Big data for Natural Language Processing
: A streaming approach.
This report provides a comprehensive analysis of the major market drivers, restraints, opportunities, challenges and addresses the key issues in the natural language processing
In view of wide popularity of the cloud computing technology and large development of the cloud-based natural language processing
These include formula recognition methods to recognize and interpret problem texts and put it into a data format that a computer can understand, natural language processing
to generate a formula representation that the formula solver can understand, and formula-processing technology that can solve the composed formula quickly and accurately.
Mutilingual Natural Language Processing
Applications: From Theory to Practice is the first single-source guide to building accurate multilingual NLP systems, and is edited by two leading experts who offer discussions and real-world solutions to blending problems.
"When you start to bring all of this together, the power of the natural language processing
engine with the power of big data [stored in the business vault], you begin to get some very meaningful interactions," explained Borth.
It uses natural language processing
to allow firm to pull key concepts, opinions and categories relevant to their business from these data sources to uncover deeper customer insights.
Attracted by the potential applications, more and more researchers from the artificial intelligence field submerged into the natural language processing
Topics include exploring the unknown nature of data, nature inspired methods for multi-objective optimization, locally recurrent neural networks and their applications, machine learning in natural language processing
, applications of neural networks in animal science, a survey of Bayesian techniques in computer vision, and improving automated planning with machine learning.
This project aims at retrieving biomedical entities like 'genes' and relationships between them from diverse forms of publications, using a mixture of techniques in text mining and Natural Language Processing
. Name-Entity Recognition is achieved by using statistical models and GENETAG corpus to extract gene names.