Abstract

A common problem in network analysis is detecting small subgraphs of interest within a large background graph. This includes multi-source fusion scenarios where data from several modalities must be integrated to form the network. This paper presents an application of novel techniques leveraging the signal processing for graphs algorithmic framework, to well-studied collaboration networks in the field of evolutionary biology. Our multi-disciplinary approach allows us to leverage case studies of transformative periods in this scientific field as truth. We build on previous work by optimizing the temporal integration filters with respect to truth data using a tensor decomposition method that maximizes the spectral norm of the integrated subgraph's adjacency matrix. We also demonstrate that we can mitigate data corruption via fusion of different data sources, demonstrating the power of this analysis framework for incomplete and corrupted data.

Original languageEnglish (US)
Title of host publication2015 18th International Conference on Information Fusion, Fusion 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages659-665
Number of pages7
ISBN (Print)9780982443866
StatePublished - Sep 14 2015
Event18th International Conference on Information Fusion, Fusion 2015 - Washington, United States
Duration: Jul 6 2015Jul 9 2015

Other

Other18th International Conference on Information Fusion, Fusion 2015
CountryUnited States
CityWashington
Period7/6/157/9/15

Fingerprint

Fusion reactions
Innovation
Electric network analysis
Tensors
Signal processing
Decomposition

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing
  • Computer Networks and Communications

Cite this

Miller, B. A., Beard, M. S., Laubichler, M., & Bliss, N. (2015). Temporal and multi-source fusion for detection of innovation in collaboration networks. In 2015 18th International Conference on Information Fusion, Fusion 2015 (pp. 659-665). [7266623] Institute of Electrical and Electronics Engineers Inc..

Temporal and multi-source fusion for detection of innovation in collaboration networks. / Miller, Benjamin A.; Beard, Michelle S.; Laubichler, Manfred; Bliss, Nadya.

2015 18th International Conference on Information Fusion, Fusion 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 659-665 7266623.

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

Miller, BA, Beard, MS, Laubichler, M & Bliss, N 2015, Temporal and multi-source fusion for detection of innovation in collaboration networks. in 2015 18th International Conference on Information Fusion, Fusion 2015., 7266623, Institute of Electrical and Electronics Engineers Inc., pp. 659-665, 18th International Conference on Information Fusion, Fusion 2015, Washington, United States, 7/6/15.
Miller BA, Beard MS, Laubichler M, Bliss N. Temporal and multi-source fusion for detection of innovation in collaboration networks. In 2015 18th International Conference on Information Fusion, Fusion 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 659-665. 7266623
Miller, Benjamin A. ; Beard, Michelle S. ; Laubichler, Manfred ; Bliss, Nadya. / Temporal and multi-source fusion for detection of innovation in collaboration networks. 2015 18th International Conference on Information Fusion, Fusion 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 659-665
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