Natural Language Processing with Java: Techniques for building machine learning and neural network models for NLP, 2nd Edition
Provides an overview of Natural Language Processing (NLP) techniques and their implementation using Java APIs. It covers fundamental concepts like tokenization, stemming, lemmatization, and Parts-of-Speech (POS) tagging, explaining how text is processed at character, word, and sentence levels. The text also explores advanced topics such as information retrieval, text classification, sentiment analysis, named-entity recognition (NER), and chatbot creation, demonstrating practical applications with various libraries and frameworks like OpenNLP, Stanford CoreNLP, LingPipe, and MALLET. Additionally, it discusses data preparation, model training and evaluation, and extracting text from different file formats (Word, PDF, HTML), emphasizing the importance of pipelines for combining NLP tasks.
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