Find Your Circles presentation

Network isalways the answer

Carlos Herrera Yagüe PhD Candidate @UPM@cyague

Alberto Asuero ArroyoSoft Engineer @Geographica

@alasarr

Thursday, December 8, 2011

@findyourcircles


@findyourcircles

This structure is optimal in many ways (humidity, temperature...).


@findyourcircles



@findyourcircles


How was it made by such a simple animal?


@findyourcircles


@findyourcircles

Probably is more likely to explain it by considering it was made by

many of these. A map of the interactions may be the key.


java.com

en.wikipedia.org/Java

forodejava.com

aprender-java.blogspot.com

How to sort results in a web search?

@findyourcircles


java.com


forodejava.com



Semantics?

@findyourcircles


java.com


forodejava.com



Semantics?

Number of visits?

@findyourcircles


java.com


forodejava.com



Semantics?

Number of visits?

What if we drawthe web as a network?

@findyourcircles


java.com


forodejava.com aprender-java.blog


@findyourcircles


java.com




@findyourcircles


java.com




@findyourcircles


How to group friends in a facebook profile?

@findyourcircles



Name Age Lives in Is from College

Victor 25 Usal

Javier 25 Madrid Salamanca Upco

Miguel 25

Pepe 25 Madrid Salamanca Uax

Ana 24 Madrid Santander Upm

Inés 25 Santander Salamanca

Alberto 25 Sevilla Huelva Uam

@findyourcircles


Name Age Lives in Is from CollegeVictor 25 UsalJavier 25 Madrid Salamanca UpcoMiguel 25 SalamancaPepe 25 Madrid Salamanca UaxAna 24 Madrid Santander UpmInés 25 Santander SalamancaAlberto 25 Sevilla Huelva UamCarlos 25 Madrid Salamanca Upm

@findyourcircles


Smart lists solution


@findyourcircles



@findyourcircles



@findyourcircles



And only you came up with this?


