Detail publikace

Combining Heterogeneous Models for Measuring Relational Similarity

ZHILA, A. YIH, W. MEEK, C. MIKOLOV, T. ZWEIG, G.

Originální název

Combining Heterogeneous Models for Measuring Relational Similarity

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

In this paper, we presented a system that combines heterogeneous models based on different information sources for measuring relational similarity.

Klíčová slova

language modeling, heterogeneous models, recurrent neural networks

Autoři

ZHILA, A.; YIH, W.; MEEK, C.; MIKOLOV, T.; ZWEIG, G.

Rok RIV

2013

Vydáno

9. 6. 2013

Nakladatel

Association for Computational Linguistics

Místo

Atlanata, Georgia

ISBN

978-1-937284-47-3

Kniha

Proceedings of NAACL-HLT 2013

Strany od

1000

Strany do

1009

Strany počet

10

URL

http://www.aclweb.org/anthology/N/N13/N13-1120.pdf

BibTex

@inproceedings{BUT105978,
  author="Alisa {Zhila} and Wen-tau {Yih} and Christopher {Meek} and Tomáš {Mikolov} and Geoffrey {Zweig}",
  title="Combining Heterogeneous Models for Measuring Relational Similarity",
  booktitle="Proceedings of NAACL-HLT 2013",
  year="2013",
  pages="1000--1009",
  publisher="Association for Computational Linguistics",
  address="Atlanata, Georgia",
  isbn="978-1-937284-47-3",
  url="http://www.aclweb.org/anthology/N/N13/N13-1120.pdf"
}