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mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} </style> <![endif]--><![if mso 9]> <style> p.MsoNormal {margin-left:4.5pt;} </style> <![endif]><!--[if gte mso 9]><xml> <o:shapedefaults v:ext="edit" spidmax="3074"/> </xml><![endif]--><!--[if gte mso 9]><xml> <o:shapelayout v:ext="edit"> <o:idmap v:ext="edit" data="1"/> </o:shapelayout></xml><![endif]--> </head> <body bgcolor=white lang=EN-US link=blue vlink=purple style='tab-interval:.5in; margin-left:4.5pt;margin-top:4.5pt;margin-right:4.5pt;margin-bottom:4.5pt' revision="dpjtrw3_502dqs7h7c4:140"> <div class=Section1> <p class=MsoNormal align=center style='margin:0in;margin-bottom:.0001pt; text-align:center'><span style='font-size:18.0pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Large graph mining: patterns, tools and case studies</span><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'><o:p></o:p></span></p> <h1 align=center style='text-align:center' id="d_7r0"><span style='font-size: 12.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'>Tutorial proposal for CIKM 2008, Napa Valley, California</span><span style='font-family: "Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'> <o:p></o:p></span></h1> <p class=MsoNormal align=center style='margin:0in;margin-bottom:.0001pt; text-align:center'><i id=temc0><span style='font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'><a href="http://www.cs.cmu.edu/~christos" title="Christos Faloutsos" id=bp35>Christos Faloutsos</a> and <a href="http://www.cs.cmu.edu/~htong" title="Hanghang Tong" id=sga->Hanghang Tong</a>,<br id=p50e2> <a href="http://www.cs.cmu.edu/" title="Carnegie Mellon Univeristy" id=gm7j>Carnegie Mellon University</a> </span></i><span style='font-size:10.0pt;font-family: "Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'><o:p></o:p></span></p> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'><br id=x2b30> <br style='mso-special-character:line-break' id=iffo0> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <h1><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Abstract</span><span style='font-family:"Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'><o:p></o:p></span></h1> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>How do graphs look like? How do they evolve over time? How can we find patterns, anomalies and regularities in them? How to find influential nodes in the network? We will present both theoretical results and algorithms as well as case studies on several real applications. Our emphasis is on the intuition behind each method, and on guidelines for the practitioner.<br id=fu-10> <br id=qkui0> The tutorial has the following parts: <b id=qkui1>(a)</b> Statistical properties and models and graph generators of static and evolving networks. <b id=qkui2>(b)</b> Tools for the analysis of static and dynamic graphs, like the Singular Value Decomposition, tensor decomposition for community detection, HITS/PageRank etc. <b id=xsxu0>(c) </b>Proximity measurements on graphs, the main ideas to quantify the closeness of two nodes of the graph, fast algorithms to compute the proximity scores, applications of proximity, like CenterPiece subgraphs, pattern match, trend analysis etc. <b id=qkui4>(d)</b> Case studies of how a virus or information or influence spreads through the network, how to&nbsp; find influential bloggers or nodes to target for viral marketing, how to find fraudsters on eBay, how to find communities on graphs.<br id=onfl0> <br id=onfl1> <b id=nszl0>Keywords</b>: Graph mining, linear algebra, SVD, tensors, pageRank<br style='mso-special-character:line-break' id=hu.-0> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <h1><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Foils</span><span style='font-family: "Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'><o:p></o:p></span></h1> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman";color:#C00000'>[<a href="part1_patterns.pdf"><span style='color:#C00000'>Part 1</span></a> | <a href="part2_matrix_tensor.pdf"><span style='color:#C00000'>Part 2</span></a> | <a href="part3_proximity.pdf"><span style='color:#C00000'>Part 3</span></a> | <a href="part4_case_studies.pdf"><span style='color:#C00000'>Part 4</span></a>]<o:p></o:p></span></p> <h1><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Aims and Learning Objectives</span><span style='font-family:"Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'> <o:p></o:p></span></h1> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>The goal of the tutorial is to cover the most powerful tools for the analysis of large, real graphs. The tutorial starts old and new patterns that most real graphs obey (small diameter, power laws etc). It continues with powerful, traditional tools from linear algebra (singular value decomposition SVD, eigenvalue analysis); it shows that they form the basis for the extremely successful PageRank and HITS algorithms; and it concludes with more advanced tools, namely, sparse low rank approximations ('CUR' and derivatives).<br id=ya0u0> The next part focuses on proximity of two nodes on a graph, and how to assess it. We describe several measures (electric current, maximum flow, escape probability), we compare them and we focus on the most successful ones and on fast algorithms to compute them.