And only you came up with this?★Yong-Yeol Ahn, James P. Bagrow and Sune Lehmann, "Link communities reveal multiscale complexity in networks", Nature 455 (2010): 761--764,arxiv:0903.3178 [Lehmann's blog-post on this]★Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg and Eric P. Xing, "Mixed membership stochastic blockmodels", arxiv:0705.4485★Nelson Augusto Alves, "Unveiling community structures in weighted networks", physics/0703087★Leonardo Angelini, Stefano Boccaletti, Daniele Marinazzo, Mario Pellicoro, and Sebastiano Stramaglia, "Fast identification of network modules by optimization of ratio association", cond-mat/0610182★L. Angelini, D. Marinazzo, M. Pellicoro and S. Stramaglia, "Natural clustering: the modularity approach", cond-mat/0607643★Alex Arenas, Javier Borge-Holthoefer, Sergio Gomez, Gorka Zamora-Lopez, "Optimal map of the modular structure of complex networks", New Journal of Physics 12 (2010): 053009, arxiv:0911.2651★A. Arenas, J. Duch, A. Fernandez, S. Gomez, "Size reduction of complex networks preserving modularity", physics/0702015 [Do you really need all those links? Wouldn't your life be simpler if you could just ignore some of them?]★Alex Arenas, Alberto Fernandez, Sergio Gomez, "Multiple resolution of the modular structure of complex networks", physics/0703218★Alex Arenas, Alberto Fernandez, Santo Fortunato, Sergio Gomez, "Motif-based communities in complex networks", arxiv:0710.0059★Jim Bagrow and Erik Bollt, "A Local Method for Detecting Communities",cond-mat/0412482★James Bagrow, Erik Bollt, Luciano da F. Costa, "Network Structure Revealed by Short Cycles", cond-mat/0612502★Brian Ball, Brian Karrer, M. E. J. Newman, "An efficient and principled method for detecting communities in networks", arxiv:1104.3590★Michael J. Barber, John W. Clark, "Detecting network communities by propagating labels under constraints", Physical Review E 80 (2009): 026129,arxiv:0903.3138★Jonathan W. Berry, Bruce Hendrickson, Randall A. LaViolette, Cynthia A. Phillips, "Tolerating the Community Detection Resolution Limit with Edge Weighting", arxiv:0903.1072 [I have to say that their abstract sounds like a recipe for over-fitting, but I haven't read the paper so that could be totally unfair.]★S. Boccaletti, M. Ivanchenko, V. Latora, A. Pluchino and A. Rapisarda, "Dynamical clustering methods to find community structures", physics/0607179★Michael James Bommarito II, Daniel Martin Katz, Jon Zelner, "On the Stability of Community Detection Algorithms on Longitudinal Citation Data",arxiv:0908.0449★U. Brandes, D. Delling, M. Gaertler, R. Goerke, M. Hoefer, Z. Nikoloski, and D. Wagner, "Maximizing Modularity is hard", physics/0608255 [i.e., maximizing Newman's Q is NP hard. I haven't read beyond the abstract yet, so I don't know if they address the question of what makes it hard in the hard cases, and whether those are properties we should expect to see in real-world networks. Conceivably, actual social networks are, on average, easy to modularize...]★Andrea Capocci, Vito D. P. Servedio, Guido Caldarelli, Francesca Colaiori, "Detecting communities in large networks", cond-mat/0402499★Horacio Castellini and Lilia Romanelli, "Social network from communities of electronic mail", nlin.CD/0509021★Sanjeev Chauhan, Michelle Girvan and Edward Ott, "", Physical Review E 80(2009): 056114★David S. Choi, Patrick J. Wolfe, Edoardo M. Airoldi, "Stochastic blockmodels with growing number of classes", arxiv:1011.4644★Leon Danon, Albert Díaz-Guilera, and Alex Arenas, "The effect of size heterogeneity on community identification in complex networks", Journal of Statistical Mechanics: Theory and Experiment (2006): P11010 =physics/0601144★Leon Danon, Albert Díaz-Guilera, Jordi Duch and Alex Arenas, "Comparing community structure identification", Journal of Statistical Mechanics: Theory and Experiment (2005): P09008 = cond-mat/0505245★Bhaskar DasGupta, Devendra Desai, "On the Complexity of Newman's Community Finding Approach for Biological and Social Networks",arxiv:1102.0969★Jordi Duch and Alex Arenas, "Community detection in complex networks using extremal optimization", Physical Review E 72 (2005): 027104★Lilia Efimova and Stephanie Hendrick, "In search for a virtual settlement: An exploration of weblog community boundaries" [PDF reprint]★Illes J. Farkas, Daniel Abel, Gergely Palla, Tamas Vicsek, "Weighted network modules", cond-mat/0703706★S. Feldt, J. Waddell, V. L. Hetrick, J. D. Berke, and M. Zochowski, "Functional clustering algorithm for the analysis of dynamic network data",Physical Review E 79 (2009): 056104★Daniel J. Fenn, Mason A. Porter, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisis",arxiv:0811.3988★Daniel J. Fenn, Mason A. Porter, Peter J. Mucha, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamical Clustering of Exchange Rates", arxiv:0905.4912★Sam Field, Kenneth A. Frank, Kathryn Schiller, Catherine Riegle-Crumb and Chandra Muller, "Identifying positions from affiliation networks: Preserving the duality of people and events", Social Networks 28 (2006): 97--123★G. W. Flake, S. R. Lawrence, C. L. Giles and F. M. Coetzee, "Self-organization and identification of Web communities", IEEE Computer 36(2002): 66--71★Santo Fortunato, "Community detection in graphs", arxiv:0906.0612★Santo Fortunato and Marc Bathélemy, "Resolution limit in community detection", physics/0607100 = cite>Proceedings of the National Academy of Sciences (USA) 104 (2007): 36--41


