Publication result detail

BUT-TYPED: Using domain knowledge for computing typed similarity

OTRUSINA, L.; SMRŽ, P.

Original Title

BUT-TYPED: Using domain knowledge for computing typed similarity

English Title

BUT-TYPED: Using domain knowledge for computing typed similarity

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

This paper deals with knowledge-based text
processing which aims at an intuitive notion
of textual similarity. Entities and relations relevant
for a particular domain are identified and
disambiguated by means of semi-supervised
machine learning techniques and resulting annotations
are applied for computing typedsimilarity
of individual texts.

English abstract

This paper deals with knowledge-based text
processing which aims at an intuitive notion
of textual similarity. Entities and relations relevant
for a particular domain are identified and
disambiguated by means of semi-supervised
machine learning techniques and resulting annotations
are applied for computing typedsimilarity
of individual texts.

Keywords

entity extraction, semantic similarity

Key words in English

entity extraction, semantic similarity

Authors

OTRUSINA, L.; SMRŽ, P.

RIV year

2014

Released

30.06.2013

Publisher

Association for Computational Linguistics

Location

Atlanta

ISBN

978-1-937284-48-0

Book

Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity

Pages from

119

Pages to

123

Pages count

5

BibTex

@inproceedings{BUT103581,
  author="Lubomír {Otrusina} and Pavel {Smrž}",
  title="BUT-TYPED: Using domain knowledge for computing typed similarity",
  booktitle="Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity",
  year="2013",
  pages="119--123",
  publisher="Association for Computational Linguistics",
  address="Atlanta",
  isbn="978-1-937284-48-0"
}