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Topic: Natural language processing


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In the News (Fri 19 Jul 19)

  
  Natural language processing - Wikipedia, the free encyclopedia
Natural language processing (NLP) is a subfield of artificial intelligence and linguistics.
Natural language understanding is sometimes referred to as an AI-complete problem, because natural language recognition seems to require extensive knowledge about the outside world and the ability to manipulate it.
The grammar for natural languages is ambiguous, i.e.
en.wikipedia.org /wiki/Natural_language_processing   (962 words)

  
 Natural Language Processing
The goal of the Natural Language Processing (NLP) group is to design and build software that will analyze, understand, and generate languages that humans use naturally, so that eventually you will be able to address your computer as though you were addressing another person.
It's ironic that natural language, the symbol system that is easiest for humans to learn and use, is hardest for a computer to master.
Amalgam is a novel system developed in the Natural Language Processing group at Microsoft Research for sentence realization during natural language generation that employs machine learning techniques.
www.research.microsoft.com /nlp   (628 words)

  
 IT-Director.com - Natural Language Processing
Natural language processing is one way to support searches (and other things) through large numbers of documents and other text.
The big disadvantage of natural language processing is that you have to have a separate version of the product for each language and, where appropriate, for each dialect of a language.
Using natural language processing, on the other hand, you can summarise documents so that you get a précis of each document, which is considerably more useful.
www.it-director.com /article.php?id=3704   (617 words)

  
 [No title]   (Site not responding. Last check: 2007-11-06)
Natural Language Processing ================================================================ The term: "natural" languages refer to the languages that people speak, like English and Japanese and Swahili, as opposed to artificial languages like programming languages or logic.
Language is a set of resources to enable us to share meanings, but isn't best thought of as a means for *encoding* meanings.
For example, language can be more efficient by not having to say the same thing twice, so we have pronouns and other ways of making use of what has already been said: A bear went into the woods.
cogsci.ucsd.edu /~batali/108b/lectures/natlang.txt   (4250 words)

  
 IBM Research - Natural Language Processing - Speaker Bureau
Natural Language Understanding in a restricted domain can be posed as problem of selecting the most probable formal language sentence given the natural language utterance.
Language modeling deals with the estimation of the frequency of a given word given the preceding words in text.
In this talk, we present a history of the "smoothing" techniques studied in language modeling to estimate unseen event probabilities, and we discuss the impact of improved smoothing in language modeling on the tasks of text compression and speech recognition.
www.research.ibm.com /compsci/nlp/bureau.html   (889 words)

  
 An Introduction to NLP
Natural language understanding: here treated as moving from isolated words (either written or determined via speech recognition) to 'meaning'.
A simple division is between semantics, referring to the meaning of words and thus the meaning of sentences formed by those words[3] and pragmatics, referring to the meanings intended by the originator of the words.
[1] NLP is often used in a way which excludes speech; SNLP is then needed as a term to include both speech and other aspects of natural language processing.
www.cs.bham.ac.uk /~pxc/nlpa/2002/AI-HO-IntroNLP.html   (2263 words)

  
 Natural Language Processing and Artificial Intelligence
Natural Language Processing is a major research area within the department and is aided by interaction with faculty in the Department of Linguistics and the Department of Psychology, and by graduate linguistics and psychology courses.
It combines natural language processing and computer vision to solve problems without any of the preprocessing that is usually done by humans.
Use of Focus in Natural Language Generation (McCoy): In order for a computer system to generate written text, it must have some method for deciding what to say next and for deciding when it is appropriate to use a pronoun.
www.cis.udel.edu /~decker/ai_nlp.html   (2602 words)

  
 FAQ - Natural Language Processing
Natural language interfaces enable the user to communicate with the computer in German, English or another human language.
Even though the successful simulation of human language competence is not to be expected in the near future, computational linguists have numerous immediate research goals involving the design, realization and maintenance of systems which facilitate everyday work, such as grammar checkers for word processing programs.
Natural Language Engineering is an international journal designed to meet the needs of professionals and researchers working in all areas of computerised language processing, whether from the perspective of theoretical or descriptive linguistics, lexicology, computer science or engineering.
www.uni-koblenz.de /~compling/CL-Allgemein/FAQ-NLP.html   (5228 words)

  
 Natural Language Processing
One goal of AI work in natural language is to enable communication between people and computers without resorting to memorization of complex commands and procedures.
Natural Language Lecture Slides and Accompanying Transcripts from Professors Tomás Lozano-Pérez and Leslie Kaelbling's Spring 2003 course: Artificial Intelligence.
Not only does the ability to use and understand natural language seem to be a fundamental aspect of human intelligence, but also its successful automation would have an incredible impact on the usability and effectiveness of computers themselves.
www.aaai.org /AITopics/html/natlang.html   (3968 words)

