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====== CSCI5070 Advanced Topics in Social Computing ======
 [ [[:teaching:csci5070:discussions:2012|Discussion Forum]] | [[:teaching:csci5070:blogs:2012|Blogs]] ]
==== Breaking News ====
  * <hi #ffff00>**November 19, 2012**.</hi> Project report template is available below or [[https://www.cse.cuhk.edu.hk/irwin.king/_media/teaching/csci5070/report_template.zip|here]]. Either Microsoft Word format or Latex format is acceptable. Your report should include title, author information, abstract, categories and subject descriptors, general terms, keywords, introduction, conclusion, and references.
  * <hi #ffff00>**November 19, 2012**.</hi> Final Project Presentation Sign-up Sheet.  Please sign up the meeting sheet at the bottom of the page or [[https://www.cse.cuhk.edu.hk/irwin.king/teaching/csci5070/2012#final_project_presentation_sign-up_sheet|here]].  The meeting date is Tuesday, December 4, 2012 from 9:00 am to 1:45 pm.  Please sign up for at least one slot with your full name of all team members.
  * <hi #ffff00>**November 5, 2012**.</hi> The midterm exam will be held on November 13, 2012 from 9:30 am to 11:45 am in NAH 115. The exam will be closed-book, but you are allowed to bring one A4 cheat sheet (You can write or print whatever you think might be useful on both sides).

  * <hi #ffff00>**October 30, 2012**.</hi> Midterm Project Evaluation Meeting Sign-up Sheet.  Please sign up the meeting sheet at the bottom of the page or [[https://www.cse.cuhk.edu.hk/irwin.king/teaching/csci5070/2012#midterm_evaluation_sign-up_sheet|here]].  The meeting date is Thursday, November 8, 2012 from 9:30 am to 3:30 pm.  Please sign up for at least one slot with your full name of all team members.

  * <hi #ffff00>**October 23, 2012**.</hi> Assignment 2 is released. The deadline is November 6 (15:59:59, Hong Kong Time), please submit your answer sheet to the course mailbox on 10th floor of Ho Sin-Hang Engineering Building before the due date.

  * <hi #ffff00>**September 28, 2012**.</hi> Assignment 1 is released. The deadline is October 12 (23:59:59, Hong Kong Time), please submit your answer sheet to the course mailbox on 10th floor of Ho Sin-Hang Engineering Building before the due date.

  * <hi #ffff00>**September 21, 2012**.</hi>  Project specifications and project template doc are available below.  Follow the links to download files.  You should have a group by now.  If you do not have a group by the next tutorial (Tuesday, September 25), we will randomly assign you to a group.  More details will be available at the tutorial.

  * <hi #ffff00>**September 19, 2012**.</hi>  Good news.  We have obtained a larger lecture hall for the class so the quota has been lifted.  Starting from September 25, 2012, CSCI5070 will be located at the **Leung Kau Kui Building** (**KKB101**).  With this new venue, we will also increase the course quota for students.  Please go to the General Office, Dept. of Comptuer Science and Engineering to add the course.

  * <hi #ffff00>**September 12, 2012**.</hi> The tutorial is every T9 in LSK 308.  Please bring your computer so that you can run the package and perform operations in real-time.  The tutorial will begin on September 18.  My office hours are M8 and T8 from 3:30 pm - 4:30 pm.

  * <hi #ffff00>**September 10, 2012**.</hi> The new semester begins.

==== Extra Credit Assignments ====
===== 20012-13 Term 1 =====


|  ^  Lecture I  ^  Lecture II  ^  Tutorial I  ^  Tutorial II  ^
^ Time    |  T2-4, 9:30 am - 12:30 pm  |    |  T9, 4:30 pm - 5:30 pm  |   |
^ Venue    |  NAH 8  |   |   LSK 308   |     |

<html><font color="red"> <b>The Golden Rule of CSCI5070: </b></font></html> No member of the CSCI5070 community shall take unfair advantage of any other member of the CSCI5070 community.

====== Course Description ======

This course introduces fundamental as well as applied computational techniques for collaborative and collective intelligence of group behaviours on the Internet. The course topics include, but are not limited to: web intelligence, web data mining, knowledge discovery on the web, web analytics, web information retrieval, learning to rank, ranking algorithms, relevance feedback, collaborative filtering, recommender systems, human/social computation, social games, opinion mining, sentiment analysis, models and theories about social networks, large graph and link-based algorithms, social marketing, monetization of the web, security/privacy issues related to web intelligence and social computing, etc.

