Finding rising stars in heterogeneous social networks

Pivithuru Wijegunawardana, Kishan Mehrotra, Chilukuri Mohan

Research output: Chapter in Book/Entry/PoemConference contribution

9 Scopus citations

Abstract

A rising star is an individual who shows the potential to become a star in the near future. We investigate the problem of finding rising stars when heterogeneous data sources are available to define the same person. The proposed solution examines multiple data sources to determine how the importance of an individual improves over time. Scores from different data sources are combined using a multi-objective optimization approach, as well as a rank aggregation approach. Compared with existing methods, our approach identifies rising stars with higher h-index, number of papers and citation count in the academic domain. Further, we show that the new approach can also be applied to other data sources such as the Information Security Stack Exchange question answer forum.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016
EditorsAnna Esposito, Miltos Alamaniotis, Amol Mali, Nikolaos Bourbakis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages614-618
Number of pages5
ISBN (Electronic)9781509044597
DOIs
StatePublished - Jan 11 2017
Event28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016 - San Jose, United States
Duration: Nov 6 2016Nov 8 2016

Publication series

NameProceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016

Other

Other28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016
Country/TerritoryUnited States
CitySan Jose
Period11/6/1611/8/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

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