Описание: This book constitutes the refereed proceedings of the 15th Industrial Conference on Advances in Data Mining, ICDM 2015, held in Hamburg, Germany, in July 2015. The 16 revised full papers presented were carefully reviewed and selected from numerous submissions.
Автор: Guojun Wang; Md Zakirul Alam Bhuiyan; Sabrina De C Название: Dependability in Sensor, Cloud, and Big Data Systems and Applications ISBN: 9811513031 ISBN-13(EAN): 9789811513039 Издательство: Springer Рейтинг: Цена: 11738.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 5th International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications, DependSys, held in Guangzhou, China, in November 2019.
The volume presents 39 full papers, which were carefully reviewed and selected from 112 submissions. The papers are organized in topical sections on ?dependability and security fundamentals and technologies; dependable and secure systems; dependable and secure applications; dependability and security measures and assessments; explainable artificial inteligence for cyberspace.
Описание: The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science.
Описание: This book constitutes refereed proceedings of the First International First International Conference on Big Data, Machine Learning, and Applications, BigDML 2019, held in Silchar, India, in December. The 6 full papers and 3 short papers were carefully reviewed and selected from 152 submissions.
Автор: Diana Trandab??; Daniela G?fu Название: Linguistic Linked Open Data ISBN: 3319329413 ISBN-13(EAN): 9783319329413 Издательство: Springer Рейтинг: Цена: 6988.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Ontological modeling of social media data.- Application of social media and linked data methodologies in real-life scenarios.- User proling and assessing the suitability of content from social media.- Extracting and linking content.- Sentiment analysis in social media and linked data.-Social data mining to create structured social media resources.
Автор: Philipp Cimiano; Christian Chiarcos; John P. McCra Название: Linguistic Linked Data ISBN: 3030302245 ISBN-13(EAN): 9783030302245 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource.
The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources.
Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.
Описание: This open access book explores the dataspace paradigm as a best-effort approach to data management within data ecosystems.
Автор: Christian Chiarcos; Sebastian Nordhoff; Sebastian Название: Linked Data in Linguistics ISBN: 3642434967 ISBN-13(EAN): 9783642434969 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The contributions assembled in this volume illustrate the band-width of applications of the Linked Data paradigm for representative types of language resources. They cover lexical-semantic resources, annotated corpora, typological databases as well as terminology and metadata repositories.
Описание: This book provides a corpus-led analysis of multi-word units (MWUs) in English, specifically fixed pairs of nouns which are linked by a conjunction, such as `mum and dad`, `bride and groom` and `law and order`.
Автор: Edward Curry Название: Real-time Linked Dataspaces ISBN: 3030296644 ISBN-13(EAN): 9783030296643 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This open access book explores the dataspace paradigm as a best-effort approach to data management within data ecosystems.
Описание: In knowledge-based natural language generation, issues of formal knowledge representation meet with the linguistic problems of choosing the most appropriate verbalization in a particular situation of utterance. This work presents a new approach to linking the realms of lexical semantics and knowledge represented in a description logic.
Описание: Developers working with NLP will be able to put their knowledge to work with this practical guide to PyTorch. You will learn to use PyTorch offerings and how to understand and analyze text using Python. You will learn to extract the underlying meaning in the text using deep neural networks and modern deep learning algorithms.
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