http://dx.doi.org/10.1038/nature09182


http://arxiv.org/abs/0903.3178


http://www.iq.harvard.edu/blog/netgov/2010/06/pervasive_overlap.html




http://arxiv.org/abs/physics/0703087


http://arxiv.org/abs/cond-mat/0610182






























http://arxiv.org/abs/nlin.CD/0509021


http://dx.doi.org/10.1103/PhysRevE.80.056114




http://dx.doi.org/10.1088/1742-5468/2006/11/P11010

http://dx.doi.org/10.1088/1742-5468/2006/11/P11010

http://dx.doi.org/10.1088/1742-5468/2006/11/P11010

http://dx.doi.org/10.1088/1742-5468/2006/11/P11010



http://dx.doi.org/10.1088/1742-5468/2005/09/P09008

http://dx.doi.org/10.1088/1742-5468/2005/09/P09008

http://dx.doi.org/10.1088/1742-5468/2005/09/P09008

http://dx.doi.org/10.1088/1742-5468/2005/09/P09008







https://doc.novay.nl/dsweb/Get/Document-46041/weblog-community-boundaries.pdf










http://dx.doi.org/10.1016/j.socnet.2005.04.005






http://dx.doi.org/10.1073/pnas.0605965104




And only you came up with this?★Yong-Yeol Ahn, James P. Bagrow and Sune Lehmann, "Link communities reveal multiscale complexity in networks", Nature 455 (2010): 761--764,arxiv:0903.3178 [Lehmann's blog-post on this]★Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg and Eric P. Xing, "Mixed membership stochastic blockmodels", arxiv:0705.4485★Nelson Augusto Alves, "Unveiling community structures in weighted networks", physics/0703087★Leonardo Angelini, Stefano Boccaletti, Daniele Marinazzo, Mario Pellicoro, and Sebastiano Stramaglia, "Fast identification of network modules by optimization of ratio association", cond-mat/0610182★L. Angelini, D. Marinazzo, M. Pellicoro and S. Stramaglia, "Natural clustering: the modularity approach", cond-mat/0607643★Alex Arenas, Javier Borge-Holthoefer, Sergio Gomez, Gorka Zamora-Lopez, "Optimal map of the modular structure of complex networks", New Journal of Physics 12 (2010): 053009, arxiv:0911.2651★A. Arenas, J. Duch, A. Fernandez, S. Gomez, "Size reduction of complex networks preserving modularity", physics/0702015 [Do you really need all those links? Wouldn't your life be simpler if you could just ignore some of them?]★Alex Arenas, Alberto Fernandez, Sergio Gomez, "Multiple resolution of the modular structure of complex networks", physics/0703218★Alex Arenas, Alberto Fernandez, Santo Fortunato, Sergio Gomez, "Motif-based communities in complex networks", arxiv:0710.0059★Jim Bagrow and Erik Bollt, "A Local Method for Detecting Communities",cond-mat/0412482★James Bagrow, Erik Bollt, Luciano da F. Costa, "Network Structure Revealed by Short Cycles", cond-mat/0612502★Brian Ball, Brian Karrer, M. E. J. Newman, "An efficient and principled method for detecting communities in networks", arxiv:1104.3590★Michael J. Barber, John W. Clark, "Detecting network communities by propagating labels under constraints", Physical Review E 80 (2009): 026129,arxiv:0903.3138★Jonathan W. Berry, Bruce Hendrickson, Randall A. LaViolette, Cynthia A. Phillips, "Tolerating the Community Detection Resolution Limit with Edge Weighting", arxiv:0903.1072 [I have to say that their abstract sounds like a recipe for over-fitting, but I haven't read the paper so that could be totally unfair.]★S. Boccaletti, M. Ivanchenko, V. Latora, A. Pluchino and A. Rapisarda, "Dynamical clustering methods to find community structures", physics/0607179★Michael James Bommarito II, Daniel Martin Katz, Jon Zelner, "On the Stability of Community Detection Algorithms on Longitudinal Citation Data",arxiv:0908.0449★U. Brandes, D. Delling, M. Gaertler, R. Goerke, M. Hoefer, Z. Nikoloski, and D. Wagner, "Maximizing Modularity is hard", physics/0608255 [i.e., maximizing Newman's Q is NP hard. I haven't read beyond the abstract yet, so I don't know if they address the question of what makes it hard in the hard cases, and whether those are properties we should expect to see in real-world networks. Conceivably, actual social networks are, on average, easy to modularize...]★Andrea Capocci, Vito D. P. Servedio, Guido Caldarelli, Francesca Colaiori, "Detecting communities in large networks", cond-mat/0402499★Horacio Castellini and Lilia Romanelli, "Social network from communities of electronic mail", nlin.CD/0509021★Sanjeev Chauhan, Michelle Girvan and Edward Ott, "", Physical Review E 80(2009): 056114★David S. Choi, Patrick J. Wolfe, Edoardo M. Airoldi, "Stochastic blockmodels with growing number of classes", arxiv:1011.4644★Leon Danon, Albert Díaz-Guilera, and Alex Arenas, "The effect of size heterogeneity on community identification in complex networks", Journal of Statistical Mechanics: Theory and Experiment (2006): P11010 =physics/0601144★Leon Danon, Albert Díaz-Guilera, Jordi Duch and Alex Arenas, "Comparing community structure identification", Journal of Statistical Mechanics: Theory and Experiment (2005): P09008 = cond-mat/0505245★Bhaskar DasGupta, Devendra Desai, "On the Complexity of Newman's Community Finding Approach for Biological and Social Networks",arxiv:1102.0969★Jordi Duch and Alex Arenas, "Community detection in complex networks using extremal optimization", Physical Review E 72 (2005): 027104★Lilia Efimova and Stephanie Hendrick, "In search for a virtual settlement: An exploration of weblog community boundaries" [PDF reprint]★Illes J. Farkas, Daniel Abel, Gergely Palla, Tamas Vicsek, "Weighted network modules", cond-mat/0703706★S. Feldt, J. Waddell, V. L. Hetrick, J. D. Berke, and M. Zochowski, "Functional clustering algorithm for the analysis of dynamic network data",Physical Review E 79 (2009): 056104★Daniel J. Fenn, Mason A. Porter, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisis",arxiv:0811.3988★Daniel J. Fenn, Mason A. Porter, Peter J. Mucha, Mark McDonald, Stacy Williams, Neil F. Johnson, Nick S. Jones, "Dynamical Clustering of Exchange Rates", arxiv:0905.4912★Sam Field, Kenneth A. Frank, Kathryn Schiller, Catherine Riegle-Crumb and Chandra Muller, "Identifying positions from affiliation networks: Preserving the duality of people and events", Social Networks 28 (2006): 97--123★G. W. Flake, S. R. Lawrence, C. L. Giles and F. M. Coetzee, "Self-organization and identification of Web communities", IEEE Computer 36(2002): 66--71★Santo Fortunato, "Community detection in graphs", arxiv:0906.0612★Santo Fortunato and Marc Bathélemy, "Resolution limit in community detection", physics/0607100 = cite>Proceedings of the National Academy of Sciences (USA) 104 (2007): 36--41

