Publication result 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

English Title

Combining Heterogeneous Models for Measuring Relational Similarity

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

In this paper, we presented a system that combinesheterogeneous models based on different informationsources for measuring relational similarity.

English abstract

In this paper, we presented a system that combinesheterogeneous models based on different informationsources for measuring relational similarity.

Keywords

language modeling, heterogeneous models, recurrent neural networks

Key words in English

language modeling, heterogeneous models, recurrent neural networks

Authors

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

RIV year

2014

Released

09.06.2013

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"
}