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WSW FYP 2014

WSW FYP 2014. Wing Shing Wong Room 810 HSH wswong@ie.cuhk.edu.hk. WSW1: Social Network. Aims Discovering interesting patterns in social network Develop a graphic display tool Tasks Learn about how to extract data from social networks Develop a display platfor m

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WSW FYP 2014

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  1. WSW FYP 2014 Wing Shing Wong Room 810 HSH wswong@ie.cuhk.edu.hk

  2. WSW1: Social Network • Aims • Discovering interesting patterns in social network • Develop a graphic display tool • Tasks • Learn about how to extract data from social networks • Develop a display platform • Extract patterns from data obtained

  3. A related version is the following: Two random people may not know each other, but there may be an “acquaintance chain from one to the other? If there is, how short is this chain? In 1967 Stanley Milgram posed the following small world problem: “Starting with any two people in the world, what is the probability that will know each other?”

  4. Milgram’s experiment A target person in Cambridge, MASS was chosen. Random volunteers, starting persons, at a distant city were chosen; Wichita, Kansas in the 1st study, Omaha, Nebraska in the 2nd. Each starting person try to send a letter to the target person, through an acquaintance chain. Acquaintance is defined as a person one knows on a first name basis.

  5. The set-up • Each volunteer was given a folder. • The folder contained: • Name of the target person • Some information of the person (but no address) • Set of rules of forwarding (e.g. first name basis) • Roster of people in the chain

  6. Medium is only 5 From S. Milgram, “The Small-World Problem,” Psychology Today Vol 1(1), 1967

  7. OTHER networking ideas

  8. Bacon number: Kevin Bacon has number 0, people who worked directly with Kevin Bacon has a Bacon number 1, and so on.

  9. Erdös number: People who coauthored with P. Erdös has Erdös number 1, people who coauthored with those who has Erdös number 1 but not with Erdös has Erdös number 2 and so on.

  10. What is the social network version of these ideas? Network of friends in facebook? Co-authors in http://scholar.google.com/? Other social networks?

  11. WSW2 Googled Data Mining There is a wealth of data from a simple google search Example: type the word 來：

  12. When you type 來往, then

  13. If you select 來自星星的你, then you get Note that there are approximately 63,100,000 entries

  14. Some intriguing questions How are they related? The timeline relation Where do they come from? What are their nature, content provider, news, commentary, etc? What happen if we google

  15. WSW3 Video Condensation/Synopsis (Suzhen Wang) Explosive growth of surveillance videos create browsing, retrieval and storage challenges Aim to summarize a day long video to just a few minutes Task to develop new online condensation algorithm

  16. Fromhttp://en.wikipedia.org/wiki/Video_Synopsis References: Y. Pritch, S. Ratovitch, A. Hendel, and S. Peleg, Clustered Synopsis of Surveillance Video, 6th IEEE Int. Conf. on Advanced Video and Signal Based Surveillance (AVSS'09), Genoa, Italy, Sept. 2-4, 2009 Y. Pritch, A. Rav-Acha, and S. Peleg, Nonchronological Video Synopsis and Indexing, IEEE Trans. PAMI, Vol 30, No 11, Nov. 2008, pp. 1971-1984. A. Rav-Acha, Y. Pritch, and S. Peleg, Making a Long Video Short: Dynamic Video Synopsis, CVPR'06, June 2006, pp. 435-441.

  17. Background needed Efficiency in image processing programming, using for example Matlab or Visual Studio. Familiar with linear algebra and convex optimization theory in order to understand methods and algorithms in the related papers.

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