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Progress in New Computer Science Research Directions

Progress in New Computer Science Research Directions. John Hopcroft Cornell University Ithaca, New York. Time of change. The information age is undergoing a fundamental revolution that is changing all aspects of our lives.

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Progress in New Computer Science Research Directions

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  1. Progress in New Computer Science Research Directions John Hopcroft Cornell University Ithaca, New York CAS May 21, 2010

  2. Time of change • The information age is undergoing a fundamental revolution that is changing all aspects of our lives. • Those individuals and nations who recognize this change and position themselves for the future will benefit enormously. CAS May 21, 2010

  3. Drivers of change • Merging of computing and communications • Data available in digital form • Networked devices and sensors • Computers becoming ubiquitous CAS May 21, 2010

  4. Internet search engines are changing • When was Einstein born? Einstein was born at Ulm, in Wurttemberg, Germany, on March 14, 1879. List of relevant web pages CAS May 21, 2010

  5. CAS May 21, 2010

  6. Internet queries will be different • Which car should I buy? • What are the key papers in Theoretical Computer Science? • Construct an annotated bibliography on graph theory. • Where should I go to college? • How did the field of CS develop? CAS May 21, 2010

  7. Which car should I buy? • Search engine response: Which criteria below are important to you? • Fuel economy • Crash safety • Reliability • Performance • Etc. CAS May 21, 2010

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  10. 2010 Toyota Camry - Auto Shows Toyota sneaks the new Camry into the Detroit Auto Show. Usually, redesigns and facelifts of cars as significant as the hot-selling Toyota Camry are accompanied by a commensurate amount of fanfare. So we were surprised when, right about the time that we were walking by the Toyota booth, a chirp of our Blackberries brought us the press release announcing that the facelifted 2010 Toyota Camry and Camry Hybrid mid-sized sedans were appearing at the 2009 NAIAS in Detroit. We’d have hardly noticed if they hadn’t told us—the headlamps are slightly larger, the grilles on the gas and hybrid models go their own way, and taillamps become primarily LED. Wheels are also new, but overall, the resemblance to the Corolla is downright uncanny. Let’s hear it for brand consistency! Four-cylinder Camrys get Toyota’s new 2.5-liter four-cylinder with a boost in horsepower to 169 for LE and XLE grades, 179 for the Camry SE, all of which are available with six-speed manual or automatic transmissions. Camry V-6 and Hybrid models are relatively unchanged under the skin. Inside, changes are likewise minimal: the options list has been shaken up a bit, but the only visible change on any Camry model is the Hybrid’s new gauge cluster and softer seat fabrics. Pricing will be announced closer to the time it goes on sale this March. • Toyota Camry • › Overview • › Specifications • › Price with Options • › Get a Free Quote • News & Reviews • 2010 Toyota Camry - Auto Shows • Top Competitors • Chevrolet Malibu • Ford Fusion • Honda Accord sedan CAS May 21, 2010

  11. Which are the key papers in Theoretical Computer Science? • Hartmanis and Stearns, “On the computational complexity of algorithms” • Blum, “A machine-independent theory of the complexity of recursive functions” • Cook, “The complexity of theorem proving procedures” • Karp, “Reducibility among combinatorial problems” • Garey and Johnson, “Computers and Intractability: A Guide to the Theory of NP-Completeness” • Yao, “Theory and Applications of Trapdoor Functions” • Shafi Goldwasser, Silvio Micali, Charles Rackoff , “The Knowledge Complexity of Interactive Proof Systems” • Sanjeev Arora, Carsten Lund, Rajeev Motwani, Madhu Sudan, and Mario Szegedy, “Proof Verification and the Hardness of Approximation Problems” CAS May 21, 2010

  12. CAS May 21, 2010

  13. Fed Ex package tracking CAS May 21, 2010

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  19. (Full Zoom Out) Animate Map Storm Tracks Total Precipitation Show Severe Regional Radar Zoom Map Click: Zoom In Zoom Out Pan Map NEXRAD Radar Binghamton, Base Reflectivity 0.50 Degree Elevation Range 124 NMI — Map of All US Radar Sites CAS May 21, 2010