<br id="o5m_0"> The tutorial concludes with several case studies: influence propagation, fraud detection on e-bay, a survey of algorithms for community detection and graph partitioning, and a description of the map/reduce method for the analysis of Tera- and Peta-byte scale graphs.<br id=gbxz0> <br style='mso-special-character:line-break' id=ggcf0> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <h3><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Outline - Description of topics</span><span style='font-family:"Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'> <o:p></o:p></span></h3> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>The proposed format is 1 day (6 hours).<br id=zolf0> <br style='mso-special-character:line-break' id=zolf1> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <p style='margin-left:.5in;text-indent:-.25in;mso-list:l3 level1 lfo2; tab-stops:list .5in' id=pjss3><![if !supportLists]><span style='font-size:10.0pt; font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:Symbol'><span style='mso-list:Ignore'><span style='font:7.0pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; </span></span></span><![endif]><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>Part I: Patterns [1h - Faloutsos]<o:p></o:p></span></p> <ul style='margin-top:0in' type=disc id=dl2s0> <ul style='margin-top:0in' type=circle> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu4><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>patterns on static graphs <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu5><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>patterns on time-evolving graphs <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu6><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>patterns on weighted graphs<o:p></o:p></span></li> </ul> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level1 lfo2;tab-stops:list .5in' id=pjss4><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Part II: Power Tools [2h - Faloutsos]<o:p></o:p></span></li> <ul style='margin-top:0in' type=circle> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=pjss6><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>SVD/PCA <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu7><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>HITS, PageRank <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu8><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>example-based decomposition: CUR, CMD and Colibri <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu9><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>tensors - concepts and applications<o:p></o:p></span></li> </ul> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level1 lfo2;tab-stops:list .5in' id=xsxu10><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Part III: Proximity [1.5h - Tong]<o:p></o:p></span></li> <ul style='margin-top:0in' type=circle> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu11><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>main ideas, properties &amp; generalizations (random walks, escape probabilities, etc) <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu12><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>fast algorithms <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu13><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>applications: (center-piece subgraphs, pattern match etc) <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu14><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>demos<o:p></o:p></span></li> </ul> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level1 lfo2;tab-stops:list .5in' id=xsxu15><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Part IV: Case Studies [1.5 hour - Faloutsos]<o:p></o:p></span></li> <ul style='margin-top:0in' type=circle> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu16><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>virus/influence propagation <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu17><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>blog analysis <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu18><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>eBay fraud detection <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu19><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>community detection and tracking (co-clustering,&nbsp; cross-associations, graphScope etc) <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu20><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>tensor for web mining: TOPHITS <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level2 lfo2;tab-stops:list 1.0in' id=xsxu21><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>scalability: map/reduce and graph mining <o:p></o:p></span></li> </ul> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l3 level1 lfo2;tab-stops:list .5in' id=xsxu22><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Conclusions<o:p></o:p></span></li> </ul> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'><br style='mso-special-character:line-break' id=x2b31> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <h3><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Target Audience</span><span style='font-family:"Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'><o:p></o:p></span></h3> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>The target audience is data management, data mining and machine learning researchers and professionals who work on static or time-evolving graphs and want to know about tools and models when dealing with large network datasets.