PROGRAM SYSTEMS: THEORY AND APPLICATIONS

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Online Scientific Journal published by the Ailamazyan Program Systems Institute of the Russian Academy of Sciences

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• Содержание выпуска •
• Methods for Optimal Control and Control Theory •
• Software and Hardware for Distributed Systems and Supercomputers •
• Mathematical Foundations of Programming •
• Artificial Intelligence, Intelligence Systems, Neural Networks •
• Mathematical Modelling •

Artificial Intelligence, Intelligence Systems, Neural Networks

Responsible for the Section: doctor of technical Sciences Vyacheslav Khachumov., candidate of technical Sciences Eugene Kurshev.

On the left: assigned number of the paper, submission date, the number of A5 pages contained in the paper, and the reference to the full-text PDF .

Article # 8_2016 18 p. PDF	submitted on 30th Dec 2015 displayed on website on 15th March 2016 Trofimov I.V. Peculiarities of fine-grained factual information extraction from text The paper states the problem of fine-grained factual information extraction form text. The author reveals some additional issues that arise from such formulation of the task. (In Russian). Key words: natural language processing, information extraction, MUC, frame, implicit information in text.
article citation	http://psta.psiras.ru/read/psta2016_1_135-152.pdf
DOI	https://doi.org/10.25209/2079-3316-2016-7-1-135-152
Article # 9_2016 18 p. PDF	submitted on 02th Feb 2015 displayed on website on 15th March 2016 Vlasova N.A., Podobryaev A.V. К вопросу об определении границ именных групп при решении задач автоматического извлечения информации из текстов на русском языке We consider the problem of complex noun phrase recognition in Russian news texts with application to automatic information extraction. By complex noun phrases we mean long noun phrases that contain genitive or/and prepositional constructions and named entities. We describe a plan of noun phrase recognition that begins with a selection of the sentence fragments that undoubtedly contain noun phrases. The fragments selection algorithm is developed. The fragments are classified by frequency of their types, number of words in the fragment, part of speech structure, presence of extracted named entities, some complex prepositions and stable expressions. We introduce a feature system to make automatic noun phrase recognition inside selected fragments. In experiments we have selected 58032 fragments from 1000 documents collection of Russian news. We consider some complex cases. (In Russian). Key words: information extraction, named entities recognition, noun phrase chunking.
article citation	http://psta.psiras.ru/read/psta2016_1_153-170.pdf
DOI	https://doi.org/10.25209/2079-3316-2016-7-1-153-170

• Methods for Optimal Control and Control Theory •
• Software and Hardware for Distributed Systems and Supercomputers •
• Mathematical Foundations of Programming •
• Artificial Intelligence, Intelligence Systems, Neural Networks •
• Mathematical Modelling •

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