A joint classification method to integrate scientific and social networks

Mahmood Neshati, Ehsaneddin Asgari, Djoerd Hiemstra, Hamid Beigy

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

6 Citations (Scopus)

Abstract

In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks. Utilizing several name similarity patterns and contextual properties of these networks, we design a focused crawler to find high probable matching pairs, then the problem of name disambiguation is reduced to predict the label of each candidate pair as either true or false matching. By defining matching dependency graph, we propose a joint label prediction model to determine the label of all candidate pairs simultaneously. An extensive set of experiments have been conducted on six test collections obtained from the DBLP and the Twitter networks to show the effectiveness of the proposed joint label prediction model.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages122-133
Number of pages12
Volume7814 LNCS
DOIs
Publication statusPublished - 2 Apr 2013
Event35th European Conference on Information Retrieval, ECIR 2013 - Moscow, Russian Federation
Duration: 24 Mar 201327 Mar 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7814 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other35th European Conference on Information Retrieval, ECIR 2013
CountryRussian Federation
CityMoscow
Period24/3/1327/3/13

Fingerprint

Social Networks
Labels
Integrate
Prediction Model
Dependency Graph
Network Design
Probable
Predict
Experiment
Experiments
Relationships
Similarity
False

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Neshati, M., Asgari, E., Hiemstra, D., & Beigy, H. (2013). A joint classification method to integrate scientific and social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7814 LNCS, pp. 122-133). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7814 LNCS). https://doi.org/10.1007/978-3-642-36973-5_11

A joint classification method to integrate scientific and social networks. / Neshati, Mahmood; Asgari, Ehsaneddin; Hiemstra, Djoerd; Beigy, Hamid.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7814 LNCS 2013. p. 122-133 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7814 LNCS).

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

Neshati, M, Asgari, E, Hiemstra, D & Beigy, H 2013, A joint classification method to integrate scientific and social networks. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7814 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7814 LNCS, pp. 122-133, 35th European Conference on Information Retrieval, ECIR 2013, Moscow, Russian Federation, 24/3/13. https://doi.org/10.1007/978-3-642-36973-5_11
Neshati M, Asgari E, Hiemstra D, Beigy H. A joint classification method to integrate scientific and social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7814 LNCS. 2013. p. 122-133. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-36973-5_11
Neshati, Mahmood ; Asgari, Ehsaneddin ; Hiemstra, Djoerd ; Beigy, Hamid. / A joint classification method to integrate scientific and social networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7814 LNCS 2013. pp. 122-133 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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