<br id=xhb51> <b id="n_m11">Prerequisites:</b></span><b><span style='font-size:13.5pt; font-family:"Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'> </span></b><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Computer science background (B.Sc. or equivalent); familiarity with undergraduate linear algebra (eigenvectors). The tutorial will focus on intuition and examples, carefully introducing only the minimal necessary mathematical tools, and always focusing on practical applications.<br id="r_bx1"> <br id=pkhq2> <br id=pkhq3> </span><b id=k4lx0><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Tutorial History<br id=k4lx1> <br id=k4lx2> </span></b><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>Overlapping tutorials have been presented at:<br style='mso-special-character:line-break' id=gyt80> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <ul style='margin-top:0in' type=disc> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l1 level1 lfo6;tab-stops:list .5in' id=gyt82><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>KDD'04 (Chakrabarti and Faloutsos; ~30% overlap) see <a href="http://www.cs.cmu.edu/~christos/TALKS/KDD04-tut/" title="http://www.cs.cmu.edu/~christos/TALKS/KDD04-tut/," id=ya60>http://www.cs.cmu.edu/~christos/TALKS/KDD04-tut/</a><o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l1 level1 lfo6;tab-stops:list .5in' id=gyt86><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>PKDD'07 and also WWW'08 (Leskovec and Faloutsos; ~50% overlap) <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l1 level1 lfo6;tab-stops:list .5in' id=xsxu28><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>ICWSM'08 (McGlohon and Faloutsos; ~50% overlap) <a href="http://www.cs.cmu.edu/~mmcgloho/pubs/ICWSM2008-tutorial.tar.gz" target="_blank" title="http://www.cs.cmu.edu/~mmcgloho/pubs/ICWSM2008-tutorial.tar.gz" id=o701>www.cs.cmu.edu/~mmcgloho/pubs/ICWSM2008-tutorial.tar.gz</a><o:p></o:p></span></li> </ul> <p id=gv7s0><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>We also plan to submit a&nbsp;short version (3 hours) of this tutorial to ICDE 2009. <o:p></o:p></span></p> <p class=MsoNormal style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'><br style='mso-special-character:line-break' id=pkhq5> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <h3><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"; mso-fareast-font-family:"Times New Roman"'>About the instructors</span><span style='font-family:"Verdana","sans-serif";mso-fareast-font-family:"Times New Roman"'> <o:p></o:p></span></h3> <table class=MsoTableGrid border=1 cellspacing=0 cellpadding=0 style='border-collapse:collapse;border:none;mso-border-alt:solid white .5pt; mso-border-themecolor:background1;mso-yfti-tbllook:1184;mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-border-insideh:.5pt solid white;mso-border-insideh-themecolor:background1; mso-border-insidev:.5pt solid white;mso-border-insidev-themecolor:background1'> <tr style='mso-yfti-irow:0;mso-yfti-firstrow:yes'> <td width=137 valign=top style='width:103.1pt;border:solid white 1.0pt; mso-border-themecolor:background1;mso-border-alt:solid white .5pt;mso-border-themecolor: background1;padding:0in 5.4pt 0in 5.4pt'> <p style='margin-right:4.5pt' id=zzlc0><span style='mso-no-proof:yes'><!--[if gte vml 1]><v:shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"> <v:stroke joinstyle="miter"/> <v:formulas> <v:f eqn="if lineDrawn pixelLineWidth 0"/> <v:f eqn="sum @0 1 0"/> <v:f eqn="sum 0 0 @1"/> <v:f eqn="prod @2 1 2"/> <v:f eqn="prod @3 21600 pixelWidth"/> <v:f eqn="prod @3 21600 pixelHeight"/> <v:f eqn="sum @0 0 1"/> <v:f eqn="prod @6 1 2"/> <v:f eqn="prod @7 21600 pixelWidth"/> <v:f eqn="sum @8 21600 0"/> <v:f eqn="prod @7 21600 pixelHeight"/> <v:f eqn="sum @10 21600 0"/> </v:formulas> <v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"/> <o:lock v:ext="edit" aspectratio="t"/> </v:shapetype><v:shape id="Picture_x0020_1" o:spid="_x0000_i1026" type="#_x0000_t75" alt="christos photo" style='width:87.75pt;height:100.5pt;visibility:visible; mso-wrap-style:square'> <v:imagedata src="cikm_tutorial_files/image001.jpg" o:title="christos photo"/> </v:shape><![endif]--><![if !vml]><img border=0 width=117 height=134 src="cikm_tutorial_files/image004.jpg" alt="christos photo" v:shapes="Picture_x0020_1"><![endif]></span><b><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'><o:p></o:p></span></b></p> </td> <td width=660 valign=top style='width:495.0pt;border:solid white 1.0pt; mso-border-themecolor:background1;border-left:none;mso-border-left-alt:solid white .5pt; mso-border-left-themecolor:background1;mso-border-alt:solid white .5pt; mso-border-themecolor:background1;padding:0in 