Recent Trends in Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary Proceedings
Author:   Wil M. P. van der Aalst ,  Vladimir Batagelj ,  Alexey Buzmakov ,  Dmitry I. Ignatov
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
Volume:   1357
ISBN:  

9783030712136


Pages:   308
Publication Date:   25 March 2021
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Recent Trends in Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary Proceedings


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Overview

This book constitutes revised selected papers of the 9th International Conference on Analysis of Images, Social Networks and Texts, AIST 2020, held in Moscow, Russia, in october 2020. Due to the COVID-19 pandemic the conference was held online. The 14 full papers, 9 short papers and 4 poster papers were carefully reviewed and selected from 108 qualified submissions. The papers are organized in topical sections on ​natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; process mining; posters.

Full Product Details

Author:   Wil M. P. van der Aalst ,  Vladimir Batagelj ,  Alexey Buzmakov ,  Dmitry I. Ignatov
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
Volume:   1357
Weight:   0.504kg
ISBN:  

9783030712136


ISBN 10:   3030712133
Pages:   308
Publication Date:   25 March 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Natural Language Processing.- Computer Vision.- Social Network Analysis.- Data Analysis and Machine Learning.- Theoretical Machine Learning and Optimization.- Process Mining.- Posters.

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