KFU. Card publication. Extracting Frame-Like Structures from Google Books NGram Dataset

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

EXTRACTING FRAME-LIKE STRUCTURES FROM GOOGLE BOOKS NGRAM DATASET

Form of presentation

Articles in international journals and collections

Year of publication

2014

Authors, employees of KFU

Ivanov Vladimir Vladimirovich, author

Bibliographic description in the original language

Ivanov V. Extracting Frame-Like Structures from Google Books NGram Dataset //Human-Inspired Computing and Its Applications. – Springer International Publishing, 2014. – S. 18-27.

Annotation

We propose a method that facilitates a process of semi-automatic FrameNet construction. The method requires Google Books NGram dataset and WordNet or another thesaurus for a particular language. We evaluated the method for Russian ngrams. Due to a huge amount of available data the method does not require sophisticated natural language processing techniques (eg for word sense disambiguation), and it shows a promising result.

Keywords

information extraction, natural language processing

The name of the journal

Lecture Notes in Computer Science

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=93637&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Ivanov Vladimir Vladimirovich	ru_RU
dc.date.accessioned	2014-01-01T00:00:00Z	ru_RU
dc.date.available	2014-01-01T00:00:00Z	ru_RU
dc.date.issued	2014	ru_RU
dc.identifier.citation	Ivanov V. Extracting Frame-Like Structures from Google Books NGram Dataset //Human-Inspired Computing and Its Applications. – Springer International Publishing, 2014. – С. 18-27.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=93637&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Computer Science	ru_RU
dc.description.abstract	We propose a method that facilitates a process of semi-automatic FrameNet construction. The method requires Google Books NGram dataset and WordNet or another thesaurus for a particular language. We evaluated the method for Russian ngrams. Due to a huge amount of available data the method does not require sophisticated natural language processing techniques (eg for word sense disambiguation), and it shows a promising result.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	information extraction	ru_RU
dc.subject	natural language processing	ru_RU
dc.title	Extracting Frame-Like Structures from Google Books NGram Dataset	ru_RU
dc.type	Articles in international journals and collections	ru_RU