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NLP-Driven Document Representations for Text Ca...
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NLP-Driven Document Representations for Text Categorization ab 48.99 € als Taschenbuch: Empirical Selection of NLP-Driven Document Representations for Text Categorization. Aus dem Bereich: Bücher, English, International, Gebundene Ausgaben,

Anbieter: hugendubel
Stand: 18.02.2020
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NLP-Driven Document Representations for Text Ca...
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NLP-Driven Document Representations for Text Categorization ab 48.99 EURO Empirical Selection of NLP-Driven Document Representations for Text Categorization

Anbieter: ebook.de
Stand: 18.02.2020
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Principle of Morphological Analysis for Kokboro...
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Coverage of this contains as meaning of NLP, Morphology, Stammer, Language importance with the integration of Computer. The main description is the Natural language processing (NLP) which is a subfield of artificial intelligence and linguistics. It studies the problems of automated generation and understanding of natural human languages. Natural language generation systems convert information from computer databases into normal-sounding human language, and natural language understanding systems convert samples of human language into more formal representations that are easier for computer programs to manipulate. Machine translation is a very important application of Natural Language Processing (NLP). Machine translation is throwing up many challenges and opening up many opportunities for doing work. Some of the problems relate to grammars, others pertain to word analysis, bilingual dictionaries, language, generation,

Anbieter: Dodax
Stand: 18.02.2020
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NLP-Driven Document Representations for Text Ca...
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Text Categorization is the task of assigning predefined labels to textual documents. Current research has been focused on using word based representations called bag-of-words (BOW) with strong statistical learners. Few studies have explored the use of more complex Natural Language Processing (NLP) driven representations based on phrases, proper names and word senses. None of these had definitive results on these features? benefits for text categorization problems. This book studies the use of NLP-driven document representations captured at many different levels of language processing, and shows that NLP-driven document representations improve text categorization. A methodology, called ?Empirical Selection Methodology for NLP-driven document representations?, is presented. Methodology helps to select document representations for each category in the categorization problem. The methodology should help Text Categorization researchers as well as researchers working on other classification problems, because it is generalizable, and can produce better instance representations for different learning problems.

Anbieter: Dodax
Stand: 18.02.2020
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Empirical Methods in Natural Language Generation
74,89 € *
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Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.

Anbieter: Dodax
Stand: 18.02.2020
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Integration of Natural Language and Vision Proc...
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Although there has been much progress in developing theories, models and systems in the areas of Natural Language Processing (NLP) and Vision Processing (VP), there has heretofore been little progress on integrating these two subareas of Artificial Intelligence (AI). This book contains a set of edited papers addressing theoretical issues and the grounding of representations in NLP and VP from philosophical and psychological points of view. The papers focus on site descriptions such as the reasoning work on space at Leeds, UK, the systems work of the ILS (Illinois, U.S.A.) and philosophical work on grounding at Torino, Italy, on Schank's earlier work on pragmatics and meaning incorporated into hypermedia teaching systems, Wilks' visions on metaphor, on experimental data for how people fuse language and vision and theories and computational models, mainly connectionist, for tackling Searle's Chinese Room Problem and Harnad's Symbol Grounding Problem. The Irish Room is introduced as a mechanism through which integration solves the Chinese Room. The U.S.A., China and the EU are well reflected, showing the fact that integration is a truly international issue. There is no doubt that all of this will be necessary for the SuperInformationHighways of the future.

Anbieter: Orell Fuessli CH
Stand: 18.02.2020
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Principle of Morphological Analysis for Kokboro...
79,90 CHF *
ggf. zzgl. Versand

Coverage of this contains as meaning of NLP, Morphology, Stammer, Language importance with the integration of Computer. The main description is the Natural language processing (NLP) which is a subfield of artificial intelligence and linguistics. It studies the problems of automated generation and understanding of natural human languages. Natural language generation systems convert information from computer databases into normal-sounding human language, and natural language understanding systems convert samples of human language into more formal representations that are easier for computer programs to manipulate. Machine translation is a very important application of Natural Language Processing (NLP). Machine translation is throwing up many challenges and opening up many opportunities for doing work. Some of the problems relate to grammars; others pertain to word analysis, bilingual dictionaries, language, generation,

Anbieter: Orell Fuessli CH
Stand: 18.02.2020
Zum Angebot
Empirical Methods in Natural Language Generation
116,00 CHF *
ggf. zzgl. Versand

Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.

