natural language processing IEEE PAPER
Natural language processing
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This report is one of five reports that were based on the MINDS workshops, led by Donna Harman (NIST) and sponsored by Heather McCallum-Bayliss of the Disruptive Technology Office of the Office of the Director of National Intelligence's Office of Science and
Natural language processing
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Natural language processing (NLP) is the study of mathematical and computational modeling of various aspects of language and the development of a wide range of systems. These include spoken language systems that integrate speech and natural language;
Natural language information processing
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Page 1. NaturalLanguage Information Processing A Computer Grammar of English and Its Applications Naomi Sager New York Universityxv Part 1. Goals and Tools 1 Chapter 1. Introduction 1 1.1 The Goals'of NaturalLanguageProcessing 1 1.2 Properties of Language : 4
The Stanford CoreNLP Natural Language Processing Toolkit.
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Abstract We describe the design and use of the Stanford CoreNLP toolkit, an extensible pipeline that provides core natural language analysis. This toolkit is quite widely used, both in the research NLP community and also among commercial and government users of
Natural language processing for Prolog programmers
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Natural Language Processing
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Natural Language Processing
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The Natural Language Processing group at the University of Szeged has been involved in human language technology research since 1998, and by now, it has become one of the leading workshops of Hungarian computational linguistics. Both computer scientists and
Natural Language Processing
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but the lifelong attempt to acquire it. Albert Einstein Natural Language Processing Gerhard . References for Natural Language Processing chapter 23 in Russell/Norvig: Practical NaturalLanguageProcessing
Exploiting diversity for natural language processing
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The recent popularity of applying machine learning methods to computational linguistics problems has given rise to a large supply of trainable natural language processing systems. Most problems of interest have an array of off-the-shelf products or downloadable code
Natural language processing: a Paninian perspective
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Integrating plot, character and natural language processing in the interactive drama Fa ade
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Abstract.ade is an artificial intelligence-based art/research experiment in electronic narrative an attempt to move beyond traditional branching or hyper-linked narrative to create a fully-realized, one-act interactive drama. We are completing a three year
Natural Language Processing
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President John F. Kennedy was assassinated. The president was shot yesterday. Relatives said that John was a good father. JFK was the youngest president in history. His family will bury him tomorrow. Friends of the Massachusetts native will hold a candlelight service in
Human engineering fcr applied natural language processing
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ABSTRACT Human engineeringfeaturesfo renhancingthe usabil ity of practical natural language systems al re described. Such featuresincludespelli ng correction, processing of incomplete (ell ipt ic-~ I) input, jntfrrog-t ior of th p underlying language definition through
Natural Language Processing
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Attempt to process language like humansNatural language processing: receives and analyzes Natural language generating: performs function on given textMachine Translation was first area of research in NLP. Suggested by Warren WeaverFlaws in solely rearranging Abstract Information retrieval addresses the problem of finding those documents whose content matches a user's request from among a large collection of documents. Currently, the most successful general purpose retrieval methods are statistical methods that treat text as
Natural Language Processing
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ABSTRACT Natural Language Processing is a technique where mechine can become more human and there by reducing the distance between human being and the mechine can bereduced. Therefore in sinple sence NLP makes human to communicate withthe
A general organization of knowledge for natural language processing: The penman upper model
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Abstractgeneral, reusable computational resource has been developed within the penman text generation project for organizing domain knowledge appropriately for linguistic realization. This resource, called the upper model, provides a domain'and task-
Combining linguistic and statistical knowledge sources in natural-language processing for atis
