Overview

This book constitutes the thoroughly refereed proceedings of the Second Iberoamerican Conference, KGSWC 2020, held in Mérida, Mexico, in November 2020. Due to the COVID-19 pandemic the conference was held online.  The 15 papers presented were carefully reviewed and selected from 45 submissions. The papers cover research and practices in several fields of AI, such as knowledge representation and reasoning, natural language processing/text mining, machine/deep learning, semantic web, and knowledge graphs.

Full Product Details

Author:   Boris Villazón-Terrazas ,  Fernando Ortiz-Rodríguez ,  Sanju M. Tiwari ,  Shishir K. Shandilya
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   1232
Weight:   0.454kg
ISBN:  

9783030653835

ISBN 10:   3030653838
Pages:   215
Publication Date:   10 December 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

A Domain Ontology for Task Instructions.- Axiomatic relation extraction from text in the domain of Tourism.- Making Neural Networks FAIR.- Creating Annotations for Web Ontology Language Ontology Generated From Relational Databases.- Malware Detection using Machine Learning.- Wikipedia Knowledge Graph for Explainable AI.- Characterizing the Diffusion of Knowledge in an Academic Community Through the Integration of Heterogeneous Data Sources and Graphs.- Relation Classification: How well do Neural Network Approaches Work?.- Standards Conformance Metrics for Geospatial Linked Data.- An Ontological Model for the Failure Detection in Power Electric Systems.- A Spatiotemporal Knowledge Bank from Rape News Articles for Decision Support.- Exploring Sequence-to-Sequence Models for SPARQL Pattern Composition.- Using Domain Ontologies for Text Classification. A Use Case to Classify Computer Science Papers.- Description of Open Data Sets as Semantic Knowledge Graphs to contribute to actions related to the 2030 Agenda and the Sustainable Development Goals.- A Machine Learning Method for Recognizing Invasive Content in Memes.

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