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This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have ‘linguistics’ in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.
Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.
This book provides a comprehensive foundation of distributional methods in computational modeling of meaning. It aims to build a common understanding of the theoretical and methodological foundations for students of computational linguistics, natural language processing, computer science, artificial intelligence, and cognitive science.
The two-volume set LNCS 10587 + 10588 constitutes the refereed proceedings of the 16th International Semantic Web Conference, ISWC 2017, held in Vienna, Austria, in October 2017. ISWC 2017 is the premier international forum, for the Semantic Web / Linked Data Community. The total of 55 full and 21 short papers presented in this volume were carefully reviewed and selected from 300 submissions. They are organized according to the tracks that were held: Research Track; Resource Track; and In-Use Track.
"This book is aimed at researchers and practitioners involved in designing and managing complex multimedia information systems"--Provided by publisher.
Dr.T.Arumuga Maria Devi, Assistant Professor, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mrs.V.S.Jeyalakshmi, Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mrs.S.Kowsalya, Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mrs.V.Bhavani, Assistant Professor, Department of Computer Applications, Mannar Thirumalai Naicker College (Autonomous), Madurai, Tamil Nadu, India.
This book is a collective volume that reports the state of the art in the applications of type theory to linguistic semantics. The volume fills a 20 year gap from the last published book on the issue and aspires to bring researchers closer to cutting edge alternatives in formal semantics research. It consists of unpublished work by some key researchers on various issues related to the type theoretical study of formal semantics and further exemplifies the advantages of using modern type theoretical approaches to linguistic semantics. Themes that are covered include modern developments of type theories in formal semantics, foundational issues in linguistic semantics like anaphora, modality and plurals, innovational interdisciplinary research like the introduction of probability theory to type theories as well as computational implementations of type theoretical approaches. This volume will be of great interest to formal semanticists that are looking for alternative ways to study linguistic semantics, but will also be of interest to theoretical computer scientists and mathematicians that are interested in the applications of type theory.
The all pervasive web is influencing all aspects of human endeavour. In order to strengthen the description of web resources, so that they are more meaningful to both humans and machines, web semantics have been proposed. These allow better annotation, understanding, search, interpretation and composition of these - sources. The growing importance of these has brought about a great increase in research into these issues. We propose a series of books that will address key issues in web semantics on an annual basis. This book series can be considered as an extended journal published annually. The series will combine theoretical results, standards, and their realizations in applications and implementations. The series is titled “Advances in Web Sem- tics” and will be published periodically by Springer to promote emerging Semantic Web technologies. It will contain the cream of the collective contribution of the Int- national Federation for Information Processing (IFIP) Web Semantics Working Group; WG 2. 12 & WG 12. 4. This book, addressing the current state of the art, is the first in the series. In subsequent years, books will address a particular theme, topic or issue where the greatest advances are being made. Examples of such topics include: (i) process semantics, (ii) web services, (iii) ontologies, (iv) workflows, (v) trust and reputation, (vi) web applications, etc. Periodically, perhaps every five years, there will be a scene-setting state of the art volume.
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence. Volume XIV results from a rigorous selection among 21 full papers received in response to a call for contributions issued in September 2008.