===== Learning Objectives =====

===== Learning Outcomes =====


===== Learning Activities =====
  - Lectures
  - Tutorials
  - Web resources
  - Videos
  - Quizzes
  - Examinations
====== Personnel ======

| ^  Lecturer  ^  Tutor  ^ Tutor ^
^ Name |  [[:home|Irwin King]]  |  Baichuan Li  |   |
^ Email |  king AT cse.cuhk.edu.hk  |  bcli AT cse.cuhk.edu.hk  |    |
^ Office   |  Rm 908  |   |   |
^ Telephone   |   3943 8398   |  | |
^ Office Hour(s)   | * M8, Monday 3:30 pm - 4:30 pm\\ \\ * T8, Tuesday 3:30 pm - 4:30 pm  |  | |

Note: This class will be taught in<html> <font color="red">English</font></html>. Homework assignments and examinations will be conducted in English.

====== Syllabus ======
The pdf files are created in Acrobat 6.0. Please obtain the correct version of the [[http://www.adobe.com/prodindex/acrobat/readstep.html#reader | Acrobat Reader]] from Adobe.

^  Week  ^  Date  ^  Topics  ^  Tutorials  ^  Homework & Events  ^  Resources   ^   
|  1  |  11/9  |  Introduction to Web Intelligence and Social Computing\\ Web 2.0\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-01-Introduction.pdf|01-Introduction.pdf]]  | | |  [[http://www.cse.cuhk.edu.hk/~king/PUB/podcasts/Tim%20O'Reilly%20on%20Web%202.0.mp3|Tim O'Reilly on Web 2.0, The Economist, 20/3/2009]]  |
|  2  |  18/9  |  Graphs\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-02-Graphs.pdf|02-Graphs.pdf]]  |  Python & R\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-01-Tutorial.pdf|CSCI5070-01-Tutorial.pdf]]  |  Project Specs and template\\ \\ 1. [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/csci5070_project_spec_v1.0.pdf|Proposal specs]]\\ 2. [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/csci5070_proposal_template_v1.0.doc|Proposal template]]  |   [[http://www.analytictech.com/networks.pdf|Introduction to Social Networks]]  |
|  3  |  25/9  |  Social Network Theory I\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-02-Graphs-Additions.pdf|02-Graphs Additions.pdf]]\\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-03-Networks.pdf|03-Networks.pdf]]      |  Crawler\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-02-Web-Crawling-Nate-Murray.pdf|02-Crawler.pdf]]    |  [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/csci5070ex1.pdf|Assignment 1]]  |   |
|  4  |  2/10  |  Public Holiday  |  Public Holiday  |    |  [[http://demonstrations.wolfram.com/SamplesOfRandomGraphs/|Generating Random Graphs]]\\  [[http://www.geocities.com/dharwadker/clique/|The Clique Algorithm]]  |
|  5  |  9/10  |  Social Network Theory II\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-04-GraphMining and Link Analysis.pdf|04-GraphMining and Link Analysis.pdf]]\\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-04-Networks.pdf|04-Networks.pdf]]  |  NetworkX and Graphviz [[https://www.cse.cuhk.edu.hk/irwin.king/_media/teaching/csci5070/csci5070-03-networkx_and_graphviz.pdf|03-NetworkX & Graphviz]]  |    |   [[http://nlp.stanford.edu/IR-book/|Introduction to Information Retrieval]]  |
|  6  |  16/10  |  Recommender Systems I\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-05-Recommender System.pdf|05-Recommender 1.pdf]]   |  Link Analysis and Memory-based Collaborative Filtering \\  [[https://www.cse.cuhk.edu.hk/irwin.king/_media/teaching/csci5070/csci5070-04-link_analysis_memory-based_cf.pdf|Link Analysis & Memory-based CF]]  |     | |
|  7  |  23/10  |  Public Holiday  |  Public Holiday  |  [[https://www.cse.cuhk.edu.hk/irwin.king/_media/teaching/csci5070/csci5070as2.pdf|Assignment 2]]  |   |
|  8  |  30/10  |  Recommender Systems I\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-05-Recommender System.pdf|05-Recommender 1.pdf]]  |   [[https://www.cse.cuhk.edu.hk/irwin.king/_media/teaching/csci5070/csci5070-05-as1_solution.pdf|Assignment 1 Solution]]  |    | |
|  9  |  6/11  |  Recommender Systems II\\ \\ [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-06-Recommender System.pdf|06-Recommender 2.pdf]]  |  [[https://www.cse.cuhk.edu.hk/irwin.king/_media/teaching/csci5070/csci5070as2_solution.pdf|Assignment 2 Solution]]  |      | |
|  10  |  13/11  |  Midterm Examination  |  [[http://www.iu.hio.no/~frodes/rm/ppt/latex.ppt|Introduction to Latex]]  | | |
|  11  |  20/11  |  Opinion Mining and CQA\\ \\ 1.  [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-07-CQA.pdf|07-CQA.pdf]] \\ 2.  [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-07-QA & Deep QA.pdf|07-QA & Deep QA.pdf]]  \\ 3.  [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-07-Sentiment Analysis.pdf|07-Sentiment Analysis.pdf]]  |  [[http://web.cs.dal.ca/~yongzhen/publication/paper/ICDM2011_SentimentAnalysisInPracticeTutorial.pdf|Sentiment Analysis in Practice]]  |  [[https://www.cse.cuhk.edu.hk/irwin.king/_media/teaching/csci5070/report_template.zip|Report Template]]\\ \\ Assignment 3  | |
|  12  |  27/11  |  Human Computation & Crowdsourcing  |  Crowdsourcing  | |  |
|  13  |  4/12  |  Wrap Up\\ \\  Project Presentations  |  Assignment 3 Solution  | |  [[http://edutechwiki.unige.ch/en/EduTech_Wiki:Books/Social_computing_in_education|EduTech on Social Computing in Education]]  |

