Publication detail

Combining Heterogeneous Models for Measuring Relational Similarity

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

Original Title

Combining Heterogeneous Models for Measuring Relational Similarity

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

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

Keywords

language modeling, heterogeneous models, recurrent neural networks

Authors

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

RIV year

2013

Released

9. 6. 2013

Publisher

Association for Computational Linguistics

Location

Atlanata, Georgia

ISBN

978-1-937284-47-3

Book

Proceedings of NAACL-HLT 2013

Pages from

1000

Pages to

1009

Pages count

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"
}