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Natural Language Toolkit — NLTK 2.0 documentation

Natural Language Toolkit — NLTK 2.0 documentation
NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning. Thanks to a hands-on guide introducing programming fundamentals alongside topics in computational linguistics, NLTK is suitable for linguists, engineers, students, educators, researchers, and industry users alike. NLTK is available for Windows, Mac OS X, and Linux. Best of all, NLTK is a free, open source, community-driven project. NLTK has been called “a wonderful tool for teaching, and working in, computational linguistics using Python,” and “an amazing library to play with natural language.”

http://nltk.org/

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Language Computer - Cicero On-Demand API The Cicero On-Demand provides a RESTful interface that wraps LCC's CiceroLite and other NLP components. This API is used for Cicero On-Demand whether the server is the one hosted at LCC or is run locally on your machine. You can access a free, rate-limited version online, as described below, at demo.languagecomputer.com. For more information on service plans, contact support. Following is a description of the REST calls, which are valid for both the hosted and local modes.

PyLab - Currently this page reflects the vision of KeirMierle , and not necessarily the community as a whole. By integrating consensus from mailing list discussions, I will refine and polish this vision and form a plan of action such that the community can move the numpy+scipy+ipython+matplotlib ensemble closer to the vision outlined below. See the following post for further discussion of the difference between the vision for a new PyLab expressed on this page, and the existing pylab package which is part of matplotlib: To make PyLab an easy to use, well packaged, well integrated, and well documented, numeric computation environment so compelling that instead of having people go to Python and discovering that it is suitable for numeric computation, The philosophy behind this vision is to consider Rails and Ruby; while Ruby was somewhat popular beforehand, it was Rails which propelled it to the forefront.

ch07 For any given question, it's likely that someone has written the answer down somewhere. The amount of natural language text that is available in electronic form is truly staggering, and is increasing every day. However, the complexity of natural language can make it very difficult to access the information in that text. Natural language processing Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human–computer interaction. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural language input, and others involve natural language generation. History[edit] The history of NLP generally starts in the 1950s, although work can be found from earlier periods.

pyquery pyquery allows you to make jquery queries on xml documents. The API is as much as possible the similar to jquery. pyquery uses lxml for fast xml and html manipulation. This is not (or at least not yet) a library to produce or interact with javascript code.

The Stanford NLP (Natural Language Processing) Group About | Questions | Mailing lists | Download | Extensions | Models | Online demo | Release history | FAQ About Stanford NER is a Java implementation of a Named Entity Recognizer. Named Entity Recognition (NER) labels sequences of words in a text which are the names of things, such as person and company names, or gene and protein names. It comes with well-engineered feature extractors for Named Entity Recognition, and many options for defining feature extractors. Included with the download are good named entity recognizers for English, particularly for the 3 classes (PERSON, ORGANIZATION, LOCATION), and we also make available on this page various other models for different languages and circumstances, including models trained on just the CoNLL 2003 English training data.

scalalab - A Matlab like environment for Scala Since Google disabled creating new downloads, new downloads can be available from: ScalaLab is migrated with Google's automatic exporter to Github: Project Summary The ScalaLab project aims to provide an efficient scientific programming environment for the Java Virtual Machine. The scripting language is based on the Scala programming language enhanced with high level scientific operators and with an integrated environment that provides a MATLAB-like working style. Also, all the huge libraries of Java scientific code can be easily accessible (and many times with a more convenient syntax).

Natural Language Processing This is a book about Natural Language Processing. By natural language we mean a language that is used for everyday communication by humans; languages like English, Hindi or Portuguese. In contrast to artificial languages such as programming languages and logical formalisms, natural languages have evolved as they pass from generation to generation, and are hard to pin down with explicit rules.

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