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Semantic Web Challenges

Overview of attention for book
Cover of 'Semantic Web Challenges'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 MOCHA2018: The Mighty Storage Challenge at ESWC 2018
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    Chapter 2 Versioned Querying with OSTRICH and Comunica in MOCHA 2018
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    Chapter 3 Benchmarking Virtuoso 8 at the Mighty Storage Challenge 2018: Challenge Results
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    Chapter 4 Open Knowledge Extraction Challenge 2018
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    Chapter 5 Relation Extraction for Knowledge Base Completion: A Supervised Approach
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    Chapter 6 The Scalable Question Answering Over Linked Data (SQA) Challenge 2018
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    Chapter 7 On the scalability of the QA System WDAqua-core1
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    Chapter 8 GQA: Grammatical Question Answering for RDF Data
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    Chapter 9 A Language Adaptive Method for Question Answering on French and English
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    Chapter 10 Semantic Sentiment Analysis Challenge at ESWC2018
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    Chapter 11 Domain-Aware Sentiment Classification with GRUs and CNNs
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    Chapter 12 Fine-Tuning of Word Embeddings for Semantic Sentiment Analysis
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    Chapter 13 The KABSA System at ESWC-2018 Challenge on Semantic Sentiment Analysis
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    Chapter 14 The IRMUDOSA System at ESWC-2018 Challenge on Semantic Sentiment Analysis
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    Chapter 15 The CLAUSY System at ESWC-2018 Challenge on Semantic Sentiment Analysis
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    Chapter 16 The NeuroSent System at ESWC-2018 Challenge on Semantic Sentiment Analysis
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    Chapter 17 The FeatureSent System at ESWC-2018 Challenge on Semantic Sentiment Analysis
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    Chapter 18 Evaluating Quality of Word Embeddings with Sentiment Polarity Identification Task
Attention for Chapter 13: The KABSA System at ESWC-2018 Challenge on Semantic Sentiment Analysis
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Citations

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Chapter title
The KABSA System at ESWC-2018 Challenge on Semantic Sentiment Analysis
Chapter number 13
Book title
Semantic Web Challenges
Published by
Springer, Cham, June 2018
DOI 10.1007/978-3-030-00072-1_13
Book ISBNs
978-3-03-000071-4, 978-3-03-000072-1
Authors

Marco Federici, Mauro Dragoni

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 20%
Student > Postgraduate 1 20%
Unknown 3 60%
Readers by discipline Count As %
Computer Science 1 20%
Social Sciences 1 20%
Unknown 3 60%

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