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The Entity Name Identification in Classification Algorithm: Testing the Advocacy Coalition Framework by Document Analysis (The Case of Russian Civil Society Policy)
P. 276–288.
Zaytsev D., Talovsky N., Kuskova V., Khvatsky Gregory
This is an application of an advanced entity recognition algorithm to a large dataset.
Publication based on the results of:
In book
Vol. 11832. , Cham: Springer, 2019.
Dmitry Soshnikov, Petrova T., Soshnikova V. et al., Big Data and Cognitive Computing 2022 Vol. 6 No. 1 Article 4
Since the beginning of the COVID-19 pandemic almost two years ago, there have been more than 700,000 scientific papers published on the subject. An individual researcher cannot possibly get acquainted with such a huge text corpus and, therefore, some help from artificial intelligence (AI) is highly needed. We propose the AI-based tool to help researchers ...
Added: February 22, 2022
Tikhonov A., Yamshchikov I. P., / Series Computer Science "arxiv.org". 2021.
Chekhov's gun is a dramatic principle stating that every element in a story must be necessary, and irrelevant elements should be removed. This paper presents a new natural language processing task — Chekhov's gun recognition or (CGR) — recognition of entities that are pivotal for the development of the plot. Though similar to classical Named Entity Recognition ...
Added: December 3, 2021
Blatt F., Schlaufer C., Central European Journal of Public Policy 2021 Vol. 15 No. 1 P. 1–16
This article examines the influence of civil society on Ukrainian anti-corruption policy after the Maidan in 2014. Drawing on the Advocacy Coalition Framework (ACF), we hypothesise that the Maidan events led to a redistribution of formal legal authority in the anti-corruption policy subsystem, opened access to policy venues for civil society actors, and increased leverage ...
Added: March 8, 2021
Zaytsev D., Gregory Khvatsky, Talovsky N. et al., , in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics.: Springer, 2020. P. 231–244.
This is an exploratory study of the effects of the Unified State Exam in Russia, using advanced network methodology. ...
Added: November 7, 2019
Lei J., Bolshakova E. I., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 50–60.
The paper describes two hybrid neural network models for named entity recognition (NER) in texts, namely Bi-LSTM-CRF and Gated-CNN-CRF, as well as results of experiments with them. ...
Added: November 3, 2019
Semantic Proximity Establishment in the Tasks of Knowledge Extraction and Named Entities Recognition
Kozerenko E. B., Kuznetsov K. I., Morozova Y. I. et al., , in: PROCEEDINGS OFTHE 2017 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE.: American Council on Science & Education, 2017. P. 339–344.
The paper deals with the problem of establishing text segments containing the similar semantic units for the tasks of analytical text processing within the semantic technology platform. The methods and instruments presented in the paper provide the discovery of relevant content based on users' focused interests within a certain domain. The hybrid approach comprising linguistic ...
Added: February 23, 2018
Brykina M. M., Toldova S., Faynveyts A. V., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной Международной конференции «Диалог» (Бекасово, 29 мая - 2 июня 2013 г.). В 2-х т.Т. 1: Основная программа конференции. Вып. 12 (19).: М.: РГГУ, 2013. P. 163–177.
The Information Extraction task and the task of Named Entities recognition (NER) in unstructured texts in particular, are essential for modern Mass Media systems. The paper presents a case study of NER system for Russian. The system was built and tested on the Russian news texts. The method of ambiguity resolution under discussion is based ...
Added: February 13, 2014