Emerging Applications of Natural Language Processing: Concepts and New Research, Sivaji Bandyopadhyay, Sudip Kumar Naskar, Asif Ekbal
Автор: Lin Название: Natural Language Understanding and Intelligent Applications ISBN: 3319504959 ISBN-13(EAN): 9783319504957 Издательство: Springer Рейтинг: Цена: 98760.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book constitutes the joint refereed proceedings of the 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and the 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, held in Kunming, China, in December 2016.
The 48 revised full papers presented together with 41 short papers were carefully reviewed and selected from 216 submissions. The papers cover fundamental research in language computing, multi-lingual access, web mining/text mining, machine learning for NLP, knowledge graph, NLP for social network, as well as applications in language computing.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 76690.00 T Наличие на складе: Нет в наличии. Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Автор: Mbarki Название: Formalizing Natural Languages with NooJ and Its Natural Language Processing Applications ISBN: 3319734199 ISBN-13(EAN): 9783319734194 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 11th International Conference, NooJ 2017, held in Kenitra and Rabat, Morocco, in May 2017. The 20 revised full papers presented in this volume were carefully reviewed and selected from 56 submissions.
Автор: Khaled Shaalan; Aboul Ella Hassanien; Fahmy Tolba Название: Intelligent Natural Language Processing: Trends and Applications ISBN: 3319670557 ISBN-13(EAN): 9783319670553 Издательство: Springer Рейтинг: Цена: 232910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Features Extraction and On-Line Recognition of Isolated Arabic Characters.- Using Text Mining Techniques for Extracting Information from Research Articles.- Authorship and Time Attribution of Arabic Texts Using JGAAP.- TALAA-ATSF: A Global Operation-Based Arabic Text Summarization Framework.- e="Calibri">An Evaluation of the Morphological Analysis of Egyptian Arabic TreeBank.- Alserag: An Automatic Diacritization System for Arabic.- font-size:11.0pt; line-height:107%;font-family: "Calibri","sans-serif";mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri;mso-fareast-theme-font: minor-latin;mso-hansi-theme-font: minor-latin;mso-bidi-font-family: Arial;mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US;mso-fareast-language: EN-US;mso-bidi-language: AR-SA">Developing a Transfer-based System for Arabic Dialects Translation.- Education and Knowledge Based Augmented Reality (AR).- 7%;font-family: "Calibri","sans-serif";mso-ascii-theme-font: minor-latin; mso-fareast-font-familyText Mining and Analytics: A Case Study from Channels Posts on Facebook.- A New Semantic Distance Measure for the VSM-Based Information Retrieval Systems.-family: "Calibri","sans-serif";mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri;mso-fareast-theme-font: minor-latin;mso-hansi-theme-font: minor-latin;mso-bidi-font-family: Arial;mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US;mso-fareast-language: EN-US;mso-bidi-language: AR-SA">
Автор: V. Santhi, D.P. Acharjya, M. Ezhilarasan Название: Emerging Technologies in Intelligent Applications for Image and Video Processing ISBN: 1466696850 ISBN-13(EAN): 9781466696853 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 228230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents current research relating to multimedia technologies including video and image restoration and enhancement as well as algorithms used for image and video compression, indexing and retrieval processes, and security concerns. It features insight from researchers from around the world.
Автор: Abhijit Mishra, Pushpak Bhattacharyya Название: Cognitively Inspired Natural Language Processing ISBN: 9811315159 ISBN-13(EAN): 9789811315152 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows ways of augmenting the capabilities of Natural Language Processing (NLP) systems by means of cognitive-mode language processing.
Автор: Yingxu Wang Название: Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications ISBN: 1466617438 ISBN-13(EAN): 9781466617438 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 189420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications covers the intricate worlds of thought, comprehension, intelligence, and knowledge through the scientific field of Cognitive Science. This groundbreaking reference contains research from global experts, covering topics that have been pivotal at major conferences covering Cognitive Science topics.
Автор: Lucia Specia, Carolina Scarton, Gustavo Henrique Paetzold Название: Quality Estimation for Machine Translation ISBN: 1681733757 ISBN-13(EAN): 9781681733753 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 87780.00 T Наличие на складе: Невозможна поставка. Описание: Many applications within natural language processing involve performing text-to-text transformations, i.e., given a text in natural language as input, systems are required to produce a version of this text (e.g., a translation), also in natural language, as output. Automatically evaluating the output of such systems is an important component in developing text-to-text applications. Two approaches have been proposed for this problem: (i) to compare the system outputs against one or more reference outputs using string matching-based evaluation metrics and (ii) to build models based on human feedback to predict the quality of system outputs without reference texts. Despite their popularity, reference-based evaluation metrics are faced with the challenge that multiple good (and bad) quality outputs can be produced by text-to-text approaches for the same input. This variation is very hard to capture, even with multiple reference texts. In addition, reference-based metrics cannot be used in production (e.g., online machine translation systems), when systems are expected to produce outputs for any unseen input. In this book, we focus on the second set of metrics, so-called Quality Estimation (QE) metrics, where the goal is to provide an estimate on how good or reliable the texts produced by an application are without access to gold-standard outputs. QE enables different types of evaluation that can target different types of users and applications. Machine learning techniques are used to build QE models with various types of quality labels and explicit features or learnt representations, which can then predict the quality of unseen system outputs. This book describes the topic of QE for text-to-text applications, covering quality labels, features, algorithms, evaluation, uses, and state-of-the-art approaches. It focuses on machine translation as application, since this represents most of the QE work done to date. It also briefly describes QE for several other applications, including text simplification, text summarization, grammatical error correction, and natural language generation.
