLP apps with minimum fuss and maximal impression.

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Extra info for Natural Language Processing with Java and LingPipe Cookbook

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This is the column labeled P(Category|Input), which is the traditional way to write probability of the category given the input. This is the column labeled log 2 P(Category, Input), which is translated as the log2 probability of the category and input. classify package for more information on the metrics and classifiers that implement them. println(classification); } } We got a richer output than we expected, because the type is Classification, but the toString() method will be applied to the runtime type JointClassification.

In the context of this recipe, the classifier instead invokes train() on the text and classification, and the evaluator takes the text, runs it past the classifier, and compares the result to the truth. Another worthwhile experiment is to permute the corpus 10 times and see the variations in performance that come from different partitioning of the data. When evaluating the final performance, always select data from after the training data epoch if possible, to better emulate production environments where the future is not known.

For the non-English category (n), there are 10 cases in truth, of which the classifier thought 1 was English (incorrectly) and 9 were non-English (correctly). Perfect system performance will have zeros in all the cells that are not located diagonally, from the top-left corner to the bottom-right corner. Visit the Javadoc for a more detailed explanation of the confusion matrix—it is well worth mastering. How it works... toArray(new String[0]); } The code will be useful when we run arbitrary data, where the labels are not known at compile time.

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Natural Language Processing with Java and LingPipe Cookbook by Breck Baldwin, Krishna Dayanidhi


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