The People’s Web Meets NLP (eBook)

Collaboratively Constructed Language Resources

Iryna Gurevych, Jungi Kim (Herausgeber)

eBook Download: PDF
2013 | 2013
XXIV, 378 Seiten
Springer Berlin (Verlag)
978-3-642-35085-6 (ISBN)

Lese- und Medienproben

The People’s Web Meets NLP -
Systemvoraussetzungen
96,29 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

Collaboratively Constructed Language Resources (CCLRs) such as Wikipedia, Wiktionary, Linked Open Data, and various resources developed using crowdsourcing techniques such as Games with a Purpose and Mechanical Turk have substantially contributed to the research in natural language processing (NLP). Various NLP tasks utilize such resources to substitute for or supplement conventional lexical semantic resources and linguistically annotated corpora. These resources also provide an extensive body of texts from which valuable knowledge is mined. There are an increasing number of community efforts to link and maintain multiple linguistic resources.
 
This book aims offers comprehensive coverage of CCLR-related topics, including their construction, utilization in NLP tasks, and interlinkage and management. Various Bachelor/Master/Ph.D. programs in natural language processing, computational linguistics, and knowledge discovery can use this book both as the main text and as a supplementary reading. The book also provides a valuable reference guide for researchers and professionals for the above topics.



Iryna Gurevych leads the UKP Lab in the Department of Computer Science of the Technische Universität Darmstadt (UKP-TUDA) and at the Institute for Educational Research and Educational Information (UKP-DIPF) in Frankfurt, Germany. She holds an endowed Lichtenberg-Chair 'Ubiquitous Knowledge Processing' of the Volkswagen Foundation. Her research in NLP primarily concerns applied lexical semantic algorithms, such as computing semantic relatedness of words or paraphrase recognition, and their use to enhance the performance of NLP tasks, such as information retrieval, question answering, or summarization.

Jungi Kim is a postdoctoral researcher at UKP Lab in the Department of Computer Science of the Technische Universität Darmstadt, Germany (UKP-TUDA). His primary research interests are in semantic resources, algorithms, and evaluations for multilingual natural language processing. His previous research includes multilingual sentiment analysis, statistical machine translation, and various NLP topics involving multiple languages, especially East Asian languages.

Iryna Gurevych leads the UKP Lab in the Department of Computer Science of the Technische Universität Darmstadt (UKP-TUDA) and at the Institute for Educational Research and Educational Information (UKP-DIPF) in Frankfurt, Germany. She holds an endowed Lichtenberg-Chair "Ubiquitous Knowledge Processing" of the Volkswagen Foundation. Her research in NLP primarily concerns applied lexical semantic algorithms, such as computing semantic relatedness of words or paraphrase recognition, and their use to enhance the performance of NLP tasks, such as information retrieval, question answering, or summarization.Jungi Kim is a postdoctoral researcher at UKP Lab in the Department of Computer Science of the Technische Universität Darmstadt, Germany (UKP-TUDA). His primary research interests are in semantic resources, algorithms, and evaluations for multilingual natural language processing. His previous research includes multilingual sentiment analysis, statistical machine translation, and various NLP topics involving multiple languages, especially East Asian languages.

Part I Approaches to Collaboratively Constructed Language Resources.- 1.Using Games to Create Language Resources: Successes and Limitations of the Approach. J.Chamberlain, K.Fort, U.Kruschwitz, M.Lafourcade and M.Poesio.- 2.Senso Comune: A Collaborative Knowledge Resource for Italian. Al.Oltramari, G.Vetere, I.Chiari, E.Jezek, F.M.Zanzotto, M.Nissim, and A.Gangemi.- 3.Building Multilingual Language Resources in Web Localisation: A Crowdsourcing Approach. A.Wasala, R.Schäler, J.Buckley, R.Weerasinghe and C.Exton. – 4.Reciprocal Enrichment Between Basque Wikipedia and Machine Translation.- I.Alegria, U.Cabezon, U.Fernandez de Betoño, G.Labaka, A.Mayor, K.Sarasola and A.Zubiaga.- Part II Mining Knowledge From and Using Collaboratively Constructed Language Resources.- 5.A Survey of NLP Methods and Resources for Analyzing the Collaborative Writing Process in Wikipedia. O.Ferschke, J.Daxenberger and I.Gurevych.- 6.ConceptNet 5: A Large Semantic Network for Relational Knowledge. R.Speer and C.Havasi.- 7.An Overview of BabelNet and its API for Multilingual Language Processing. R.Navigli and S.P.Ponzetto.- 8.Hierarchical Organization of Collaboratively Constructed Content. J.Yu, Z-J.Zha, and T-S.Chua.- 9.Word Sense Disambiguation using Wikipedia. B.Dandala, R.Mihalcea, and R.Bunescu.- Part III Interconnecting and Managing Collaboratively Constructed Language Resources.- 10.An Open Linguistic Infrastructure for Annotated Corpora. N.Ide.- 11.TowardsWeb-Scale Collaborative Knowledge Extraction. S.Hellmann, S. Auer.- 12.Building a Linked Open Data Cloud of Linguistic Resources: Motivations and Developments. C.Chiarcos, S.Moran, P.N.Mendes, S.Nordhoff, R.Littauer.- 13.Community Efforts around the ISOcat Data Category Registry. S.E.Wright, M.Windhouwer, I.Schuurman, M.Kemps-Snijders.- Index.

Erscheint lt. Verlag 3.4.2013
Reihe/Serie Theory and Applications of Natural Language Processing
Theory and Applications of Natural Language Processing
Vorwort Nicoletta Calzolari
Zusatzinfo XXIV, 378 p.
Verlagsort Berlin
Sprache englisch
Themenwelt Geisteswissenschaften Sprach- / Literaturwissenschaft Sprachwissenschaft
Mathematik / Informatik Informatik Datenbanken
Schlagworte 68T50, • Collaboratively Constructed Resource • Collective Intelligence / Human Computation • Computational Linguistics • Language Resource • Natural Language Processing
ISBN-10 3-642-35085-2 / 3642350852
ISBN-13 978-3-642-35085-6 / 9783642350856
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 9,6 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Zusätzliches Feature: Online Lesen
Dieses eBook können Sie zusätzlich zum Download auch online im Webbrowser lesen.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
inklusive eLearning-Kurs mit über 7.000 Aufgaben. Regeln, Anwendung, …

von Uwe Dethloff; Horst Wagner

eBook Download (2023)
UTB GmbH (Verlag)
64,99