135 algorithms in U. Michigan index



































http://dx.doi.org/10.1088/1742-5468/2006/11/P11010

http://dx.doi.org/10.1088/1742-5468/2006/11/P11010

http://dx.doi.org/10.1088/1742-5468/2006/11/P11010

http://dx.doi.org/10.1088/1742-5468/2006/11/P11010



http://dx.doi.org/10.1088/1742-5468/2005/09/P09008

http://dx.doi.org/10.1088/1742-5468/2005/09/P09008

http://dx.doi.org/10.1088/1742-5468/2005/09/P09008

http://dx.doi.org/10.1088/1742-5468/2005/09/P09008




























What makes you different?



Computing reduced to commercial limits



Allows overlapping(1 person may be in 2 groups)




Allows overlapping(1 person may be in 2 groups)

User interfaceto help



Who are you?

@findyourcircles

Carlos HerreraAge 25

Work Experience• Current - PhD Candidate (@ UPM) (1st year)

• Research field: complex networks• Published paper

• June 2011 - 1st IEEE Network Science Workshop, West Point NY: "Generating scale-free networks with adjustable clustering coefficient via random walks," doi: 10.1109/NSW.2011.6004642

• 2008-09 International Board Member ( Treasurer & Industry relations) of Electrical Engineering European Student Association (EESTEC).

Education• 2010 - MoS in Electrical Engineering ( Telecommunications) @ Universidad Politécnica de Madrid• 2011 - Master in Statical-Computational Information Treatment @ Complutense U. of Madrid • Accepted for a research stay @ MIT with professor M. Gonzalez

Awards • Scholarships for Academic Excellence years 2004 and 2005 provided by Madrid Region

Government. (700 scholarship among 200K eligible candidates)


Who are you?

@findyourcircles

Alberto AsueroAge 25

Work Experience• Software Engineer @Geographica Spatial

• Lead software analyst since May 2011• GIS Software develpment• Mobile and web software developement

• System administrator @ CMU San Juan• Computer networks (LARTC, Load Balancing)• Virtualization (Xen)• IT Services management FTP, NFS, LVM, PAM-SQL

Education• MoS in Computer Science,

• Universidad Autonóma de Madrd & University of Applied Sciences of Western Switzerland (HEIG-VD)

Technical Skills


How does it looks like?

@findyourcircles


Text

You can try a proof of concept in findyourcircles.com


FYC proof of concept only evaluates friendship links, but could be applied to any social graph which can be defined among users (tagged pictures, events

attended...)

IDEA DEVELOPMENT


Date post:	29-Aug-2014
Category:	Technology
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Find Your Circles presentation

Technology