  
 CS 224N / Ling 280
This course is designed to introduce students to the fundamental concepts and ideas in natural language processing (NLP), and to get them up to speed with current research in the area.
Word-level, syntactic, and semantic processing from both a linguistic and an algorithmic perspective are considered.
The focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, disambiguation, and parsing.
www.stanford.edu /class/cs224n   (373 words)

  
 NLP@Pitt
We are pursuing research in a wide range of natural language processing problems, including discourse and dialogue, spoken language processing, affective computing, natural language learning, statistical parsing, and machine translation.
On the other hand research in human-human interaction has also shown that listeners are flexible in their use of language in that they are able to adapt to speaker-dependant patterns, and that they are capable of establishing and using new referring expressions and sub-languages for specific domains.
The natural approach argues that in order to be easy to use, such interfaces should approximate human-human interaction as closely as possible, including context-dependant generation and understanding of referring expressions.
nlp.cs.pitt.edu   (1382 words)

  
 Natural Language Processing FAQ
Keywords: language natural processing computational linguistics Last-Modified: Fri Feb 2 14:18:48 EST 2001 Posting-Frequency: Monthly Version: 0.1 Archive-Name: natural-lang-processing-faq This is the latest release of an FAQ (frequently asked questions and answers) list for the comp.ai.nat-lang newsgroup.
Mark Kantrowitz's Natural Language Generation (NLG) bibliography is available by anonymous ftp from ftp://ftp.cs.cmu.edu/user/ai/areas/nlp/nlg/bib/mk/ [128.2.206.173] In addition to the tech report, the BibTeX file containing the bibliography is also available.
Proceedings of the ACL Workshop on Reversible Grammar in Natural Language Processing, UC Berkeley, 1991.
www.faqs.org /faqs/natural-lang-processing-faq   (5300 words)

  
 Natural Language Processing and Information Extraction
NLP draws from a number of areas including linguistics, statistics and machine learning techniques like neural networks and support vector machines.
Natural Language Processing is a large area, which includes topics like text understanding and machine learning.
The Natural Language Processing Laborary web page of the University of Massachusetts states that they no longer longer active in NLP.
www.bearcave.com /misl/misl_tech/nlp.html   (3393 words)

  
 PC AI - Natural Language Processing
Applications of NLP include machine translation of one human-language text to another; generation of human-language text such as fiction, manuals, and general descriptions; interfacing to other systems such as databases and robotic systems thus enabling the use of human-language type commands and queries; and understanding human-language text to provide a summary or to draw conclusions.
One of the easiest tasks for a NLP system is to parse a sentence to determine its syntax.
The Speech and Language Technology (SLT) Group is focusing on Speech Processing, Natural Language Processing and Optical Character Recognition.
www.pcai.com /web/ai_info/natural_lang_proc.html   (605 words)

  
 Natural Language Processing Lab home page
Along with the Center for Speech and Language Processing, the members of the NLP Lab are committed to finding novel and efficient computational methods that rival human performance in natural language competency tasks.
Effective natural language interfaces will be an enabling technology for the mass exploitation of the benefits of computing.
In conjuction with the Center for Speech and Language Processing, the members of the NLP Lab are committed to finding novel and efficient computational methods that rival human performance in natural language competency tasks.
nlp.cs.jhu.edu /nlp   (193 words)

  
 ITworld.com - The future of natural-language processing
Natural-language processing (NLP) is an area of artificial intelligence research that attempts to reproduce the human interpretation of language.
NLP methodologies and techniques assume that the patterns in grammar and the conceptual relationships between words in language can be articulated scientifically.
One of the major limitations of modern NLP is that most linguists approach NLP at the pragmatic level by gathering huge amounts of information into large knowledge bases that describe the world in its entirety.
www.itworld.com /AppDev/916/UIR001229ontology   (3089 words)

  
 IBM Research | Research Areas | Natural Language Processing
Our mission is to offer speech and language technologies that form the core of current and future products and solutions for processing natural language.
Furthermore, our work addresses theoretical issues of computational linguistics and encompasses a wide range of application areas such as speech processing, machine translation, question answering, interactive dialogue systems, text mining and information extraction, natural language understanding and generation, information retrieval, and automatic text summarization.
Using NLP technologies, documents are transformed into a collection of concepts, described using terms discovered in the text.
www.research.ibm.com /compsci/spotlight/nlp/index.html   (938 words)

  
 Natural Language Processing (NLP) at Cornell
We are also developing natural language techniques for automating the lexical knowledge acquisition tasks that comprise the building of any NLP system.
Coreference is a key task in a number of NLP applications and is often cited as one of the most difficult problems in NLP owing to its reliance on sophisticated world knowledge.
In contrast to most existing coreference resolution algorithms that employ hand-crafted heuristics and filters, we are interested in applying both supervised and unsupervised machine learning techniques to the construction of robust and portable coreference systems.
www.cs.cornell.edu /Info/Projects/NLP   (1860 words)

