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Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers de Wil M. P. van der Aalst

Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers: Lecture Notes in Computer Science, cartea 12602

Editat de Wil M. P. van der Aalst, Vladimir Batagelj, Dmitry I. Ignatov, Michael Khachay, Olessia Koltsova, Andrey Kutuzov, Sergei O. Kuznetsov, Irina A. Lomazova, Natalia Loukachevitch, Amedeo Napoli, Alexander Panchenko, Panos M. Pardalos, Marcello Pelillo, Andrey V. Savchenko, Elena Tutubalina
en Limba Engleză Paperback – 9 apr 2021
This book constitutes revised selected papers from the 9th International Conference on Analysis of Images, Social Networks and Texts, AIST 2020, held during October 15-16, 2020. The conference was planned to take place in Moscow, Russia, but changed to an online format due to the COVID-19 pandemic. The 27 full papers and 4 short papers presented in this volume were carefully reviewed and selected from a total of 108 qualified submissions. The papers are organized in topical sections as follows: invited papers; natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; and process mining.
 
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Specificații

ISBN-13: 9783030726096
ISBN-10: 3030726096
Pagini: 468
Ilustrații: XXIV, 468 p. 29 illus., 1 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.69 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI

Locul publicării:Cham, Switzerland

Cuprins

Invited Papers.- Making ML Models Fairer through Explanations: the Case of LimeOut.- RuREBus: a Case Study of Joint Named Entity Recognition and Relation Extraction from e-Government Domain.- On Interpretability and Similarity in Concept-Based Machine Learning.- Natural Language Processing.- DaNetQA: a yes/no Question Answering Dataset for the Russian Language.- Do Topics Make a Metaphor? Topic Modeling for Metaphor Identification and Analysis in Russian.- Metagraph-Based Approach for Neural Text Question Generation.- Abstractive Summarization of Russian News Learning on Quality Media.- RST Discourse Parser for Russian: an Experimental Study of Deep Learning Models.- A Comparative Study of Feature Types for Age-Based Text Classification.- Emotion Classification in Russian: Feature Engineering and Analysis.- Generating Sport Summaries: A Case Study for Russian.- Automatic Generation of Annotated Collection for Recognition of Sentiment Frames.- ELMo and BERT in Semantic Change Detection for Russian.- BERT for Sequence-to-Sequence Multi-Label Text Classification.- Computer Vision.- Deep Learning on Point Clouds for False Positive Reduction at Nodule Detection in Chest CT Scans.- Identifying User Interests and Habits Using Object Detection and Semantic Segmentation Models.- Semi-Automatic Manga Colorization Using Conditional Adversarial Networks.- Automated Image and Video Quality Assessment for Computational Video Editing.- An Ensemble-based Classifier of Photographs of Commercial Buildings Facades.- Social Network Analysis.- Linking Friends in Social Networks using HashTag Attributes.- Emotional Analysis of Russian Texts Using Emojis in Social Networks.- Community Detection Based on the Nodes Role in a Network: the Telegram Platform Case.- Study Of Strategies For Disseminating Information In Social Networks Using Simulation Tools.- Data Analysis and Machine Learning.- Advanced Data Recognition Technique for Real-Time and Monitoring Systems.- Human Action Recognition for Boxing Training Simulator.- Bayesian Filtering in a Latent Space to Predict Bank Net Income from Acquiring.- Gradient-Based Adversarial Attacks on Categorical Sequence Models via Traversing an Embedded World.- Russia on the Global Artificial Intelligence Scene.- New Properties Of The Data Distillation Method When Working With Tabular Data.- Unsupervised Anomaly Detection for Semi-Structured Sequence Healthcare Data.- Theoretical Machine Learning and Optimization.- Lower Bound Polynomial Fast Procedure for the Resource-Constrained Project Scheduling Problem Tested on PSPLIB Instances.- Fast Approximation Algorithms for Stabbing Special Families of Line Segments with Equal Disks.- Process Mining.- Checking Conformance between Colored Petri Nets and Event Logs.- Data and Reference Semantic-Based Simulator of DB-nets with the Use of Renew Tool.