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ABSTRACT During the past year, signi cant improvements have been made in the natural- language processing technology used in the SRI ATIS spoken-language understanding system. The principal developments have been (1) the incorporation of information from
Natural Language Processing
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CC conjunction, coordinating and both but either or CD numeral, cardinal mid-1890 nine- thirty 0.5 one DT determiner a all an every no that the EX existential there there FW foreign word gemeinschaft hund ich jeux IN preposition or conjunction, subordinating among
Natural Language Processing
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Decoder design is important: [Koehn et al. 03]For real MT models, this kind of dynamic program is a disaster (why)Standard solution
Natural Language Processing
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Abstract: This study describes Hidden Markov Model and its application in natural language process, first introduces the basic concept of Hidden Markov Model, then introduces the three basic issues and the basic algorithm to solve the problems, finally gives the
Natural Language Processing
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138 Vincenzo Lombardo and Patrick Sturt parser maintains a fully connected structure as each word is received in the input, without allowing partially structured input to be stored in a disconnected state (for examples of theories which assume strong incrementality, see
Natural Language Processing,
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Abstract The natural language processing's main object is to create programs capable of processing and understanding natural languages. Natural language refers to the language spoken or written by human beings, as opposed to artificial languages, computer,
Natural Language Processing
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Joseph Weizenbaum wrote the computer program Eliza in 1969 to demonstrate how easily people can be fooled into thinking that machines have some deep understanding. young woman: Men are all alike. eliza: In what way young woman: They're always bugging us
Natural Language Processing
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Humans rapidly and incrementally accumulate and integrate information from world and discourse context and the current utterance so as to interpret what someone is saying in real time. Often commit early. They can often finish each other's sentences!If a human
Natural Language Processing
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Demand-Driven NLP forIntroduction Why use NLP Architectures for using NLP Research Context The TAGARELA system Listening Reading Description Rephrasing Vocabulary Fill-in-Blank System Architecture NLP analysis modules Requirements
Natural language processing
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In the theory of linguistic morphology, morphemes are considered to be the smallest meaning-bearing elements of language, and they can be defined in a language- independent manner. It seems that even approximative automated morphological analysis
Natural Language Processing
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First, we learn word alignments, then we infer aligned phrases. Counting Phrase Pairs Gracias
Natural Language Processing
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For many NLP tasks, we can sidestep semantic analysis:Statistical MT: direct mapping target sentencesWSD: surface context features as proxy for semanticsBut some tasks require semantic reasoningQuestion answering What is the capital of
Natural Language Processing
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Authors and publishers who wish their publications to be considered for review in Computational Linguistics should send a copy to the book review editor, Graeme Hirst, Department of Computer Science, University of Toronto, Toronto, Canada M5S 3G4. All relevant books received
Natural language processing
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Page 1. NaturalLanguageProcessing Lecture 23 12/1/2015 Jim Martin Page 2. 12/1/15 Speech and LanguageProcessing Jurafsky and Martin 2 TodayScheduleQuiz 2 ReviewHW 3 QuestionsMachine translation framework StatisticalEvaluation methods
Natural Language Processing
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Page 1. NaturalLanguageProcessingMathematical and Computational Linguistics Foundations of Statistical NaturalLanguageProcessing, MIT Press, 1999. CS101 Win2015: Linguistics NaturalLanguageProcessing Page 3.
Natural Language Processing
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Page 1. CS 533: NaturalLanguageProcessing Lecture 01 1 CS 533: NaturalLanguage Processing Lecture 05 Hidden Markov and Max Entropy Models CS 533: NaturalLanguage ProcessingProfessor McCarty 2 TheoryMaximum Entropy Models
Hybrid connectionist natural language processing
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The objective of this book is to describe a new approach in hybrid connectionist natural language processing which bridges the gap between strictly symbolic and connectionist systems. This objective is tackled in two ways: the book gives an overview of hybrid Abstract Computer-based natural language processing is a multi-disciplinary field which is driven by several applications, including: 1. text understanding, 2. text composition and report generation, 3. machine translation from one language to another, 4. code
