Harvesting Related Entities with a Search Engine

Shuqi Sun; Shiqi Zhao; Muyun Yang; Haifeng Wang; Sheng Li

Harvesting Related Entities with a Search Engine

Shuqi Sun
, Shiqi Zhao
, Muyun Yang
, Haifeng Wang
, Sheng Li

Faculty of Computing

Harbin Institute of Technology
Baidu Inc

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

Abstract

This paper addresses the problem of related entity extraction and focuses on extracting related persons as a case study. The proposed method builds on a search engine. Specifically, we mine candidate related persons for a query person q using q's search results and the query logs containing q. The acquired candidates are then automatically rated and ranked using a SVM regression model that investigates multiple features. Experimental results on a set of 200 randomly sampled query persons show that the precision of the extracted top-1, 5, and 10 related persons exceeds 91%, 90%, and 84%, respectively, which significantly outperforms a state-of-the-art baseline.

Original language	English
Title of host publication	IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing
Editors	Haifeng Wang, David Yarowsky
Publisher	Association for Computational Linguistics (ACL)
Pages	1019-1027
Number of pages	9
ISBN (Electronic)	9789744665645
State	Published - 2011
Event	5th International Joint Conference on Natural Language Processing, IJCNLP 2011 - Chiang Mai, Thailand Duration: 8 Nov 2011 → 13 Nov 2011

Publication series

Name	IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing

Conference

Conference	5th International Joint Conference on Natural Language Processing, IJCNLP 2011
Country/Territory	Thailand
City	Chiang Mai
Period	8/11/11 → 13/11/11

Cite this

Sun, S., Zhao, S., Yang, M., Wang, H., & Li, S. (2011). Harvesting Related Entities with a Search Engine. In H. Wang, & D. Yarowsky (Eds.), IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing (pp. 1019-1027). (IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing). Association for Computational Linguistics (ACL).

Sun, Shuqi ; Zhao, Shiqi ; Yang, Muyun et al. / Harvesting Related Entities with a Search Engine. IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing. editor / Haifeng Wang ; David Yarowsky. Association for Computational Linguistics (ACL), 2011. pp. 1019-1027 (IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing).

@inproceedings{038bd0de3b0149ca8119f7dddb528b05,

title = "Harvesting Related Entities with a Search Engine",

abstract = "This paper addresses the problem of related entity extraction and focuses on extracting related persons as a case study. The proposed method builds on a search engine. Specifically, we mine candidate related persons for a query person q using q's search results and the query logs containing q. The acquired candidates are then automatically rated and ranked using a SVM regression model that investigates multiple features. Experimental results on a set of 200 randomly sampled query persons show that the precision of the extracted top-1, 5, and 10 related persons exceeds 91\%, 90\%, and 84\%, respectively, which significantly outperforms a state-of-the-art baseline.",

author = "Shuqi Sun and Shiqi Zhao and Muyun Yang and Haifeng Wang and Sheng Li",

note = "Publisher Copyright: {\textcopyright} 2011 AFNLP; 5th International Joint Conference on Natural Language Processing, IJCNLP 2011 ; Conference date: 08-11-2011 Through 13-11-2011",

year = "2011",

language = "英语",

series = "IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing",

publisher = "Association for Computational Linguistics (ACL)",

pages = "1019--1027",

editor = "Haifeng Wang and David Yarowsky",

booktitle = "IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing",

address = "澳大利亚",

}

Sun, S, Zhao, S, Yang, M, Wang, H & Li, S 2011, Harvesting Related Entities with a Search Engine. in H Wang & D Yarowsky (eds), IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing. IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing, Association for Computational Linguistics (ACL), pp. 1019-1027, 5th International Joint Conference on Natural Language Processing, IJCNLP 2011, Chiang Mai, Thailand, 8/11/11.

Harvesting Related Entities with a Search Engine. / Sun, Shuqi; Zhao, Shiqi; Yang, Muyun et al.
IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing. ed. / Haifeng Wang; David Yarowsky. Association for Computational Linguistics (ACL), 2011. p. 1019-1027 (IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing).

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

TY - GEN

T1 - Harvesting Related Entities with a Search Engine

AU - Sun, Shuqi

AU - Zhao, Shiqi

AU - Yang, Muyun

AU - Wang, Haifeng

AU - Li, Sheng

PY - 2011

Y1 - 2011

N2 - This paper addresses the problem of related entity extraction and focuses on extracting related persons as a case study. The proposed method builds on a search engine. Specifically, we mine candidate related persons for a query person q using q's search results and the query logs containing q. The acquired candidates are then automatically rated and ranked using a SVM regression model that investigates multiple features. Experimental results on a set of 200 randomly sampled query persons show that the precision of the extracted top-1, 5, and 10 related persons exceeds 91%, 90%, and 84%, respectively, which significantly outperforms a state-of-the-art baseline.

AB - This paper addresses the problem of related entity extraction and focuses on extracting related persons as a case study. The proposed method builds on a search engine. Specifically, we mine candidate related persons for a query person q using q's search results and the query logs containing q. The acquired candidates are then automatically rated and ranked using a SVM regression model that investigates multiple features. Experimental results on a set of 200 randomly sampled query persons show that the precision of the extracted top-1, 5, and 10 related persons exceeds 91%, 90%, and 84%, respectively, which significantly outperforms a state-of-the-art baseline.

UR - https://www.scopus.com/pages/publications/85123571360

M3 - 会议稿件

AN - SCOPUS:85123571360

T3 - IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing

SP - 1019

EP - 1027

BT - IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing

A2 - Wang, Haifeng

A2 - Yarowsky, David

PB - Association for Computational Linguistics (ACL)

T2 - 5th International Joint Conference on Natural Language Processing, IJCNLP 2011

Y2 - 8 November 2011 through 13 November 2011

ER -

Sun S, Zhao S, Yang M, Wang H, Li S. Harvesting Related Entities with a Search Engine. In Wang H, Yarowsky D, editors, IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing. Association for Computational Linguistics (ACL). 2011. p. 1019-1027. (IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing).

Harvesting Related Entities with a Search Engine

Abstract

Publication series

Conference

Other files and links

Fingerprint

Cite this