Cross-lingual type inference

Bo Xu; Yi Zhang; Jiaqing Liang; Yanghua Xiao; Seung Won Hwang; Wei Wang

doi:10.1007/978-3-319-32025-0_28

Cross-lingual type inference

Bo Xu, Yi Zhang, Jiaqing Liang, Yanghua Xiao, Seung Won Hwang, Wei Wang

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

20 Citations (Scopus)

Abstract

Entity typing is an essential task for constructing a knowledge base. However, many non-English knowledge bases fail to type their entities due to the absence of a reasonable local hierarchical taxonomy. Since constructing a widely accepted taxonomy is a hard problem, we propose to type these non-English entities with some widely accepted taxonomies in English, such as DBpedia, Yago and Freebase. We define this problem as cross-lingual type inference. In this paper, we present CUTE to type Chinese entities with DBpedia types. First we exploit the cross-lingual entity linking between Chinese and English entities to construct the training data. Then we propose a multi-label hierarchical classification algorithm to type these Chinese entities. Experimental results show the effectiveness and efficiency of our method.

Original language	English
Title of host publication	Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings
Editors	Shamkant B. Navathe, Weili Wu, Shashi Shekhar, Xiaoyong Du, Hui Xiong, X. Sean Wang
Publisher	Springer Verlag
Pages	447-462
Number of pages	16
ISBN (Print)	9783319320243
DOIs	https://doi.org/10.1007/978-3-319-32025-0_28
Publication status	Published - 2016
Event	21st International Conference on Database Systems for Advanced Applications, DASFAA 2016 - Dallas, United States Duration: 2016 Apr 16 → 2016 Apr 19

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9642
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	21st International Conference on Database Systems for Advanced Applications, DASFAA 2016
Country/Territory	United States
City	Dallas
Period	16/4/16 → 16/4/19

Bibliographical note

Funding Information:
Y. Xiao—This paper was supported by the National NSFC (No. 61472085, 61171132, 61033010, U1509213), by National Key Basic Research Program of China under No. 2015CB358800, by Shanghai Municipal Science and Technology Commission foundation key project under No. 15JC1400900. Seung-won Hwang was supported by Microsoft.

Publisher Copyright:
© Springer International Publishing Switzerland 2016.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-32025-0_28

Cite this

Xu, B., Zhang, Y., Liang, J., Xiao, Y., Hwang, S. W., & Wang, W. (2016). Cross-lingual type inference. In S. B. Navathe, W. Wu, S. Shekhar, X. Du, H. Xiong, & X. S. Wang (Eds.), Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings (pp. 447-462). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9642). Springer Verlag. https://doi.org/10.1007/978-3-319-32025-0_28

Xu, Bo ; Zhang, Yi ; Liang, Jiaqing et al. / Cross-lingual type inference. Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings. editor / Shamkant B. Navathe ; Weili Wu ; Shashi Shekhar ; Xiaoyong Du ; Hui Xiong ; X. Sean Wang. Springer Verlag, 2016. pp. 447-462 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Cross-lingual type inference",

abstract = "Entity typing is an essential task for constructing a knowledge base. However, many non-English knowledge bases fail to type their entities due to the absence of a reasonable local hierarchical taxonomy. Since constructing a widely accepted taxonomy is a hard problem, we propose to type these non-English entities with some widely accepted taxonomies in English, such as DBpedia, Yago and Freebase. We define this problem as cross-lingual type inference. In this paper, we present CUTE to type Chinese entities with DBpedia types. First we exploit the cross-lingual entity linking between Chinese and English entities to construct the training data. Then we propose a multi-label hierarchical classification algorithm to type these Chinese entities. Experimental results show the effectiveness and efficiency of our method.",

author = "Bo Xu and Yi Zhang and Jiaqing Liang and Yanghua Xiao and Hwang, {Seung Won} and Wei Wang",

note = "Funding Information: Y. Xiao—This paper was supported by the National NSFC (No. 61472085, 61171132, 61033010, U1509213), by National Key Basic Research Program of China under No. 2015CB358800, by Shanghai Municipal Science and Technology Commission foundation key project under No. 15JC1400900. Seung-won Hwang was supported by Microsoft. Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016 ; Conference date: 16-04-2016 Through 19-04-2016",