Anbieter: Orell Fuessli CH
Stand: 18.02.2020
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LMF Lexical Markup Framework
115,00 CHF *
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The community responsible for developing lexicons for Natural Language Processing (NLP) and Machine Readable Dictionaries (MRDs) started their ISO standardization activities in 2003. These activities resulted in the ISO standard Lexical Markup Framework (LMF). After selecting and defining a common terminology, the LMF team had to identify the common notions shared by all lexicons in order to specify a common skeleton (called the core model) and understand the various requirements coming from different groups of users. The goals of LMF are to provide a common model for the creation and use of lexical resources, to manage the exchange of data between and among these resources, and to enable the merging of a large number of individual electronic resources to form extensive global electronic resources. The various types of individual instantiations of LMF can include monolingual, bilingual or multilingual lexical resources. The same specifications can be used for small and large lexicons, both simple and complex, as well as for both written and spoken lexical representations. The descriptions range from morphology, syntax and computational semantics to computer-assisted translation. The languages covered are not restricted to European languages, but apply to all natural languages. The LMF specification is now a success and numerous lexicon managers currently use LMF in different languages and contexts. This book starts with the historical context of LMF, before providing an overview of the LMF model and the Data Category Registry, which provides a flexible means for applying constants like /grammatical gender/ in a variety of different settings. It then presents concrete applications and experiments on real data, which are important for developers who want to learn about the use of LMF. Contents 1. LMF Historical Context and Perspectives, Nicoletta Calzolari, Monica Monachini and Claudia Soria. 2. Model Description, Gil Francopoulo and Monte George. 3. LMF and the Data Category Registry: Principles and Application, Menzo Windhouwer and Sue Ellen Wright. 4. Wordnet-LMF: A Standard Representation for Multilingual Wordnets, Piek Vossen, Claudia Soria and Monica Monachini. 5. Prolmf: A Multilingual Dictionary of Proper Names and their Relations, Denis Maurel, B atrice Bouchou-Markhoff. 6. LMF for Arabic, Aida Khemakhem, Bilel Gargouri, Kais Haddar and Abdelmajid Ben Hamadou. 7. LMF for a Selection of African Languages, Chantal Enguehard and Mathieu Mangeot. 8. LMF and its Implementation in Some Asian Languages, Takenobu Tokunaga, Sophia Y.M. Lee, Virach Sornlertlamvanich, Kiyoaki Shirai, Shu-Kai Hsieh and Chu-Ren Huang. 9. DUELME: Dutch Electronic Lexicon of Multiword Expressions, Jan Odijk. 10. UBY-LMF Exploring the Boundaries of Language-Independent Lexicon Models, Judith Eckle-Kohler, Iryna Gurevych, Silvana Hartmann, Michael Matuschek and Christian M. Meyer. 11. Conversion of Lexicon-Grammar Tables to LMF: Application to French, ric Laporte, Elsa Tolone and Matthieu Constant. 12. Collaborative Tools: From Wiktionary to LMF, for Synchronic and Diachronic Language Data, Thierry Declerck, Pirsoka Lendvai and Karlheinz M rth. 13. LMF Experiments on Format Conversions for Resource Merging: Converters and Problems, Marta Villegas, Muntsa Padr and N ria Bel. 14. LMF as a Foundation for Servicized Lexical Resources, Yoshihiko Hayashi, Monica Monachini, Bora Savas, Claudia Soria and Nicoletta Calzolari. 15. Creating a Serialization of LMF: The Experience of the RELISH Project, Menzo Windhouwer, Justin Petro, Irina Nevskaya, Sebastian Drude, Helen Aristar-Dry and Jost Gippert. 16. Global Atlas: Proper Nouns, From Wikipedia to LMF, Gil Francopoulo, Fr d ric Marcoul, David Cau

Anbieter: Orell Fuessli CH
Stand: 18.02.2020
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