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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.
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.
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Knowledge Graphs and Language Technology - ISWC 2016 International Workshops: KEKI and NLP&DBpedia, Kobe, Japan, October 17-21, 2016, Revised Selected Papers (Paperback, 1st ed. 2017)
Marieke Van Erp, Sebastian Hellmann, John P. Mccrae, Christian Chiarcos, Key-Sun Choi, …
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R1,972
Discovery Miles 19 720
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Ships in 10 - 15 working days
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This book constitutes the combined refereed proceedings of ISWC
Satellite Wor shops KEKIand NLP&DBpedia 2016 which were held in
conjunction with ISWC 2016 in Kobe, Japan, inOctober 2016. The 9
papers presented were carefully selected and reviewed from
20submissions. They focus on the use of linguistic linked open
data, the linguistic aspectsof DBpedia, the improvement of of
DBpedia through NLP applications, on increasing theNLP applications
through integrating knowledge from DPpedia.
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Language, Data, and Knowledge - First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings (Paperback, 1st ed. 2017)
Jorge Gracia, Francis Bond, John P. Mccrae, Paul Buitelaar, Christian Chiarcos, …
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R2,777
Discovery Miles 27 770
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Ships in 10 - 15 working days
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This book constitutes the proceedings of the First International
Conference on Language, Data and Knowledge, LDK 2017, held in
Galway, Ireland, in June 2017. The 14 full papers and 19 short
papers included in this volume were carefully reviewed and selected
from 68 initial submissions. They deal with language data;
knowledge graphs; applications in NLP; and use cases in digital
humanities, social sciences, and BioNLP.
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