Natural language

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  • Logic programming, an important new method of compute programming resulting from recent research in artifucial intelligence and computer science, has proved to be especially appropriate for solving problems in natrual-language processing. "Prolog and Natural Language Analysis" provides a concise and practical introduction to logic programming and the logic-programming language Prolog both as vehicles for understanding elementary computational linguistics and as tools for implementing the basic components of natural-language-processing systems....

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  • BOOK DESCRIPTION This book offers a highly accessible introduction to Natural Language Processing, the field that underpins a variety of language technologies, ranging from predictive text and email filtering to automatic summarization and translation. With Natural Language Processing with Python, you’ll learn how to write Python programs to work with large collections of unstructured text. You’ll access richly-annotated datasets using a comprehensive range of linguistic data structures.

    pdf504p hoa_can 26-01-2013 33 12   Download

  • Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don’t need any programming or linguistics experience to get started.

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  • In the following we give an account of a computer program for the translation of natural languages. The program has the following features: (1) it is adaptable to the translation of any two natural languages, not just to some particular pair; (2) it is a self-modifying program—that is, given the information that it has produced an incorrect translation, together with the translation which it should have produced according to the linguistic judgment of an operator, it will modify itself so as to eliminate the cause of the incorrect translation....

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  • We present a natural language generation approach which models, exploits, and manipulates the non-linguistic context in situated communication, using techniques from AI planning. We show how to generate instructions which deliberately guide the hearer to a location that is convenient for the generation of simple referring expressions, and how to generate referring expressions with context-dependent adjectives.

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  • This demonstration presents the Annotation Librarian, an application programming interface that supports rapid development of natural language processing (NLP) projects built in Apache Unstructured Information Management Architecture (UIMA). The flexibility of UIMA to support all types of unstructured data – images, audio, and text – increases the complexity of some of the most common NLP development tasks.

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  • The Natural Language Toolkit is a suite of program modules, data sets and tutorials supporting research and teaching in computational linguistics and natural language processing. NLTK is written in Python and distributed under the GPL open source license. Over the past year the toolkit has been rewritten, simplifying many linguistic data structures and taking advantage of recent enhancements in the Python language. This paper reports on the simplified toolkit and explains how it is used in teaching NLP....

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  • For a natural language access to database system to be practical it must achieve a good match between the capabilities of the user and the requirements of the task. The user brings his own natural language and his own style of interaction to the system. The task brings the questions that must be answered and the database domaln+s semantics. All natural language access systems achieve some degree of success. But to make progress as a field, we need to be able to evaluate the degree of this success. For too long, the best we have menaged has been to...

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  • In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (b) a lower accuracy than traditional attribute/value methods. In this paper, we show that tree kernels are very helpful in the processing of natural language as (a) we provide a simple algorithm to compute tree kernels in linear average running time and (b) our study on the classification properties of diverse tree kernels show that kernel combinations always improve the traditional methods. ...

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  • This opinion paper discusses subjective natural language problems in terms of their motivations, applications, characterizations, and implications. It argues that such problems deserve increased attention because of their potential to challenge the status of theoretical understanding, problem-solving methods, and evaluation techniques in computational linguistics. The author supports a more holistic approach to such problems; a view that extends beyond opinion mining or sentiment analysis.

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  • We present Wikulu1 , a system focusing on supporting wiki users with their everyday tasks by means of an intelligent interface. Wikulu is implemented as an extensible architecture which transparently integrates natural language processing (NLP) techniques with wikis. It is designed to be deployed with any wiki platform, and the current prototype integrates a wide range of NLP algorithms such as keyphrase extraction, link discovery, text segmentation, summarization, or text similarity.

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  • To improve the interaction between students and an intelligent tutoring system, we developed two Natural Language generators, that we systematically evaluated in a three way comparison that included the original system as well. We found that the generator which intuitively produces the best language does engender the most learning. Specifically, it appears that functional aggregation is responsible for the improvement.

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  • In this paper we present a new approach to controlling the behaviour of a natural language generation system by correlating internal decisions taken during free generation of a wide range of texts with the surface stylistic characteristics of the resulting outputs, and using the correlation to control the generator. This contrasts with the generate-andtest architecture adopted by most previous empirically-based generation approaches, offering a more efficient, generic and holistic method of generator control. ...

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  • The Natural Language Understanding Engine Test Environment (ETE) is a GUI software tool that aids in the development and maintenance of large, modular, natural language understanding (NLU) systems. Natural language understanding systems are composed of modules (such as partof-speech taggers, parsers and semantic analyzers) which are difficult to test individually because of the complexity of their output data structures.

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  • Knowledge acquisition is a serious bottleneck for natural language understanding systems. For this reason, large-scale linguistic resources have been compiled and made available by organizations such as the Linguistic Data Consortium (Comlex) and Princeton University (WordNet). Systems making use of these resources can greatly accelerate the development process by avoiding the need for the developer to re-create this information. In this paper we describe how we integrated these large scale linguistic resources into our natural language understanding system. ...

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  • This paper describes an all level approach on statistical natural language translation (SNLT). W i t h o u t any predefined knowledge the system learns a statistical translation lexicon (STL), word classes (WCs) and translation rules (TRs) from a parallel corpus thereby producing a generalized form of a word alignment (WA). The translation process itself is realized as a beam search.

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  • This paper reports on the ESPRIT project MELISSA (Methods and Tools for NaturalLanguage Interfacing with Standard Software Applications) ~. MELISSA aims at developing the technology and tools enabling end users to interface with computer applications, using natural-language (NL), and to obtain a precompetitive product validated in selected enduser applications. This paper gives an overview of the approach to solving (NL) interfacing problem and outlines some of the methods and software components developed in the project. ...

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  • The system achieves conceptual generation using a discourse schema system [McKnent selects items from a knowledge base and orders them ewon 1985, Paris 1985]; stylistic generation will be ruleinto a message to address some discourse goal. This mes- based. The revision component will review the generated sage is passed to the stylistic component that makes lex- text and produce recommendations to the conceptual and ical and syntactic choices to produce a natural language stylistic components as to how to improve the text. ...

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  • We developed a prototype information retrieval system which uses advanced natural language processing techniques to enhance the effectiveness of traditional key-word based document retrieval. The backbone of our system is a statistical retrieval engine which performs automated indexing of documents, then search and ranking in response to user queries. This core architecture is augmented with advanced natural language processing tools which are both robust and efficient.

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  • This hybrid system participated in the 1993 ATIS natural language evaluation. Although only four months old, the scores achieved by the combined system were quite respectable. Because of differences between language understanding and speech recognition, significant changes are required in the hidden Markov model methodology. Unlike speech, where each phoneme results in a local sequence of spectra, the relation between the meaning of a sentence and the sequence of words is not a simple linear sequential model. ...

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