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Application of Graph Rewriting to Natural Language Processing

The paradigm of Graph Rewriting is used very little in the field of Natural Language Processing. But graphs are a natural way;

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Graph-based Natural Language Processing and Information Retrieval

Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these;

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Handbook of Graph Grammars and Computing by Graph Transformation

foundations of all the basic approaches to rule-based graph specification and transformation: algebraic approach, logic approach, node-based rewriting;

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Natural Language Understanding and Intelligent Applications

This book constitutes the joint refereed proceedings of the 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC;

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Graph-Based Semi-Supervised Learning

. In a separate line of work, researchers have started to realize that graphs provide a natural way to represent data in a variety of domains;

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Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017, held in Nanjing, China, in October 2017;

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Language and Automata Theory and Applications

This book constitutes the refereed proceedings of the 12th International Conference on Language and Automata Theory and Applications, LATA;

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Handbook of Natural Language Processing

areas, such as sentiment analysis. New to the Second Edition Greater prominence of statistical approaches New applications section Broader;

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Natural Language Processing

in applications to the statistical translation. Section 3 focuses on mathematical algorithms in natural language processing, describing bridging between;

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Language and Automata Theory and Applications

This book constitutes the refereed proceedings of the 10th International Conference on Language and Automata Theory and Applications, LATA;

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Natural Language Processing and Chinese Computing

graph/IE; Machine Learning for NLP; Machine Translation; NLP Applications; NLP for Social Network; NLP Fundamentals; Text Mining; Short Papers;

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Natural Language Processing and Chinese Computing

graph/IE; Machine Learning for NLP; Machine Translation; NLP Applications; NLP for Social Network; NLP Fundamentals; Text Mining; Short Papers;

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Deep Learning for Natural Language Processing

Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key Features Gain;

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Applied Natural Language Processing with Python

Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document;

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Natural Language Processing and Chinese Computing

Bot/QA/IR; knowledge graph/IE; machine learning for NLP; machine translation; and NLP applications. The papers of the second volume are;

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Natural Language Processing and Text Mining

Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text;

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Language and Automata Theory and Applications

This book constitutes the refereed proceedings of the 9th International Conference on Language and Automata Theory and Applications, LATA;

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Large-Scale Graph Processing Using Apache Giraph

This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power;

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The Oxford Handbook of Computational Linguistics

-labelling, text-to-speech synthesis, translation technology, opinion mining and sentiment analysis, and the application of Natural Language;

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Natural Language Processing Recipes

Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises;

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Querying Graphs

Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary;

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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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Scientific Applications Of Language Methods

Applications of Language Methods is a multi-author volume containing pieces of work (either original research or surveys) exemplifying the application;

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Embeddings in Natural Language Processing

development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures;

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Embeddings in Natural Language Processing

development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures;

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Embeddings in Natural Language Processing

development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures;

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