Entity relationship extraction based on potential relationship pattern

Chen Chen; Huilin Liu; Guoren Wang; Linlin Ding; Lili Yu

doi:10.1007/978-3-642-16515-3_46

Entity relationship extraction based on potential relationship pattern

Chen Chen^*, Huilin Liu, Guoren Wang, Linlin Ding, Lili Yu

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

The keep rising of web information ensures the development of entity focused information retrieval system. However, the problem of mining the relationships effectively between entities has not been well resolved. For the entity relationship extraction (RE) problem, this paper firstly establishes the basic pattern trees which can present the overall relation structures and then designs a similarity function according to which we can judge which pattern the sentence containing two entities belongs to. Knowing the matched pattern, we can discovery the relationship easily. By a large number of experiments on real data, the proposed methods are proved running accurately and efficiently.

Original language	English
Title of host publication	Web Information Systems and Mining - International Conference, WISM 2010, Proceedings
Pages	370-377
Number of pages	8
Edition	M4D
DOIs	https://doi.org/10.1007/978-3-642-16515-3_46
Publication status	Published - 2010
Externally published	Yes
Event	2010 International Conference on Web Information Systems and Mining, WISM 2010 - Sanya, China Duration: 23 Oct 2010 → 24 Oct 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	M4D
Volume	6318 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2010 International Conference on Web Information Systems and Mining, WISM 2010
Country/Territory	China
City	Sanya
Period	23/10/10 → 24/10/10

Keywords

Entity
Pattern
Relationship extraction
Similarity function

Access to Document

10.1007/978-3-642-16515-3_46

Cite this

Chen, C., Liu, H., Wang, G., Ding, L., & Yu, L. (2010). Entity relationship extraction based on potential relationship pattern. In Web Information Systems and Mining - International Conference, WISM 2010, Proceedings (M4D ed., pp. 370-377). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6318 LNCS, No. M4D). https://doi.org/10.1007/978-3-642-16515-3_46

Chen, Chen ; Liu, Huilin ; Wang, Guoren et al. / Entity relationship extraction based on potential relationship pattern. Web Information Systems and Mining - International Conference, WISM 2010, Proceedings. M4D. ed. 2010. pp. 370-377 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); M4D).

@inproceedings{1cc30e7055d244caa5cdf7554f568bbd,

title = "Entity relationship extraction based on potential relationship pattern",

abstract = "The keep rising of web information ensures the development of entity focused information retrieval system. However, the problem of mining the relationships effectively between entities has not been well resolved. For the entity relationship extraction (RE) problem, this paper firstly establishes the basic pattern trees which can present the overall relation structures and then designs a similarity function according to which we can judge which pattern the sentence containing two entities belongs to. Knowing the matched pattern, we can discovery the relationship easily. By a large number of experiments on real data, the proposed methods are proved running accurately and efficiently.",

keywords = "Entity, Pattern, Relationship extraction, Similarity function",

author = "Chen Chen and Huilin Liu and Guoren Wang and Linlin Ding and Lili Yu",

year = "2010",

doi = "10.1007/978-3-642-16515-3_46",

language = "English",

isbn = "3642165141",

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

number = "M4D",

pages = "370--377",

booktitle = "Web Information Systems and Mining - International Conference, WISM 2010, Proceedings",

edition = "M4D",

note = "2010 International Conference on Web Information Systems and Mining, WISM 2010 ; Conference date: 23-10-2010 Through 24-10-2010",

}

Chen, C, Liu, H, Wang, G, Ding, L & Yu, L 2010, Entity relationship extraction based on potential relationship pattern. in Web Information Systems and Mining - International Conference, WISM 2010, Proceedings. M4D edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. M4D, vol. 6318 LNCS, pp. 370-377, 2010 International Conference on Web Information Systems and Mining, WISM 2010, Sanya, China, 23/10/10. https://doi.org/10.1007/978-3-642-16515-3_46

Entity relationship extraction based on potential relationship pattern. / Chen, Chen; Liu, Huilin; Wang, Guoren et al.
Web Information Systems and Mining - International Conference, WISM 2010, Proceedings. M4D. ed. 2010. p. 370-377 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6318 LNCS, No. M4D).

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

TY - GEN

T1 - Entity relationship extraction based on potential relationship pattern

AU - Chen, Chen

AU - Liu, Huilin

AU - Wang, Guoren

AU - Ding, Linlin

AU - Yu, Lili

PY - 2010

Y1 - 2010

N2 - The keep rising of web information ensures the development of entity focused information retrieval system. However, the problem of mining the relationships effectively between entities has not been well resolved. For the entity relationship extraction (RE) problem, this paper firstly establishes the basic pattern trees which can present the overall relation structures and then designs a similarity function according to which we can judge which pattern the sentence containing two entities belongs to. Knowing the matched pattern, we can discovery the relationship easily. By a large number of experiments on real data, the proposed methods are proved running accurately and efficiently.

AB - The keep rising of web information ensures the development of entity focused information retrieval system. However, the problem of mining the relationships effectively between entities has not been well resolved. For the entity relationship extraction (RE) problem, this paper firstly establishes the basic pattern trees which can present the overall relation structures and then designs a similarity function according to which we can judge which pattern the sentence containing two entities belongs to. Knowing the matched pattern, we can discovery the relationship easily. By a large number of experiments on real data, the proposed methods are proved running accurately and efficiently.

KW - Entity

KW - Pattern

KW - Relationship extraction

KW - Similarity function

UR - http://www.scopus.com/inward/record.url?scp=78649509188&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-16515-3_46

DO - 10.1007/978-3-642-16515-3_46

M3 - Conference contribution

AN - SCOPUS:78649509188

SN - 3642165141

SN - 9783642165146

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

SP - 370

EP - 377

BT - Web Information Systems and Mining - International Conference, WISM 2010, Proceedings

T2 - 2010 International Conference on Web Information Systems and Mining, WISM 2010

Y2 - 23 October 2010 through 24 October 2010

ER -

Chen C, Liu H, Wang G, Ding L, Yu L. Entity relationship extraction based on potential relationship pattern. In Web Information Systems and Mining - International Conference, WISM 2010, Proceedings. M4D ed. 2010. p. 370-377. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); M4D). doi: 10.1007/978-3-642-16515-3_46

Entity relationship extraction based on potential relationship pattern

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this