The Open Text Mining Interface (OTMI) is an initiative from Nature Publishing Group (NPG). It aims to enable scholarly publishers, among others, to disclose their full text for indexing and text-mining purposes but without giving it away in a form that is
Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well.
Powerful Search Engine designed for Document Management, Competitive Intelligence, Press Analysis and Text Mining, Web Mining, Knowledge Discovery, Strategic Watch...Has Report Writer, Web Spider, Publisher, more...
The eXtensible Text Framework (XTF) is a flexible indexing and query tool that supports searching across collections of heterogeneous data and presents results in a highly configurable manner. The highlights of the XTF system are described in an online brochure
David D. Lewis, Ph.D.
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Services: I work with clients to make the most effective use possible of textual data. Applications I have worked on include search engines, text categorization, filtering of email and web pages, mining of customer data, and a variety of others. My clients have included both vendors and users of text processing software, and my work with them has included mining data sets, analyzing manual and automated text processing procedures, designing algorithms and system architectures, performing competitive and strategic analysis, training, and ongoing advisory relationships. Contact me to see how we can work together.
M. Hearst. Proceedings of the 37th annual meeting of the Association for Computational
Linguistics on Computational Linguistics, стр. 3--10. Morristown, NJ, USA, Association for Computational Linguistics, (1999)
M. Hearst. Proceedings of the 37th annual meeting of the Association for Computational
Linguistics on Computational Linguistics, стр. 3--10. Morristown, NJ, USA, Association for Computational Linguistics, (1999)