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doi = "10.1007/978-3-319-32025-0_28",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Xu, B, Zhang, Y, Liang, J, Xiao, Y, Hwang, SW & Wang, W 2016, Cross-lingual type inference. in SB Navathe, W Wu, S Shekhar, X Du, H Xiong & XS Wang (eds), Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9642, Springer Verlag, pp. 447-462, 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016, Dallas, United States, 16/4/16. https://doi.org/10.1007/978-3-319-32025-0_28

Cross-lingual type inference. / Xu, Bo; Zhang, Yi; Liang, Jiaqing et al.
Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings. ed. / Shamkant B. Navathe; Weili Wu; Shashi Shekhar; Xiaoyong Du; Hui Xiong; X. Sean Wang. Springer Verlag, 2016. p. 447-462 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9642).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Cross-lingual type inference

AU - Xu, Bo

AU - Zhang, Yi

AU - Liang, Jiaqing

AU - Xiao, Yanghua

AU - Hwang, Seung Won

AU - Wang, Wei

N1 - Funding Information: Y. Xiao—This paper was supported by the National NSFC (No. 61472085, 61171132, 61033010, U1509213), by National Key Basic Research Program of China under No. 2015CB358800, by Shanghai Municipal Science and Technology Commission foundation key project under No. 15JC1400900. Seung-won Hwang was supported by Microsoft. Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - Entity typing is an essential task for constructing a knowledge base. However, many non-English knowledge bases fail to type their entities due to the absence of a reasonable local hierarchical taxonomy. Since constructing a widely accepted taxonomy is a hard problem, we propose to type these non-English entities with some widely accepted taxonomies in English, such as DBpedia, Yago and Freebase. We define this problem as cross-lingual type inference. In this paper, we present CUTE to type Chinese entities with DBpedia types. First we exploit the cross-lingual entity linking between Chinese and English entities to construct the training data. Then we propose a multi-label hierarchical classification algorithm to type these Chinese entities. Experimental results show the effectiveness and efficiency of our method.

AB - Entity typing is an essential task for constructing a knowledge base. However, many non-English knowledge bases fail to type their entities due to the absence of a reasonable local hierarchical taxonomy. Since constructing a widely accepted taxonomy is a hard problem, we propose to type these non-English entities with some widely accepted taxonomies in English, such as DBpedia, Yago and Freebase. We define this problem as cross-lingual type inference. In this paper, we present CUTE to type Chinese entities with DBpedia types. First we exploit the cross-lingual entity linking between Chinese and English entities to construct the training data. Then we propose a multi-label hierarchical classification algorithm to type these Chinese entities. Experimental results show the effectiveness and efficiency of our method.

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DO - 10.1007/978-3-319-32025-0_28

M3 - Conference contribution

AN - SCOPUS:84962440923

SN - 9783319320243

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 447

EP - 462

BT - Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings

A2 - Navathe, Shamkant B.

A2 - Wu, Weili

A2 - Shekhar, Shashi

A2 - Du, Xiaoyong

A2 - Xiong, Hui

A2 - Wang, X. Sean

PB - Springer Verlag

T2 - 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016

Y2 - 16 April 2016 through 19 April 2016

ER -

Xu B, Zhang Y, Liang J, Xiao Y, Hwang SW, Wang W. Cross-lingual type inference. In Navathe SB, Wu W, Shekhar S, Du X, Xiong H, Wang XS, editors, Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings. Springer Verlag. 2016. p. 447-462. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-32025-0_28

Cross-lingual type inference

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