Artificial Intelligence and Natural Language
9th Conference, AINL 2020, Helsinki, Finland, October 7-9, 2020, Proceedings
Published on 30. September 2020
X, 203 pages
978-3-030-59082-6 (ISBN)
Description
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.
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.
More details
Series
Edition
1st ed. 2020
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
X, 203 p. 67 illus., 36 illus. in color.
ISBN-13
978-3-030-59082-6 (9783030590826)
DOI
10.1007/978-3-030-59082-6
Schweitzer Classification
Other editions
Additional editions
Andrey Filchenkov | Janne Kauttonen | Lidia Pivovarova
Artificial Intelligence and Natural Language
9th Conference, AINL 2020, Helsinki, Finland, October 7-9, 2020, Proceedings
Book
09/2020
Springer
€53.49
Shipment within 7-9 days
Content
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.
