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Artificial Intelligence and Natural Language

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Cover of 'Artificial Intelligence and Natural Language'

Table of Contents

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    Book Overview
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    Chapter 1 Effects of Training Data Size and Class Imbalance on the Performance of Classifiers
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    Chapter 2 SentiRusColl: Russian Collocation Lexicon for Sentiment Analysis
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    Chapter 3 An Approach to Inter-annotator Agreement Evaluation for the Named Entities Annotation Task at OpenCorpora
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    Chapter 4 Soft Estimates of User Protection from Social Engineering Attacks
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    Chapter 5 Retrieval of Visually Shared News
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    Chapter 6 Comparative Analysis of Scientific Papers Collections via Topic Modeling and Co-authorship Networks
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    Chapter 7 Experimental Comparison of Unsupervised Approaches in the Task of Separating Specializations Within Professions in Job Vacancies
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    Chapter 8 Usage of HMM-Based Speech Recognition Methods for Automated Determination of a Similarity Level Between Languages
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    Chapter 9 Prosodic Boundaries Prediction in Russian Using Morphological and Syntactic Features
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    Chapter 10 Binary Autoencoder for Text Modeling
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    Chapter 11 Bi-LSTM Model for Morpheme Segmentation of Russian Words
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    Chapter 12 An Approach to Abstractive Summarization for Norwegian Bokmål
Attention for Chapter 4: Soft Estimates of User Protection from Social Engineering Attacks
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Chapter title
Soft Estimates of User Protection from Social Engineering Attacks
Chapter number 4
Book title
Artificial Intelligence and Natural Language
Published by
Springer, Cham, November 2019
DOI 10.1007/978-3-030-34518-1_4
Book ISBNs
978-3-03-034517-4, 978-3-03-034518-1
Authors

Maxim V. Abramov, Alexander L. Tulupyev, Abramov, Maxim V., Tulupyev, Alexander L.

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