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Titlebook: Data Analytics and Management in Data Intensive Domains; 22nd International C Alexander Sychev,Sergey Makhortov,Bernhard Thalhei Conference

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Part of Speech and Gramset Tagging Algorithms for Unknown Words Based on Morphological Dictionaries s to words are presented in the article. These algorithms use our morphological dictionaries, where the lemma, part of speech and a set of grammatical features (gramset) are known for each word form. The algorithms are based on the analogy hypothesis that words with the same suffixes are likely to h
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Extrinsic Evaluation of Cross-Lingual Embeddings on the Patent Classification Tasky of transferring knowledge between languages. We consider Multilingual Unsupervised and Supervised Embeddings (MUSE), multilingual BERT embeddings, XLM-RoBERTa (XLM-R) model embeddings, and Language-Agnostic Sentence Representations (LASER). Various classification algorithms use them as inputs for
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An Approach to Extracting Ontology Concepts from Requirementsussian-language. Relevance of developing an approach to automating the process of extraction of the ontology concepts from the requirements written in natural language is due to the necessity to maintain the requirements specification in a consistent state under conditions of business environment va
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Extrinsic Evaluation of Cross-Lingual Embeddings on the Patent Classification Tasksolving the task of the patent categorization. It is a zero-shot cross-lingual classification task since the training and the validation sets include the English texts, and the test set consists of documents in Russian.
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1865-0929 nt in semantic web; data analysis in medicine; data analysis in astronomy; information extraction from text..* The conference was held virtually due to the COVID-19 pandemic..978-3-030-81199-0978-3-030-81200-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Managing Data-Intensive Research Problem-Solving Lifecycle process reuse, hypothesis testing, and data publishing. Problems are solved according to formal domain knowledge specifications over multiple integrated resources. The semantics of every decision may be formally verified.
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https://doi.org/10.1007/978-3-031-48561-9solving the task of the patent categorization. It is a zero-shot cross-lingual classification task since the training and the validation sets include the English texts, and the test set consists of documents in Russian.
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