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<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>This talk is sponsored by the <st1:place w:st="on"><st1:PlaceType
w:st="on">University</st1:PlaceType> of <st1:PlaceName w:st="on">Chicago</st1:PlaceName></st1:place>
and TTI-C. The contact for this event is Steve Smale (834-2510) <a
href="mailto:smale@tti-c.org" title="blocked::mailto:smale@tti-c.org">smale@tti-c.org</a>.
It will be held on Friday, November 9, in 251 Ryerson from 2:30 pm to 3:30 pm.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>The large-scale structure of real-world networks.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>Mark Newman<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>Department of Physics and Center for the Study of Complex
Systems<o:p></o:p></span></font></p>
<p class=MsoNormal><st1:place w:st="on"><st1:PlaceType w:st="on"><font size=2
face=Arial><span style='font-size:10.0pt;font-family:Arial'>University</span></font></st1:PlaceType><font
size=2 face=Arial><span style='font-size:10.0pt;font-family:Arial'> of <st1:PlaceName
w:st="on">Michigan</st1:PlaceName></span></font></st1:place><font size=2
face=Arial><span style='font-size:10.0pt;font-family:Arial'><o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>Many systems take the form of networks: the Internet, the
World Wide Web, social networks, citation networks, metabolic networks, food
webs, and neural networks are just a few examples. In this talk I will
show some recent empirical data for these and other networks and discuss how we
can discover and understand their large-scale structure and its implications.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>The problem is that many networks are too large to visualize
in their entirety, so to understand what they “look lie” we need
algorithmic or statistical techniques to pick useful patterns out of large
network data sets. I will describe recent work on several methods that
attempt to detect structural features such as clustering and hierarchy using
spectral and other techniques. I will give a variety of illustrative applications
throughout the talk.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
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