Natural Language Processing
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Page 1. 1 NATURALLANGUAGEPROCESSING (COM4513/6513) SYNTACTIC PARSING PART 2: TRANSITION-BASED DEPENDENCY PARSING a.vlachos@sheffield.ac.uk Andreas Vlachos Department of Computer Science University of Sheffield Page 2. 2
Natural Language Processing
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¦ Objective test items¦ constrained answer, to be selected among a set of alternatives¦ short answer (word or phrase) in response to a question¦ objective and impartial scoring¦
Natural language processing
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Page 1. NaturalLanguageProcessing Lecture 9 2/10/2015 Shumin Wu Page 2. 2/10/15 Speech and LanguageProcessing Jurafsky and Martin 2 TodayMore on HMMsReview statistical POS tagging3 HMM problems and algorithmsDecoding (Viterbi)
Natural language processing
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Page 1. NaturalLanguageProcessing NLP to Enhance Clinical Decision Support Peter Haug MD Intermountain Healthcare Page 2. Testing a Series of NLP Systems SPRUS SymText M-Plus Problem Identifier (MMTx) Problem Identifier (MMTx) Computable Ontologies
Natural Language Processing
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Page 1. 1 NaturalLanguageProcessing Classification I Dan Klein – UC Berkeley Page 2. 2 Classification Page 3. 3 ClassificationAutomatically make a decision about inputs Example: documentcategoryExample: image of digitdigit
Learning schemata for natural language processing
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ABSTRACT This paper describes a natural language system which improves its own performance through learning. The system processes short English narratives and is able to acquire, from a single narrative, a new schema for a stereotypical set of actions. During
Prolog for natural language processing
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As a discipline, NLP is not noted for its traditions. However, a welcome trend is beginning to emerge with the publication in the last three odd-numbered years of impressive texts on NLP and the Prolog programming language. First there was Pereira and Shieber's (1987)
Natural language processing and systems biology
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Natural language processing (NLP) is the processing, or treatment by computer, of natural language, ie, human languages, as opposed to programming languages. The two differ from each other in a very fundamental way: the interpretation of a programming language is
A large subcategorization lexicon for natural language processingapplications
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Abstract We introduce a large computational subcategorization lexicon which includes subcategorization frame (SCF) and frequency information for 6,397 English verbs. This extensive lexicon was acquired automatically from five corpora and the Web using the
Using natural language processing and discourse features to identify understanding errors in a spoken dialogue system
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Abstract While it has recently become possible to build spoken dialogue systems that interact with users in real-time in a range of domains, systems that support conversational natural language are still subject to a large number of spoken language understanding (
Coh-Metrix: An automated tool for theoretical and applied natural language processing
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Abstract Coh-Metrix provides indices for the characteristics of texts on multiple levels of analysis, including word characteristics, sentence characteristics, and the discourse relationships between ideas in text. Coh-Metrix was developed to provide a wide range of
Natural Language Processing in Information Retrieval.
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Abstract Many Natural Language Processing (NLP) techniques have been used in Information Retrieval. The results are not encouraging. Simple methods (stopwording, porter- style stemming, etc.) usually yield significant improvements, while higher-level processing
Building Natural Language Generation Systems. Studies in Natural Language Processing
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This book explains how to build Natural Language Generation (NLG) systems--computer software systems that automatically generate understandable texts in English or other human languages. NLG systems use knowledge about language and the application
Natural language processing with Thought Treasure
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When the Dartmouth Summer Research Project on Artificial Intelligence was held in 1956, the creation of an intelligent computer seemed to be just around the corner. Since then, the number of researchers in the field has grown to over 10,000 and the number of pages in
Word Formation in Natural Language Processing Systems.
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ABSTRACT Systems which process natural language require a reliable source of information about words. Not only must their lexical subsystems handle a large known words; they must also cope with The morphologicalprincipl esunderlying" possible word"
Web Text Corpus for Natural Language Processing.
