Artificial intelligence and natural language : 9th Conference, AINL 2020, Helsinki, Finland, October 7-9, 2020, Proceedings /: 9th Conference, AINL 2020, Helsinki, Finland, October 7-9, 2020, Proceedings. (2020)
- Record Type:
- Book
- Title:
- Artificial intelligence and natural language : 9th Conference, AINL 2020, Helsinki, Finland, October 7-9, 2020, Proceedings /: 9th Conference, AINL 2020, Helsinki, Finland, October 7-9, 2020, Proceedings. (2020)
- Main Title:
- Artificial intelligence and natural language : 9th Conference, AINL 2020, Helsinki, Finland, October 7-9, 2020, Proceedings
- Other Titles:
- AINL 2020
- Further Information:
- Note: Andrey Filchenkov, Janne Kauttonen, Lidia Pivovarova (eds.).
- Other Names:
- Filchenkov, Andrey
Kauttonen, Janne
Pivovarova, Lidia
Conference on Artificial Intelligence and Natural Language, 9th - Contents:
- Intro -- Preface -- Organization -- Contents -- PolSentiLex: Sentiment Detection in Socio-Political Discussions on Russian Social Media -- 1 Introduction -- 2 Related Work -- 2.1 Sentiment Analysis in the Russian Langauge -- 3 PolSentiLex -- 3.1 LiveJournal Collection of Social and Political Posts -- 3.2 Selection of Potentially Sentiment-Bearing Words -- 3.3 Data Mark Up -- 3.4 The Three Versions of PolSentiLex -- 4 PolSentiLex Quality Assessment -- 4.1 Datasets -- 5 Results -- 6 Conclusion -- References Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Experiments with the Russian Corpus of VKontakte Posts -- 3.1 Corpus Collecting and Preprocessing -- 3.2 Author-Topic Models -- 3.3 Automatic Labeling of Topics -- 3.4 Model of Hidden Communities in VKontakte Social Network -- 4 Results and Evaluation -- 5 Summary -- References -- Dialog Modelling Experiments with Finnish One-to-One Chat Data -- 1 Introduction -- 2 Related Work -- 2.1 Language Resources for One-to-One Chat Dialogue Data 2.2 Machine Learning for Chat Data Modelling -- 2.3 Evaluation Results for Chat Data Models -- 3 Experimental Setting -- 3.1 Description of the Data Sets -- 3.2 Implementation and Parameters of Methods -- 3.3 Data Preprocessing -- 4 Results -- 4.1 Output Examples -- 5 Analysis and Discussion -- 6 Conclusions -- References -- Advances of Transformer-Based Models for News Headline Generation -- 1Intro -- Preface -- Organization -- Contents -- PolSentiLex: Sentiment Detection in Socio-Political Discussions on Russian Social Media -- 1 Introduction -- 2 Related Work -- 2.1 Sentiment Analysis in the Russian Langauge -- 3 PolSentiLex -- 3.1 LiveJournal Collection of Social and Political Posts -- 3.2 Selection of Potentially Sentiment-Bearing Words -- 3.3 Data Mark Up -- 3.4 The Three Versions of PolSentiLex -- 4 PolSentiLex Quality Assessment -- 4.1 Datasets -- 5 Results -- 6 Conclusion -- References Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Experiments with the Russian Corpus of VKontakte Posts -- 3.1 Corpus Collecting and Preprocessing -- 3.2 Author-Topic Models -- 3.3 Automatic Labeling of Topics -- 3.4 Model of Hidden Communities in VKontakte Social Network -- 4 Results and Evaluation -- 5 Summary -- References -- Dialog Modelling Experiments with Finnish One-to-One Chat Data -- 1 Introduction -- 2 Related Work -- 2.1 Language Resources for One-to-One Chat Dialogue Data 2.2 Machine Learning for Chat Data Modelling -- 2.3 Evaluation Results for Chat Data Models -- 3 Experimental Setting -- 3.1 Description of the Data Sets -- 3.2 Implementation and Parameters of Methods -- 3.3 Data Preprocessing -- 4 Results -- 4.1 Output Examples -- 5 Analysis and Discussion -- 6 Conclusions -- References -- Advances of Transformer-Based Models for News Headline Generation -- 1 Introduction -- 2 Related Work -- 3 Models Description -- 4 Datasets -- 5 Experiments -- 5.1 Evaluation -- 5.2 Training Dynamics -- 6 Results -- 6.1 Human Evaluation -- 6.2 Error Analysis 7 Conclusion and Future Work -- References -- An Explanation Method for Black-Box Machine Learning Survival Models Using the Chebyshev Distance -- 1 Introduction -- 2 Basic Definitions of Survival Analysis -- 3 LIME -- 4 A General Algorithm of SurvLIME and SurvLIME-Inf -- 5 Optimization Problem for Computing Parameters -- 6 Numerical Experiments -- 6.1 Synthetic Data -- 6.2 Real Data -- 7 Conclusion -- References -- Unsupervised Neural Aspect Extraction with Related Terms -- 1 Introduction -- 2 Related Work -- 3 The Proposal -- 3.1 Model -- 3.2 Training Objective -- 4 Experiments -- 4.1 Datasets 4.2 Experimental Settings -- 4.3 Evaluation Settings -- 4.4 Aspect Extraction Results -- 4.5 Aspect and Aspect Term Extraction Results -- 5 Conclusions -- References -- Predicting Eurovision Song Contest Results Using Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Collection of Eurovision Tweets -- 3.2 Identification of the Source Country -- 3.3 Tweet Tokenization -- 3.4 Identification of the Target Country -- 3.5 Sentiment Analysis -- 3.6 Tallying of Final Results -- 4 Experimental Results -- 4.1 Televoting Algorithm -- 4.2 Different Sampling Windows … (more)
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2020
- Copyright Date:
- 2020
- Extent:
- 1 online resource (203 pages)
- Subjects:
- 006.3/5
Natural language processing (Computer science) -- Congresses
Artificial intelligence -- Congresses
Artificial intelligence
Natural language processing (Computer science)
Electronic books
Electronic books
Conference papers and proceedings - Languages:
- English
- ISBNs:
- 9783030590826
- Related ISBNs:
- 9783030590819
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- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- British Library HMNTS - ELD.DS.561423
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