Superficial method for extracting social network for academics using web snippets

Mahyuddin K M Nasution, Shahrul Azman Mohd Noah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

Social network analysis (SNA) has become one of the main themes in the Semantic Web agenda. The use of web is steadily gaining ground in the study of social networks. Few researchers have shown the possibility of extracting social network from the Web via search engine. However to get a rich and trusted social network from such an approach proved to be difficult. In this paper we proposed an Information Retrieval (IR) driven method for dealing with the heterogeneity of features in the Web. We demontrate the possibility of exploiting features in Web snippets returned by search engines for disambiguating entities and building relations among entities during the process of extracting social networks. Our approach has shown the capacity to extract underlying strength relations which are beyond recognition using the standard co-occurrence analysis employed by many research.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages483-490
Number of pages8
Volume6401 LNAI
DOIs
Publication statusPublished - 2010
Event5th International Conference on Rough Set and Knowledge Technology, RSKT 2010 - Beijing
Duration: 15 Oct 201017 Oct 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6401 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Conference on Rough Set and Knowledge Technology, RSKT 2010
CityBeijing
Period15/10/1017/10/10

Fingerprint

Search engines
World Wide Web
Social Networks
Semantic Web
Electric network analysis
Information retrieval
Search Engine
Social Network Analysis
Web Search
Information Retrieval

Keywords

  • Jaccard coefficient
  • Semantic Web
  • Social networks analysis
  • TFIDF

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Nasution, M. K. M., & Mohd Noah, S. A. (2010). Superficial method for extracting social network for academics using web snippets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6401 LNAI, pp. 483-490). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6401 LNAI). https://doi.org/10.1007/978-3-642-16248-0_68

Superficial method for extracting social network for academics using web snippets. / Nasution, Mahyuddin K M; Mohd Noah, Shahrul Azman.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI 2010. p. 483-490 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6401 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nasution, MKM & Mohd Noah, SA 2010, Superficial method for extracting social network for academics using web snippets. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6401 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6401 LNAI, pp. 483-490, 5th International Conference on Rough Set and Knowledge Technology, RSKT 2010, Beijing, 15/10/10. https://doi.org/10.1007/978-3-642-16248-0_68
Nasution MKM, Mohd Noah SA. Superficial method for extracting social network for academics using web snippets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI. 2010. p. 483-490. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-16248-0_68
Nasution, Mahyuddin K M ; Mohd Noah, Shahrul Azman. / Superficial method for extracting social network for academics using web snippets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI 2010. pp. 483-490 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{aeb7e36f26aa44b982efbd97b0670790,
title = "Superficial method for extracting social network for academics using web snippets",
abstract = "Social network analysis (SNA) has become one of the main themes in the Semantic Web agenda. The use of web is steadily gaining ground in the study of social networks. Few researchers have shown the possibility of extracting social network from the Web via search engine. However to get a rich and trusted social network from such an approach proved to be difficult. In this paper we proposed an Information Retrieval (IR) driven method for dealing with the heterogeneity of features in the Web. We demontrate the possibility of exploiting features in Web snippets returned by search engines for disambiguating entities and building relations among entities during the process of extracting social networks. Our approach has shown the capacity to extract underlying strength relations which are beyond recognition using the standard co-occurrence analysis employed by many research.",
keywords = "Jaccard coefficient, Semantic Web, Social networks analysis, TFIDF",
author = "Nasution, {Mahyuddin K M} and {Mohd Noah}, {Shahrul Azman}",
year = "2010",
doi = "10.1007/978-3-642-16248-0_68",
language = "English",
isbn = "3642162479",
volume = "6401 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "483--490",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Superficial method for extracting social network for academics using web snippets

AU - Nasution, Mahyuddin K M

AU - Mohd Noah, Shahrul Azman

PY - 2010

Y1 - 2010

N2 - Social network analysis (SNA) has become one of the main themes in the Semantic Web agenda. The use of web is steadily gaining ground in the study of social networks. Few researchers have shown the possibility of extracting social network from the Web via search engine. However to get a rich and trusted social network from such an approach proved to be difficult. In this paper we proposed an Information Retrieval (IR) driven method for dealing with the heterogeneity of features in the Web. We demontrate the possibility of exploiting features in Web snippets returned by search engines for disambiguating entities and building relations among entities during the process of extracting social networks. Our approach has shown the capacity to extract underlying strength relations which are beyond recognition using the standard co-occurrence analysis employed by many research.

AB - Social network analysis (SNA) has become one of the main themes in the Semantic Web agenda. The use of web is steadily gaining ground in the study of social networks. Few researchers have shown the possibility of extracting social network from the Web via search engine. However to get a rich and trusted social network from such an approach proved to be difficult. In this paper we proposed an Information Retrieval (IR) driven method for dealing with the heterogeneity of features in the Web. We demontrate the possibility of exploiting features in Web snippets returned by search engines for disambiguating entities and building relations among entities during the process of extracting social networks. Our approach has shown the capacity to extract underlying strength relations which are beyond recognition using the standard co-occurrence analysis employed by many research.

KW - Jaccard coefficient

KW - Semantic Web

KW - Social networks analysis

KW - TFIDF

UR - http://www.scopus.com/inward/record.url?scp=78349257765&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78349257765&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-16248-0_68

DO - 10.1007/978-3-642-16248-0_68

M3 - Conference contribution

AN - SCOPUS:78349257765

SN - 3642162479

SN - 9783642162473

VL - 6401 LNAI

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

SP - 483

EP - 490

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

ER -