Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
This paper is the first part of contextual predictability model investigation for Russian, it is focused on linguistic and psychology interpretation of models, features, metrics and sets of features. The aim of this paper is to identify the dependence of the implementation of contextual predictability procedures on the genre characteristics of the text (or text collection): scientific vs. fictional. We construct a model predicting text elements and designate its features for texts of different genres and domains. We analyze various methods for studying contextual predictability, carry out a computational experiment against scientific and fictional texts, and verify its results by the experiment with informants (cloze-tests) and word embeddings (word2vec CBOW model). As a result, text processing model is built. It is evaluated based on the selected contextual predictability features and experiments with informants.
Original language | English |
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Title of host publication | Mining Intelligence and Knowledge Exploration - 7th International Conference, MIKE 2019, Proceedings |
Editors | P. B.R., Veena Thenkanidiyoor, Rajendra Prasath, Odelu Vanga |
Publisher | Springer Nature |
Chapter | 11 |
Pages | 104-119 |
Number of pages | 16 |
ISBN (Print) | 9783030661861 |
DOIs | |
State | Published - 2020 |
Event | 7th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2019 - Veling, India Duration: 19 Dec 2019 → 22 Dec 2019 |
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11987 LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference | 7th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2019 |
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Country/Territory | India |
City | Veling |
Period | 19/12/19 → 22/12/19 |
ID: 73342010