5.4pt 0in 5.4pt'> <p style='margin-right:4.5pt;text-align:justify'><b><span style='font-size: 10.0pt;font-family:"Verdana","sans-serif"'>Christos Faloutsos</span></b><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'> is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), the Research Contributions Award in ICDM 2006, twelve ``best paper'' awards, and several teaching awards. He has served as a member of the executive committee of SIGKDD; he has published over 160 refereed articles, 11 book chapters and one monograph. He holds five patents and he has given over 20 tutorials and 10 invited distinguished lectures. His research interests include data mining for streams and graphs, fractals, database performance, and indexing for multimedia and bio-informatics data. <o:p></o:p></span></p> <p style='margin-right:4.5pt'><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>(Full CV at <a href="http://www.cs.cmu.edu/~christos/webvitae.pdf" target="_blank" title="www.cs.cmu.edu/~christos/webvitae.pdf" id=cgns>www.cs.cmu.edu/~christos/webvitae.pdf</a> )<o:p></o:p></span></p> <p style='margin-right:4.5pt'><b><span style='font-size:10.0pt;font-family: "Verdana","sans-serif"'><o:p>&nbsp;</o:p></span></b></p> </td> </tr> <tr style='mso-yfti-irow:1;mso-yfti-lastrow:yes'> <td width=137 valign=top style='width:103.1pt;border:solid white 1.0pt; mso-border-themecolor:background1;border-top:none;mso-border-top-alt:solid white .5pt; mso-border-top-themecolor:background1;mso-border-alt:solid white .5pt; mso-border-themecolor:background1;padding:0in 5.4pt 0in 5.4pt'> <p style='margin-right:4.5pt'><span style='font-size:9.0pt;font-family:"Times","serif"; mso-no-proof:yes'><!--[if gte vml 1]><v:shape id="Picture_x0020_4" o:spid="_x0000_i1025" type="#_x0000_t75" alt="http://www.cs.cmu.edu/~htong/htong.jpg" style='width:85.5pt; height:100.5pt;visibility:visible;mso-wrap-style:square'> <v:imagedata src="cikm_tutorial_files/image002.jpg" o:title="htong" cropright="3932f"/> </v:shape><![endif]--><![if !vml]><img border=0 width=114 height=134 src="cikm_tutorial_files/image005.jpg" alt="http://www.cs.cmu.edu/~htong/htong.jpg" v:shapes="Picture_x0020_4"><![endif]></span><b><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'><o:p></o:p></span></b></p> </td> <td width=660 valign=top style='width:495.0pt;border-top:none;border-left: none;border-bottom:solid white 1.0pt;mso-border-bottom-themecolor:background1; border-right:solid white 1.0pt;mso-border-right-themecolor:background1; mso-border-top-alt:solid white .5pt;mso-border-top-themecolor:background1; mso-border-left-alt:solid white .5pt;mso-border-left-themecolor:background1; mso-border-alt:solid white .5pt;mso-border-themecolor:background1;padding: 0in 5.4pt 0in 5.4pt'> <p style='text-align:justify'><b><span style='font-size:10.0pt;font-family: "Verdana","sans-serif"'>Hanghang Tong</span></b><span style='font-size:10.0pt; font-family:"Verdana","sans-serif"'> is a senior Ph.D. student in the Machine Learning Department at Carnegie Mellon University. He has received best paper awards from&nbsp; SIAM-DM 2008 and ICDM 2006, and he has 25 refereed publications. He holds an M.S. degree and a B.S. degree from Tsinghua University, P.R. China. His research interests include data mining for multimedia and for graphs. (Full CV at&nbsp; <a href="http://www.cs.cmu.edu/~htong/pdf/cv_Tong.pdf" target="_blank" title="http://www.cs.cmu.edu/~htong/pdf/cv_Tong.pdf" id=xb56>www.cs.cmu.edu/~htong/pdf/cv_Tong.pdf</a> )<o:p></o:p></span></p> </td> </tr> </table> <p><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>&nbsp; <o:p></o:p></span></p> <p id=sn5l0><b id=zzlc3><span style='font-size:13.5pt;font-family:"Verdana","sans-serif"'>Related References</span></b><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'> <o:p></o:p></span></p> <p id=w6-x1><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>&nbsp; <o:p></o:p></span></p> <ol style='margin-top:0in' start=1 type=1 id=sn5l3> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l4><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Sergey Brin and Lawrence Page. The Anatomy of a Large-Scale Hypertextual Web Search Engine, Computer Networks 30(1-7): 107-117, 1998. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l5><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Randy Bryant. Data Intensive Scientific Computing, Tech report. available at <a href="http://www.cs.cmu.edu/~bryant/pubdir/cmu-cs-07-128.pdf" id=u-a20>http://www.cs.cmu.edu/~bryant/pubdir/cmu-cs-07-128.pdf</a>. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=u-a21><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Deepayan Chakrabarti, Spiros Papadimitriou, Dharmendra S. Modha, and Christos Faloutsos. Fully Automatic Cross-Associations, KDD 2004, Washington, DC. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l6><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Inderjit S. Dhillon, Subramanyam Mallela, and Dharmendra S. Modha. Information-theoretic co-clustering. KDD 2003, Washington, DC. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l7><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Petros Drineas, Ravi Kannan, and Michael W. Mahoney. Fast monte carlo algorithms for matrices iii: Computing a compressed approximate matrix decomposition, SIAM Journal of Computing, 2005. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l8><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jon Kleinberg. Authoritative sources in a hyperlinked environment, Proc. 9th ACM-SIAM Symposium on Discrete Algorithms, 1998. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l9><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Tamara Kolda, Brett Bader, and Joseph Kenny. Higher-order Web link analysis using multilinear algebra, ICDM 2005, Houston, Texas. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l10><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jure Leskovec, Jon Kleinberg and Christos Faloutsos. Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations, KDD 2005, Chicago, IL. (&quot;Best Research Paper&quot; award). <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l11><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jure Leskovec, Deepayan Chakrabarti, Jon Kleinberg, and Christos Faloutsos. Realistic, Mathematically Tractable Graph Generation and Evolution, Using Kronecker Multiplication, ECML/PKDD 2005, Porto, Portugal. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l12><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jure Leskovec and&nbsp; Christos Faloutsos. Scalable Modeling of Real Graphs using Kronecker Multiplication, ICML 2007, Corvallis, OR, USA <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l13><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jure Leskovec, Mary McGlohon, Christos Faloutsos, Natalie S. Glance, and Matthew Hurst. Patterns of Cascading Behavior in Large Blog Graphs, SDM 2007, Minneapolis, Minnesota. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l14><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Shashank Pandit, Duen Horng (Polo) Chau, Samuel Wang and Christos Faloutsos. NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks WWW 2007, Banff, Alberta, Canada, May 8-12, 2007. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l15><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jimeng Sun, Dacheng Tao, and Christos Faloutsos. Beyond Streams and Graphs: Dynamic Tensor Analysis, KDD 2006, Philadelphia, PA. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l16><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Faloutsos. Less is More: Compact Matrix Decomposition for Large Sparse Graphs, SDM 2007, Minneapolis, Minnesota. (&quot;Best Research Paper&quot; award) <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l17><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Jimeng Sun, Spiros Papadimitriou, Philip S. Yu, and Christos Faloutsos. GraphScope: parameter-free mining of large time-evolving graphs, KDD 2007, San Jose, CA. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l18><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Hanghang Tong, Christos Faloutsos, and Jia-Yu Pan. Fast Random Walk with Restart and Its Applications, ICDM 2006, Hong Kong. (&quot;Best Research Paper&quot; award) <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l19><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Hanghang Tong and Christos Faloutsos. Center-Piece Subgraphs: Problem Definition and Fast Solutions, KDD 2006, Philadelphia, PA. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l20><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Hanghang Tong, Brian Gallagher, Tina Eliassi-Rad, and Christos Faloutsos. Fast best-effort pattern matching in large attributed graphs, KDD 2007, San Jose, CA. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l21><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Hanghang Tong, Yehuda Koren, and Christos Faloutsos. Fast direction-aware proximity for graph mining, KDD 2007, San Jose, CA. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l22><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Hanghang Tong, Spiros Papadimitriou, Philip S. Yu and Christos Faloutsos. Proximity Tracking on Time-Evolving Bipartite Graphs. SDM 2008, Atlanta, GA. (&quot;Best Paper&quot; award) <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l23><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, Philip S. Yu, and Christos Faloutsos. Colibri: Fast Mining of Large Static and Dynamic Graphs, KDD 2008, Las Vegas, NV. <o:p></o:p></span></li> <li class=MsoNormal style='margin-top:0in;margin-bottom:0in;margin-bottom: .0001pt;mso-list:l2 level1 lfo9;tab-stops:list .5in' id=sn5l24><span style='font-size:10.0pt;font-family:"Verdana","sans-serif";mso-fareast-font-family: "Times New Roman"'>Yang Wang, Deepayan Chakrabarti, Chenxi Wang and Christos Faloutsos. Epidemic Spreading in Real Networks: an Eigenvalue Viewpoint, SRDS 2003, Florence, Italy. <o:p></o:p></span></li> </ol> <p id=sn5l25><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>&nbsp; <o:p></o:p></span></p> <p><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>Last Updated: July 27, 2008<o:p></o:p></span></p> <p id=sn5l26><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>&nbsp; <o:p></o:p></span></p> <p id=zzlc4><span style='font-size:10.0pt;font-family:"Verdana","sans-serif"'>&nbsp; <o:p></o:p></span></p> </div> </body> </html>