Overview

​This book constitutes the refereed proceedings of the 9th Conference on Artificial Intelligence and Natural Language, AINL 2020, held in Helsinki, Finland, in October 2020.  The 11 revised full papers and 3 short papers were carefully reviewed and selected from 36 submissions. Additionally, the volume presents 1 shared task paper. The volume presents recent research in areas of of text mining, speech technologies, dialogue systems, information retrieval, machine learning, articial intelligence, and robotics. 

Full Product Details

Author:   Andrey Filchenkov ,  Janne Kauttonen ,  Lidia Pivovarova
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   1292
Weight:   0.454kg
ISBN:  

9783030590819

ISBN 10:   303059081
Pages:   203
Publication Date:   30 September 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

PolSentiLex: Sentiment Detection in Socio-political Discussions on Russian Social Media.- Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus.- Dialog Modelling Experiments with Finnish One-to-One Chat Data.- Advances of Transformer-Based Models for News Headline Generation.- An explanation method for black-box machine learning survival models using the Chebyshev distance.- Unsupervised Neural Aspect Extraction with Related Terms.- Predicting Eurovision Song Contest Results using Sentiment Analysis.- Improving Results on Russian Sentiment Datasets.- Dataset for Automatic Summarization of Russian News.- Dataset for evaluation of mathematical reasoning abilities in Russian.- Searching Case Law Judgments by Using Other Judgments as a Query.- GenPR: Generative PageRank framework for Semi-Supervised Learning on citation graphs.- Finding New Multiword Expressions for Existing Thesaurus.- Matching LIWC with Russian Thesauri: An Exploratory Study.- Chinese-Russian Shared Task on Multi-Domain Translation.

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