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Named Entity Recognition in Russian-Language Texts

Student: Triaskova Arina

Supervisor: Alexey Malafeev

Faculty: Faculty of Humanities (Nizhny Novgorod)

Educational Programme: Fundamental and Applied Linguistics (Bachelor)

Final Grade: 8

Year of Graduation: 2019

Under the named entity modern linguistics understands a word or a phrase that denotes an object or phenomenon of a certain category. In most cases they have attributes of proper names. Extracting named entities is important for text analysis, business analysis, text search etc. In present work, different machine learning algorithms used to solve named entity recognition task are analyzed, applied and compared. Consequently, the goal of the research is to extract named entities such as names of individuals, locations, organizations and group which includes other types, using machine learning algorithms such as Perceptron, Linear Classifier with SGD training, Conditional Random Fields and evaluate the effectiveness of applied approaches.

Full text (added June 1, 2019)

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