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15.2 - Predicting Future Relations: Incremental and Robust Link Prediction

Project - Summary


The project aims to develop and evaluate a robust link predicting methods incorporating ensemble and incremental learning capability. The objectives are to:

  • Implement multiple link prediction methods
  • Develop and evaluate the ensemble link prediction methods
  • Develop an incremental learning method and evaluate the performance of the model
  • Design and implement an interactive visualization system

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Vijay Raghavan PI Not available Not available UL Lafayette
Raju Gottumukkala PI Not available Not available UL Lafayette
Ryan Benton PI Not available Not available University of South Alabama
Murali K. Pusala Graduate Student Not available Not available UL Lafayette
Amirhossein Tavanaei Graduate Student Not available Not available UL Lafayette
Narendra Sanikommu Graduate Student Not available Not available UL Lafayette
Jaya Krishna Graduate Student Not available Not available UL Lafayette

Project - Impact and Uses/Benefits

We evaluated the proposed robust and efficient link prediction system with high level of performance in purpose of generating the possible hypothesis using biomedical literature. However, our model can be applied to a wide variety of problems, which can be modeled as graphs. Furthermore, we are working with Schumacher Clinical Partners to employ the link prediction model in predicting the medical conditions of patients.

Project - Deep Dive

Project - Documents

FilenameFilesizeLast modified
15.9_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.9_year_4_executive_summary.pdf287.8 KiB2019/08/22 11:50
15.6_year_4_executive_summary.pdf159.6 KiB2019/08/22 11:50
15.8_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.8_year_4_executive_summary.pdf160.0 KiB2019/08/22 11:50
15.3_year_4_presentation.pptx2.2 MiB2019/08/22 11:50
15.5_year_4_quad_chart.pptx1.4 MiB2019/08/22 11:50
15.4_year_4_presentation.pdf2.2 MiB2019/08/22 11:50
15.7_year_4_executive_summary.pdf157.5 KiB2019/08/22 11:50
15.7_year_4_presentation.pdf699.1 KiB2019/08/22 11:50
15.5_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.7_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.6_year_4_quad.pptx1.5 MiB2019/08/22 11:50
15.5_year_4_presentation.pptx2.5 MiB2019/08/22 11:50
15.6_year_4_presentation.pptx2.4 MiB2019/08/22 11:50
15.6_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.4_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.1_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.2_year_4_executive_summary.pdf172.6 KiB2019/08/22 11:50
15.2_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.3_year_4_quad_chart.pptx1.3 MiB2019/08/22 11:50
15.1_year_4_executive_summary.pdf162.5 KiB2019/08/22 11:50
15.1_year_4_presentation.pptx2.0 MiB2019/08/22 11:50
15.3_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.4_year_4_executive_summary.pdf163.1 KiB2019/08/22 11:50
15.3_year_4_executive_summary.pdf175.3 KiB2019/08/22 11:50
15.1_year_4_quad_chart.pptx1.3 MiB2019/08/22 11:50
15.5_year_4_executive_summary.pdf155.1 KiB2019/08/22 11:50
15.9_year_4_final_report.pdf1.0 MiB2019/08/22 10:33
15.5_year_4_final_report.pdf1.4 MiB2019/08/22 10:33
15.2_year_4_final_report.pdf1.4 MiB2019/08/22 10:33
15.8_year_4_final_report.pdf1.6 MiB2019/08/22 10:33
15.7_year_4_final_report.pdf370.1 KiB2019/08/22 10:33
15.4_year_4_final_report.pdf985.6 KiB2019/08/22 10:33
15.3_year_4_final_report.pdf1.1 MiB2019/08/22 10:33
15.6_year_4_final_report.pdf627.9 KiB2019/08/22 10:33
15.1_year_4_final_report.pdf899.0 KiB2019/08/22 10:33
projects/year4/15.2.1566487832.txt.gz · Last modified: 2019/08/22 10:30 by sally.johnson