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Web Information Systems and Technologies

Overview of attention for book
Cover of 'Web Information Systems and Technologies'

Table of Contents

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    Book Overview
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    Chapter 1 Virtual Testing Environment for Smart Automations in the Internet of Things
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    Chapter 2 Machine Learning Based Finding of Similar Sentences from French Clinical Notes
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    Chapter 3 A Comparative Study of Energy Domain Ontologies
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    Chapter 4 Semantic Label Representations with Lbl2Vec: A Similarity-Based Approach for Unsupervised Text Classification
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    Chapter 5 Towards Intelligent Processing of Electronic Invoices: The General Framework and Case Study of Short Text Deep Learning in Brazil
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    Chapter 6 Indonesia Government and Social Networks: Response Analysis About Food Security During COVID-19 Pandemic
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    Chapter 7 An Adaptive Filter for Preference Fine-Tuning in Recommender Systems
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    Chapter 8 Graph-Based Recommendation Engine for Stock Investment Decisions
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    Chapter 9 LDViz: A Tool to Assist the Multidimensional Exploration of SPARQL Endpoints
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    Chapter 10 Flexible Detection of Similar DOM Elements
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    Chapter 11 GeoSoft : A Language for Soft Querying Features Within GeoJSON Information Layers
Attention for Chapter 4: Semantic Label Representations with Lbl2Vec: A Similarity-Based Approach for Unsupervised Text Classification
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Readers on

mendeley
6 Mendeley
Summary
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Chapter title
Semantic Label Representations with Lbl2Vec: A Similarity-Based Approach for Unsupervised Text Classification
Chapter number 4
Book title
Web Information Systems and Technologies
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-24197-0_4
Book ISBNs
978-3-03-124196-3, 978-3-03-124197-0
Authors

Schopf, Tim, Braun, Daniel, Matthes, Florian

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 33%
Professor > Associate Professor 1 17%
Unknown 3 50%
Readers by discipline Count As %
Computer Science 2 33%
Business, Management and Accounting 1 17%
Unknown 3 50%

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