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Abstract Web text has been successfully used as training data for many NLP applications. While most previous work accesses web text through search engine hit counts, we created a Web Corpus by downloading web pages to create a topic-diverse collection of 10 billion
Using natural language processing for identifying and interpreting tables in plain text
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Documents in many technical domains express much of their content in tabular form. Natural language processing applications in such domains need table interpretation functions to make this information available. Our work on information extraction in plain textlegacy
A comparative study of parameter estimation methods for statistical natural language processing
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Abstract This paper presents a comparative study of five parameter estimation algorithms on four NLP tasks. Three of the five algorithms are well-known in the computational linguistics community: Maximum Entropy (ME) estimation with L2 regularization, the Averaged
ClearTK: A UIMA toolkit for statistical natural language processing
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Abstract This paper describes a toolkit, ClearTK, which was developed at the Center for Computational Language and Education Research at the University of Colorado at Boulder. ClearTK is a framework that supports statistical natural language processing and
Name-It: Naming and Detecting Faces in Video the Integration of Image andNatural Language Processing
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Abstract We have been developing Name-It, a system that associates faces and names in news videos. First, as the only knowledge source, the system is given news videos which include image sequences and transcripts obtained from audio tracks or closed caption
On Natural Language Processing and Plan Recognition.
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Abstract The research areas of plan recognition and natural language parsing share many common features and even algorithms. However, the dialog between these two disciplines has not been effective. Specifically, significant recent results in parsing mildly context
Natural language processing for requirements engineering: Applicability to large requirements documents
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Abstract This paper describes a case study on application of natural language processing in very early stages of software development. At this early stage it is very important for the domain expert (who is, most probably, the future user) and the software expert to define a
Natural language processing in the faq finder system: Results and prospects
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Abstract This paper describes some recent results regarding the employment of natural language processing techniques in the FAQ FINDER system. FAQ FINDER is a natural language question-answering system that uses files of frequently-asked questions as its
The (non) necessity of recursion in natural language processing
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Abstract The prima facie unbounded nature of natural language, contrasted with the finite character of our memory and computational resources, is often taken to warrant a recursive language processing mechanism. The widely held distinction between an idealized
Rule-based approach in Arabic natural language processing
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Abstract:The rule-based approach has successfully been used in developing many natural language processing systems. Systems that use rule-based transformations are based on a core of solid linguistic knowledge. The linguistic knowledge acquired for one natural
An introduction to natural language processing through Prolog
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It may seem unusual for the author of a directly competing textbook (Covington 1994) to review this one---but in fact the competition is not head-on. My book introduces Prolog programmers to natural language, whereas this book introduces linguists to Prolog
Combining machine learning and natural language processing for automatic keyword extraction
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Automatic key w ord ex traction is the task of automatically selectin ga small set of terms describ in g the content of a sin g le document. T hat a key-w ord is ex tracted means that it is present ver b atim in the document to w hich it is assig ned. T his dissertation discusses
Machine learning and natural language processing
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Abstract In this report, some collaborative work between the fields of Machine Learning (ML) and Natural Language Processing (NLP) is presented. The document is structured in two parts. The first part includes a superficial but comprehensive survey covering the state-of-
Domain adaptation of natural language processing systems
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Statistical language processing tools are being applied to an ever wider and more varied range of linguistic data. Researchers and engineers are using statistical models to organize and understand financial news, legal documents, biomedical abstracts, and weblog
Some applications of natural language processing to the field of augmentative and alternative communication
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Augmentative and Alternative Communication (AAC) is the field of study concerned with providing devices or techniques to augment the communicative ability of a person whose disability makes it difficult to speak in an understandable fashion. A variety of AAC devices
Comparing natural language processing tools to extract medical problems from narrative text.
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Abstract To help maintain a complete, accurate and timely Problem List, we are developing a system to automatically retrieve medical problems from free-text documents. This system uses Natural Language Processing to analyze all electronic narrative text documents in a
Upper modeling: A general organization of knowledge for natural language processing
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Abstract A general, reusable computational resource has been developed within the Penman text generation project for organizing domain knowledge appropriately for linguistic realization. This resource, called the upper model, provides a domain-and task-
Resources for Arabic natural language processing
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Problem: Lack of adequate supply of resources stands as an impediment to language development.Solution: Build non-profit language resource center to promote language development through the sharing of resourcesAcquire specialized equipment, develop
A comparative study of current Clinical Natural Language Processingsystems on handling abbreviations in discharge summaries.
