Improving spatial semantic analysis by a combining model

Shiqi Li; Tiejun Zhao; Hanjing Li

doi:10.1109/ICEE.2010.363

Improving spatial semantic analysis by a combining model

Shiqi Li^*
, Tiejun Zhao
, Hanjing Li

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

This paper presents a combination base machine learning approach to spatial semantic analysis in Chinese. The model consists of multiple pre-training classifiers and a gating mechanism for integrating the outputs of these classifiers. Then we use EM algorithm to train the parameters of the combining model. Finally the experimental results show an overall improvement on the standard corpus CPB.

Original language	English
Title of host publication	Proceedings of the International Conference on E-Business and E-Government, ICEE 2010
Pages	1430-1433
Number of pages	4
DOIs	https://doi.org/10.1109/ICEE.2010.363
State	Published - 2010
Externally published	Yes
Event	1st International Conference on E-Business and E-Government, ICEE 2010 - Guangzhou, China Duration: 7 May 2010 → 9 May 2010

Publication series

Name	Proceedings of the International Conference on E-Business and E-Government, ICEE 2010

Conference

Conference	1st International Conference on E-Business and E-Government, ICEE 2010
Country/Territory	China
City	Guangzhou
Period	7/05/10 → 9/05/10

Keywords

Classifier combination
Mixture of experts
Spatial semantic analysis

Access to Document

10.1109/ICEE.2010.363

Cite this

@inproceedings{901b37c7360c4fb9bea634a40c511777,

title = "Improving spatial semantic analysis by a combining model",

abstract = "This paper presents a combination base machine learning approach to spatial semantic analysis in Chinese. The model consists of multiple pre-training classifiers and a gating mechanism for integrating the outputs of these classifiers. Then we use EM algorithm to train the parameters of the combining model. Finally the experimental results show an overall improvement on the standard corpus CPB.",

keywords = "Classifier combination, Mixture of experts, Spatial semantic analysis",

author = "Shiqi Li and Tiejun Zhao and Hanjing Li",

year = "2010",

doi = "10.1109/ICEE.2010.363",

language = "英语",

isbn = "9780769539973",

series = "Proceedings of the International Conference on E-Business and E-Government, ICEE 2010",

pages = "1430--1433",

booktitle = "Proceedings of the International Conference on E-Business and E-Government, ICEE 2010",

note = "1st International Conference on E-Business and E-Government, ICEE 2010 ; Conference date: 07-05-2010 Through 09-05-2010",

}

Li, S, Zhao, T & Li, H 2010, Improving spatial semantic analysis by a combining model. in Proceedings of the International Conference on E-Business and E-Government, ICEE 2010., 5591533, Proceedings of the International Conference on E-Business and E-Government, ICEE 2010, pp. 1430-1433, 1st International Conference on E-Business and E-Government, ICEE 2010, Guangzhou, China, 7/05/10. https://doi.org/10.1109/ICEE.2010.363

Improving spatial semantic analysis by a combining model. / Li, Shiqi; Zhao, Tiejun; Li, Hanjing.
Proceedings of the International Conference on E-Business and E-Government, ICEE 2010. 2010. p. 1430-1433 5591533 (Proceedings of the International Conference on E-Business and E-Government, ICEE 2010).

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

TY - GEN

T1 - Improving spatial semantic analysis by a combining model

AU - Li, Shiqi

AU - Zhao, Tiejun

AU - Li, Hanjing

PY - 2010

Y1 - 2010

N2 - This paper presents a combination base machine learning approach to spatial semantic analysis in Chinese. The model consists of multiple pre-training classifiers and a gating mechanism for integrating the outputs of these classifiers. Then we use EM algorithm to train the parameters of the combining model. Finally the experimental results show an overall improvement on the standard corpus CPB.

AB - This paper presents a combination base machine learning approach to spatial semantic analysis in Chinese. The model consists of multiple pre-training classifiers and a gating mechanism for integrating the outputs of these classifiers. Then we use EM algorithm to train the parameters of the combining model. Finally the experimental results show an overall improvement on the standard corpus CPB.

KW - Classifier combination

KW - Mixture of experts

KW - Spatial semantic analysis

UR - https://www.scopus.com/pages/publications/78649637247

U2 - 10.1109/ICEE.2010.363

DO - 10.1109/ICEE.2010.363

M3 - 会议稿件

AN - SCOPUS:78649637247

SN - 9780769539973

T3 - Proceedings of the International Conference on E-Business and E-Government, ICEE 2010

SP - 1430

EP - 1433

BT - Proceedings of the International Conference on E-Business and E-Government, ICEE 2010

T2 - 1st International Conference on E-Business and E-Government, ICEE 2010

Y2 - 7 May 2010 through 9 May 2010

ER -

Improving spatial semantic analysis by a combining model

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this