La Cueva (56)

= Optimizing Community Detection =

Awards

 * 3rd Prize
 * Women in Science and Engineering

Team
The La Cueva High School team (#56) is from ABQ.

Team Members

 * Lauren Li
 * Stephanie Djidjev
 * Alexandra Porter

Sponsoring Teacher

 * Samuel Smith

Complete Challenge Entry: Final Report, Source Code, Website, Video
Final Report
 * Written Final Report

Source Code
 * Code is contained in an appendix of the pdf

Web Version of Final Report
 * Web version of Final Report

Video
 * Need link to YouTube Video to Finalist Judges

Comments from Judges
As describe in the final report this project creates a possibly original tool for studying problems in a wide variety of application areas. --Drew 16:27, 28 April 2012 (PDT)

Written Final Report Needs Update
My impression after reading the currently available written Final Report, was that I believed this team accomplished a lot more than was successfully communicated in the written report. I had many questions about this project and none of them were answered in the report. This impression was confirmed when all of my questions were answered in the oral presentation. --Drew 16:27, 28 April 2012 (PDT)

Prior Years Work
Last year Stephanie was a member of team 66 which worked on an Ant Colony Optimization. This year Stephanie joined a new team applying Ant Colony Optimization techniques instead of parallelizing last year's code. --Drew 16:27, 28 April 2012 (PDT)

Improper use of graph theory terminology
Cleve was upset that the team did not use the proper graph theory terminology for what they are doing, graph partitioning. Using incorrect terminology may have prevented the team from finding prior research in this well studied area. Algorithms and Software for Partitioning Graphs

--Drew 16:02, 28 April 2012 (PDT)

Suggestions for future research
Stephanie and Alexandra are graduating this year. I hope Lauren recruits some new team members and continues this promising research. The techniques described in this project may well be original and useful. I will be disappointed if we do not see how this research turns out.

--Drew 16:54, 28 April 2012 (PDT)

Apply the tools to large graphs in a variety of disciplines

 * choose several interesting applications from among the areas discussed in this years report:
 * biological networks and pathways,
 * metabolic networks,
 * the Internet,
 * social networks,
 * citation networks,
 * economic networks, etc.
 * with thousands, if not millions of nodes.
 * interpret the results.

Use 3rd party tools for graph partitioning

 * Compare results with standard graph partitioning algorithms.
 * Compare results with your novel Ant Colony Optimization based technique.

--Drew 16:36, 28 April 2012 (PDT)

Performance issues with large graphs
Many of the standard algorithms scale poorly with large graphs.

Your novel ACO based algorithm may perform much better.

Consider using the parallelization techniques developed by Team 66 in this year's competition.

--Drew 16:02, 28 April 2012 (PDT)

Continuing this research next year
Has a lot of potential, even if your algorithm does not turn out to be better than standard algorithms.

--Drew 21:47, 17 May 2012 (PDT)

History: Proposal, Interim Report

 * La Cueva (56)/Proposal
 * La Cueva (56)/Interim Report