  20. Collective Inference on Markov Models for Modeling Bird Migration Space time CAS May 21, 2010

  21. Daniel Sheldon, M. A. Saleh Elmohamed, Dexter Kozen CAS May 21, 2010

  22. Science base to support activities • Track flow of ideas in scientific literature • Track evolution of communities in social networks • Extract information from unstructured data sources. CAS May 21, 2010

  23. Tracking the flow of ideas in scientific literature Yookyung Jo CAS May 21, 2010

  24. Web Chord Usage Index Probabilistic Text File Retrieve Text Index Page rank Web Link Graph Web Page Search Rank Discourse Word Centering Anaphora Retrieval Query Search Text Tracking the flow of ideas in the scientific literature Yookyung Jo CAS May 21, 2010

  25. Original papers CAS May 21, 2010

  26. Original papers cleaned up CAS May 21, 2010

  27. Referenced papers CAS May 21, 2010

  28. Referenced papers cleaned up. Three distinct categories of papers CAS May 21, 2010

  29. CAS May 21, 2010

  30. Tracking communities in social networks Liaoruo Wang CAS May 21, 2010

  31. “Statistical Properties of Community Structure in Large Social and Information Networks”, Jure Leskovec; Kevin Lang; Anirban Dasgupta; Michael Mahoney • Studied over 70 large sparse real-world networks. • Best communities are of approximate size 100 to 150. CAS May 21, 2010

  32. Our most striking finding is that in nearly every network dataset we examined, we observe tight but almost trivial communities at very small scales, and at larger size scales, the best possible communities gradually "blend in" with the rest of the network and thus become less "community-like." CAS May 21, 2010

  33. Conductance 100 Size of community CAS May 21, 2010

  34. Giant component CAS May 21, 2010

  35. Whisker: A component with v vertices connected by edges CAS May 21, 2010

  36. Our view of a community Colleagues at Cornell Classmates TCS Me More connections outside than inside Family and friends CAS May 21, 2010

  37. Core Should we remove all whiskers and search for communities in the core? CAS May 21, 2010

  38. Should we remove whiskers? • Does there exist a core in social networks? Yes • Experimentally it appears at p=1/n in G(n,p) model • Is the core unique? Yes and No • In G(n,p) model should we require that a whisker have only a finite number of edges connecting it to the core? Laura Wang CAS May 21, 2010

  39. Algorithms • How do you find the core? • Are there communities in the core of social networks? CAS May 21, 2010

  40. How do we find whiskers? • NP-complete if graph has a whisker • There exists graphs with whiskers for which neither the union of two whiskers nor the intersection of two whiskers is a whisker CAS May 21, 2010

  41. Graph with no unique core 3 1 1 CAS May 21, 2010

  42. Graph with no unique core 1 CAS May 21, 2010

  43. What is a community? • How do you find them? CAS May 21, 2010

  44. Communities • Conductance • Can we compress graph? • Rosvall and Bergstrom, “An informatio-theoretic framework for resolving community structure in complex networks” • Hypothesis testing • Yookyung Jo CAS May 21, 2010

  45. Description of graph with community structure • Specify which vertices are in which communities. • Specify the number of edges between each pair of communities. CAS May 21, 2010

  46. Information necessary to specify graph given community structure • m=number of communities • ni=number of vertices in ith community • lij number of edges between ith and jth communities CAS May 21, 2010

  47. Description of graph consists of description of community structure plus specification of graph given structure. • Specify community for each edge and the number of edges between each community • Can this method be used to specify more complex community structure where communities overlap? CAS May 21, 2010

  48. Hypothesis testing • Null hypothesis: All edges generated with some probability p0 • Hypothesis: Edges in communities generated with probability p1, other edges with probability p0. CAS May 21, 2010

  49. Clustering Social networksMishra, Schreiber, Stanton, and Tarjan • Each member of community is connected to a beta fraction of community • No member outside the community is connected to more than an alpha fraction of the community • Some connectivity constraint CAS May 21, 2010

  50. In sparse graphs • How do you find alpha – beta communities? • What if each person in the community is connected to more members outside the community then inside? CAS May 21, 2010

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