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Abstract Clinical Natural Language Processing (NLP) systems extract clinical information from narrative clinical texts in many settings. Previous research mentions the challenges of handling abbreviations in clinical texts, but provides little insight into how well current NLP
Natural Language Processing for patents analysis and classification
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Abstract The availability of huge amount of data from a bewildering variety of sources leads to the well-identified nowadays paradox: an overload of information means no usable knowledge. Text Mining and Knowledge Management technologies are therefore
36. NATURAL LANGUAGE PROCESSING IN COMPUTER-ASSISTEDLANGUAGE LEARNING
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Abstract This chapter examines the application of natural language processing to computerassisted language learning including the history of work in this field over the last
Natural language processing in Virtual Reality training environments
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ABSTRACT Technological advances in areas such as transportation, communications, and science are rapidly changing our world--the rate of change will only increase in the 21st century. Innovations in training will be needed to meet these new requirements. Not only
Empirical data on corpus design and usage in biomedical natural language processing.
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Abstract This paper describes the designs of six publicly available biomedical corpora. We then present usage data for the six corpora. We show that corpora that are carefully annotated with respect to structural and linguistic characteristics and that are distributed in
Natural language processing and information retrieval.
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The PC came, bringing distributed processing to the desktop users used tools themselves, directly, users started/wanted to do IR, users got comfortable with the autocontent wizard in PowerPoint etc, and now demand more from IRThe volume of data
Using natural language processing to improve accuracy of automated notifiable disease reporting.
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Abstract We examined whether using a natural language processing (NLP) system results in improved accuracy and completeness of automated electronic laboratory reporting (ELR) of notifiable conditions. We used data from a community-wide health information exchange
The gene ontology as a source of lexical semantic knowledge for a biologicalnatural language processing application
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ABSTRACT Mappings between the Gene Ontology (GO) and terms found in a corpus of selected Medline abstracts are studied as a means to augment the lexicon for a text processing application, and as a source of lexical semantic knowledge. We perform an
Deeper natural language processing for evaluating student answers in intelligent tutoring systems
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Abstract This paper addresses the problem of evaluating students' answers in intelligent tutoring environments with mixed-initiative dialogue by modelling it as a textual entailment problem. The problem of meaning representation and inference is a pervasive challenge
Linguistics and natural language processing
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Introduction The paper addresses the issue of cooperation between linguistics and natural language processing (NLP), in general, and between linguistics and machine translation (MT), in particular. It focuses on just one direction of such cooperation, namely applications of
IceNLP: a natural language processing toolkit for icelandic.
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Abstract Icelandic is a morphologically complex language, for which language technology resources are scarce. Only a few years ago, it could be stated that language technology was practically non-existent in Iceland. In this paper, we describe the development of an NLP
Suffix array and its applications in empirical natural language processing
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A1: how do you say how do you do in chinese A2: do you say how do you do in chinese A3: you say how do you do in chinese A4: say how do you do in chinese A5: how do you do in chinese A6: do you do in chinese A7: you do in chinese A8: do in chinese A9: in chinese
Medical facts to support inferencing in natural language processing.
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We report on the use of medical facts to support the enhancement of natural language processing of biomedical text. Inferencing in semantic interpretation depends on a fact repository as well as an ontology. We used statistical methods to construct a repository of drug-disorder co- IFSR was established to stimulate all activities associated with the scientific study of systems and to coordinate such activities at international level. The aim of this series is to stimulate publication of high-quality monographs and textbooks on various topics of
Unsupervised and Knowledge-free Natural Language Processing in the Structure Discovery Paradigm.
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Abstract After almost 60 years of attempts to implement natural language competence on machines, there is still no automatic language processing system that comes even close to human language performance. The fields of Computational Linguistics and Natural
Description logics for natural language processing
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Abstract This paper surveys in short the activity of the Knowledge Representation and Reasoning group at IRST for Natural Language Processing. We have developed two Description Logic based systems to be used in large Natural Language dialogue
Towards an open-domain conversational system fully based on natural language processing.
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Abstract This paper proposes an architecture for an open-domain conversational system and evaluates an implemented system. The proposed architecture is fully composed of modules based on natural language processing techniques. Experimental results using
Facilitating research in pathology using natural language processing.