Автор: Manfred Stede, Jodi Schneider Название: Argumentation Mining ISBN: 1681734613 ISBN-13(EAN): 9781681734613 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 97950.00 T Наличие на складе: Невозможна поставка. Описание: Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications at the major conferences and journals of the field. Its goals are to identify argumentation in text or dialogue; to construct representations of the constellation of claims, supporting and attacking moves (in different levels of detail); and to characterize the patterns of reasoning that appear to license the argumentation. Furthermore, recent work also addresses the difficult tasks of evaluating the persuasiveness and quality of arguments. Some of the linguistic genres that are being studied include legal text, student essays, political discourse and debate, newspaper editorials, scientific writing, and others.The book starts with a discussion of the linguistic perspective, characteristics of argumentative language, and their relationship to certain other notions such as subjectivity.Besides the connection to linguistics, argumentation has for a long time been a topic in Artificial Intelligence, where the focus is on devising adequate representations and reasoning formalisms that capture the properties of argumentative exchange. It is generally very difficult to connect the two realms of reasoning and text analysis, but we are convinced that it should be attempted in the long term, and therefore we also touch upon some fundamentals of reasoning approaches.Then the book turns to its focus, the computational side of mining argumentation in text. We first introduce a number of annotated corpora that have been used in the research. From the NLP perspective, argumentation mining shares subtasks with research fields such as subjectivity and sentiment analysis, semantic relation extraction, and discourse parsing. Therefore, many technical approaches are being borrowed from those (and other) fields. We break argumentation mining into a series of subtasks, starting with the preparatory steps of classifying text as argumentative (or not) and segmenting it into elementary units. Then, central steps are the automatic identification of claims, and finding statements that support or oppose the claim. For certain applications, it is also of interest to compute a full structure of an argumentative constellation of statements. Next, we discuss a few steps that try to 'dig deeper': to infer the underlying reasoning pattern for a textual argument, to reconstruct unstated premises (so-called 'enthymemes'), and to evaluate the quality of the argumentation. We also take a brief look at 'the other side' of mining, i.e., the generation or synthesis of argumentative text.The book finishes with a summary of the argumentation mining tasks, a sketch of potential applications, and a-necessarily subjective-outlook for the field.
Автор: Srinivasa-Desikan Bhargav Название: Natural Language Processing and Computational Linguistics ISBN: 178883853X ISBN-13(EAN): 9781788838535 Издательство: Неизвестно Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discover how you can perform your own modern text analysis, to make predictions, create inferences, and gain insights about the data around you today. Learn how to harness the powerful Python ecosystem and tools such as spaCy and Gensim to perform natural language processing, and computational linguistics algorithms.
Автор: Edited By Milind Tam Название: Artificial intelligence and social work ISBN: 1108425992 ISBN-13(EAN): 9781108425995 Издательство: Cambridge Academ Рейтинг: Цена: 121440.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: For students, academic researchers, industry leaders, and practitioners, this introductory guide shows how social work and artificial intelligence can be combined for the greater good. Real-life examples of work with homeless youth, diabetes patients, and other interventions provide inspiration for readers to apply such methods to their own work.
Автор: Stede Manfred, Schneider Jodi Название: Argumentation Mining ISBN: 1681734591 ISBN-13(EAN): 9781681734590 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 76690.00 T Наличие на складе: Невозможна поставка. Описание: Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications at the major conferences and journals of the field. Its goals are to identify argumentation in text or dialogue; to construct representations of the constellation of claims, supporting and attacking moves (in different levels of detail); and to characterize the patterns of reasoning that appear to license the argumentation. Furthermore, recent work also addresses the difficult tasks of evaluating the persuasiveness and quality of arguments. Some of the linguistic genres that are being studied include legal text, student essays, political discourse and debate, newspaper editorials, scientific writing, and others.The book starts with a discussion of the linguistic perspective, characteristics of argumentative language, and their relationship to certain other notions such as subjectivity.Besides the connection to linguistics, argumentation has for a long time been a topic in Artificial Intelligence, where the focus is on devising adequate representations and reasoning formalisms that capture the properties of argumentative exchange. It is generally very difficult to connect the two realms of reasoning and text analysis, but we are convinced that it should be attempted in the long term, and therefore we also touch upon some fundamentals of reasoning approaches.Then the book turns to its focus, the computational side of mining argumentation in text. We first introduce a number of annotated corpora that have been used in the research. From the NLP perspective, argumentation mining shares subtasks with research fields such as subjectivity and sentiment analysis, semantic relation extraction, and discourse parsing. Therefore, many technical approaches are being borrowed from those (and other) fields. We break argumentation mining into a series of subtasks, starting with the preparatory steps of classifying text as argumentative (or not) and segmenting it into elementary units. Then, central steps are the automatic identification of claims, and finding statements that support or oppose the claim. For certain applications, it is also of interest to compute a full structure of an argumentative constellation of statements. Next, we discuss a few steps that try to 'dig deeper': to infer the underlying reasoning pattern for a textual argument, to reconstruct unstated premises (so-called 'enthymemes'), and to evaluate the quality of the argumentation. We also take a brief look at 'the other side' of mining, i.e., the generation or synthesis of argumentative text.The book finishes with a summary of the argumentation mining tasks, a sketch of potential applications, and a-necessarily subjective-outlook for the field.
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