  
 Dalhousie Natural Language Processing Group
The Dalhousie Natural Language Processing Group (DNLP) provides information about NLP-related research conducted at the University of Dalhousie, and it isa forum for discussion, collaboration, and interaction between researchers interested in the philosophies, theories, and applications related to NLP.
The Dalhousie NLP Group was formed in May 2003 by a combined effort from faculty members and graduate students.
Some of the topics the group is interested in are: language modeling, information extraction, information retrieval, question answering, parsing, text mining, data mining, text categorization, document clustering, speech recognition, automatic translation, syntactic and semantic analysis.
flame.cs.dal.ca /~nlp   (504 words)

  
 Mary D. Taffet's Home Page: WWW Sites for Natural Language Processing -- Instructor's Version
http://web.syr.edu/~mdtaffet/nlp_sites.html; this student version was created primarily for the use of the current students in the Natural Language Processing course taught by Elizabeth Liddy at Syracuse University's School of Information Studies, but if you would find it useful for your students as well, please feel free to share it with them.
Other useful links for NLP students, relating to any aspect of Natural Language Processing that might be encountered in an academic course, from the lowest levels of language processing to the highest levels
There is a switch which controls the language of input; you are asked to Specify the language of the text to be submitted.
web.syr.edu /~mdtaffet/nlp_sites_for_instructors.html   (2623 words)

  
 Natural Language Processing: Curry Guinn
Two key technologies that can help reduce the burden on instructors and increase the efficiency and independence of trainees are virtual reality simulators and natural language processing.
This paper focuses on the design of a virtual reality trainer that uses a spoken natural language interface with the trainee.
AMAT integrates spoken language processing, virtual reality, multimedia and instructional technologies to train and assist the turret mechanic in diagnosing and maintenance on the M1A1 Abrams Tank in a hands-busy, eyes-busy environment.
people.uncw.edu /guinnc/interests/nlp.html   (572 words)

  
 CS@CU NLP   (Site not responding. Last check: 2007-11-06)
The Natural Language Processing (NLP) track is intended for students who wish to gain expertise in NLP technologies and applications.
NLP technologies are of central importance in automating the analysis of text and speech databases and in enabling man-machine interactions through natural language.
Candidates preparing for graduation should submit a completed application for degree to the Registrar's Office and submit a track graduation form to C.S. Student Services (an example of a completed form is available here).
www.cs.columbia.edu /education/ms/nlp   (448 words)

  
 CS674: Natural Language Processing
An empirical study of smoothing techniques for language modeling Proceedings of the 34th Meeting of the Association for Computational Linguistics, pp 310--318.
The Computation and Language E-Print Archive is a handy repository for NLP papers.
Speech and Language Processing, by Daniel Jurafksy and James Martin.
www.cs.cornell.edu /courses/cs674/2002SP   (1356 words)

  
 N-GSLT: Natural Language Processing Course (2006)
The course is aimed both at students with limited knowledge of the field, for whom it is compulsory within GSLT, and at students with a more extensive background in natural language processing, who will be expected to take more active part in the discussion of current research.
In addition to the practical exercises and online discussions, students will be expected to produce a term paper where they discuss a research problem of their own choice in relation to other areas of natural language processing.
The set topic for this paper is to discuss the place of your own research problem within the larger field of NLP and to relate it to other problems and methods.
www.ling.su.se /DaLi/education/courses/ngslt_nlp06/index.html   (637 words)

  
 Natural Language Processing Tools
It is intended for both phonology students and researchers in that it facilitates understanding of phonological rule fundamentals and helps manage large complex bodies of phonological rules.
Description: Natural Language (TM) is an extensible natural language interface to relational SQL databases.
It employs a parser, semantic interface, natural language generator, and a deductive system that interprets English questions in the context of the specific applications.
www.cs.cofc.edu /~manaris/ai-education-repository/nlp-tools.html   (1459 words)

  
 IBM Research | IBM Research | Natural Language Processing   (Site not responding. Last check: 2007-11-06)
Natural Language Processing at IBM is a dynamic research area spanning a wide range of topics vital for the development of cutting-edge applications of language engineering.
We work on theoretical issues of computational linguistics and develop technologies such as speech processing, machine translation, universal and application-specific dialog engines, information retrieval, text mining and hypertext databases, automatic text summarization, natural language understanding and generation, to mention just a few.
One key goal is to provide advanced NLP software for multiple languages and modalities exploited in business applications.
domino.research.ibm.com /comm/research.nsf/pages/r.nlp.html   (134 words)

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