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Abstract. Clinical research projects frequently rely on manual extraction of information from pathology reports, which is a costly and time-consuming process. This paper describes use of a natural language processing (NLP) system to automatically extract and structure
Graphical query composition and natural language processing in an RDF visualization interface
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44 4 NaturalLanguageProcessing 46 4.1 Introduction . . . . .4.2.3 The Challenge of NaturalLanguageProcessing . . . . . 49 4.3 The Scope of NaturalLanguageProcessing . . . . . 49 4.4 Areas of NaturalLanguageProcessing . . . . .
Hdrug, A flexible and extendible development environment for natural language processing
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Hdrug is an environment to develop grammars, parsers and generators for natural languages. The package is written in Sicstus Prolog and Tcl/Tk. The system provides a graphical user interface with a command interpreter, and a number of visualisation tools,
Improving the sensitivity of the problem list in an intensive care unit by usingnatural language processing
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Abstract To improve the completeness of an electronic problem list, we have developed a system using Natural Language Processing to automatically extract potential medical problems from clinical freetext documents; these problems are then proposed for inclusion
An Overview of Corpus-Based Statistics-Oriented (CBSO) Techniques forNatural Language Processing
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* Department of Electrical Engineering National Tsing-Hua University Hsinchu, Taiwan 300, ROC Advanced Technology Center, Computercommunication Research Laboratories, Industrial Technology Research Institute Chutung, Hsinchu, Taiwan 310, ROC email: kysu
Integrating natural language, knowledge representation and reasoning, and analogical processing to learn by reading
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Abstract Learning by reading requires integrating several strands of AI research. We describe a prototype system, Learning Reader, which combines natural language processing, a large-scale knowledge base, and analogical processing to learn by reading
The description of adjectives for natural language processing: Theoretical and applied perspectives
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Abstract Adjectives constitute a challenging issue for NLP applications.¿ From a syntactic viewpoint, they can be predicative or attributive. From a semantic viewpoint, their sense can vary depending on the context in which they appear. In this paper we present an overview
Applied natural language processing
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As far as successful engineering of artificial intelligence concepts and their commercial impact is concerned, expert system technology has attracted the interest of those people currently involved in the AI business. Shwartz's book, however, deals with an entirely
DiET-Diagnostic and Evaluation Tools for natural language processingapplications
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Abstract The project DiET is developing a comprehensive environment for the construction, annotation and maintenance of structured reference data for the diagnosis and evaluation of NLP applications.target user group are developers, professional evaluators and
Learning probabilistic lexicalized grammars for natural language processing
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Page 1. Learning Probabilistic Lexicalized Grammars for NaturalLanguageProcessing Rebecca Hwa Harvard University rebecca@eecs.harvard.edu Page 2. Grammar InductionLearning a tractable representation of linguistic structures for naturallanguage
An appfication of natural language processing to domain modeliing: Two case studies
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Abstract This paper describes an approach for analysis of natural language requirements documents and two case studies conducted to prove the feasibility of the approach. The goal of the analysis is to define a common language understood both by the domain expert and
Building an automated problem list based on natural language processing: lessons learned in the early phase of development.
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Abstract Detailed problem lists that comply with JCAHO requirements are important components of electronic health records. Besides improving continuity of care electronic problem lists could serve as foundation infrastructure for clinical trial recruitment, research,
Natural Language Processing: a historical review
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Abstract This paper reviews natural language processing (NLP) from the late 1940's to the present, seeking to identify its successive trends as these reflect concerns with different problems or the pursuit of different approaches to solving these problems and building
A comparison of semantic categories of the ISO reference terminology models for nursing and the MedLEE natural language processing system
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Abstract Natural language processing (NLP) systems have demonstrated utility in parsing narrative texts for purposes such as surveillance and decision support. However, there has been little work related to NLP of nursing narratives. The purpose of this study was to
A logical language for natural language processing
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Abstract We present a formal description of a logical language that is based on a propositional semantic network. Variables in this language are not atomic and have potentially complex structure. We start from the individual components of a semantic CSE PROJECTS