Analysis of Images, Social Networks and Texts : 10th International Conference, AIST 2021, Tbilisi, Georgia, December 16–18, 2021, Revised Selected Papers / / edited by Evgeny Burnaev, Dmitry I. Ignatov, Sergei Ivanov, Michael Khachay, Olessia Koltsova, Andrei Kutuzov, Sergei O. Kuznetsov, Natalia Loukachevitch, Amedeo Napoli, Alexander Panchenko, Panos M. Pardalos, Jari Saramäki, Andrey V. Savchenko, Evgenii Tsymbalov, Elena Tutubalina

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
• Edizione: 1st ed. 2022.
• Descrizione fisica: 1 online resource (358 pages)
• Disciplina: 006.312; 621.367
• Soggetto topico: Data mining; Machine learning; Database management; Natural language processing (Computer science); Information storage and retrieval systems; Application software; Data Mining and Knowledge Discovery; Machine Learning; Database Management; Natural Language Processing (NLP); Information Storage and Retrieval; Computer and Information Systems Applications; Mineria de dades; Processament d'imatges; Tractament de textos; Tractament del llenguatge natural (Informàtica); Reconeixement de formes (Informàtica); Xarxes socials en línia
• Soggetto genere / forma: Congressos; Llibres electrònics
• Persona (resp. second.): BurnaevEvgeny
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Invited Papers -- On Georgian Text Processing Toolkit Development -- Taxonomy Enrichment with Text and Graph Vector Representation -- Natural Language Processing -- Near-Zero-Shot Suggestion Mining with a Little Help from WordNet -- Selection of Pseudo-Annotated Data for Adverse Drug Reaction Classification Across Drug Groups -- Building a Combined Morphological Model for Russian Word Forms -- SocialBERT -- Transformers for Online Social Network Language Modelling -- Lexicon-based Methods vs. BERT for Text Sentiment Analysis -- Multilingual Embeddings for Clustering Cultural Events -- Jokingbird: Funny Headline Generation for News -- Learning to Rank with Capsule Neural Networks -- Building a Bilingual QA-system with ruGPT-3 -- Sculpting enhanced dependencies for Belarusian -- Improving morpheme segmentation using BERT embeddings -- Training dataset and dictionary sizes matter in BERT models: the case of Baltic languages -- Computer Vision -- Development of a method for iris-based person recognition using convolutional neural networks -- Data dimension reduction technique based on preservation of Hellinger divergence -- Group-level Affect Recognition in Video using Deviation of Frame Features -- Outfit Recommendation Using Visual Similarity -- Data Analysis and Machine Learning -- Scalable computation of prediction intervals for neural networks with matrix sketching -- Application of Data Analysis Methods for Optimizing the Multifunctional Service Center Operation -- Depression Detection by Person's Voice -- Social Network Analysis -- Research Papers Recommendation -- Multimodal Space of Users' Interests and Preferences in Social Networks -- Citation network applications in a scientific co-authorship recommender system -- Theoretical Machine Learning and Optimization -- How Fast Can the Uniform Capacitated Facility Location Problem Be Solved on Path Graphs -- On a weakly supervised classification problem -- A Local Search Algorithm for the Biclustering Problem.
• Sommario/riassunto: This book constitutes revised selected papers from the thoroughly refereed proceedings of the 10th International Conference on Analysis of Images, Social Networks and Texts, AIST 2021, held in Tbilisi, Georgia, during December 16–18, 2021. The 20 full papers and 5 short papers included in this book were carefully reviewed and selected from 118 submissions. They were organized in topical sections as follows: Invited papers; natural language processing; computer vision; data analysis and machine learning; social network analysis; and theoretical machine learning and optimization.
• Titolo autorizzato: Analysis of images, social networks and texts
• ISBN: 9783031165009; 3031165004
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910624318603321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 13217