  * Web 2.0
    * Ajax, CSS, 
  * Social Media
    * blogs, microblogs, wikis, mashup, 

====== Class Project ======
===== Class Project Presentation Schedule =====
  * TBA

===== Class Project Presentation Requirements=====
  - For each group, the total time for the presentation is 15 minutes, including 12 minutes for the talk and 3 minutes for Q&A. The presentation will follow the order above. Since this class will last until the end of all the presentations, if the time is not suitable for you, you can tell us to change your order. \\
  - In the presentation, there is no demo part. The demo part is an independent process divided into two sub-sections. The first section will be hold in tutorial time on Dec. 1st. In this section, all the groups should demo your program to the two tutors. The tutors will guide you to revise your program. The second section will be hold on Wednesday, Dec. 16th. In this section, Prof. King will check your program before the final submission of your codes. \\
  - For groups implementing graphical algorithms, you should explain one algorithm as detailed as you can in the presentation. You should give an example with the structure of nodes, values, and your calculations. You also need to analyze the complexity of your algorithms and test whether your algorithms can be applied in large graphs. For other groups, you should focus on three aspects including the motivation of your idea, the detailed algorithms, and the justification of your methods comparing to naive methods through experiments.

====== Examination Matters ======


===== Examination Schedule =====
|              ^        Time           ^        Venue          ^    Notes    ^
^    Midterm Examination\\ Written    |    TBA  |   TBA   |    TBA    |
^    Midterm Examination\\ Programming    |    TBA   |   TBA   |    TBA    |
^    Final Examination    |   TBA | TBA | TBA   |


  * [[http://rgsntl.rgs.cuhk.edu.hk/rws_prd_life/main1.asp|CUHK Registration and Examination]]



===== Written Midterm Matters =====
  - The midterm will test your knowledge of the materials.
  - Answer all questions using the answer booklet.  There will be more available at the venue if needed.
  - Write legibly.  Anything we cannot decipher will be considered incorrect.
  - One A4-sized cheat-sheet page.

====== Grade Assessment Scheme ======
^  Homework\\ Assignments  ^  Project Report  ^  Project Presentation  ^  Final Examination  ^
|  20%  |  20%  |  10%  |  50%  |

  -Assignments (30%) 
    -Written assignments
    -Optional quizzes
  -Midterm Examination (30%) 
  - Project (40%)
    - Report (20%)
    - Presentations (20%)
  -Extra Credit (There is no penalty for not doing the extra credit problems. Extra credit will only help you in borderline cases.)

====== Required Background ======
  - Pre-requisites
    -- CSC 1110 or 1130 or its equivalent. (Not for students who have taken CSC 2520). 
====== Reference Books ======


====== FAQ ======

  - **Q: What is departmental guideline for plagiarism?**\\ A: If a student is found plagiarizing, his/her case will be reported to the Department Discipline Committee. If the case is proven after deliberation, the student will automatically fail the course in which he/she committed plagiarism. The definition of plagiarism includes copying of the whole or parts of written assignments, programming exercises, reports, quiz papers, mid-term examinations. The penalty will apply to both the one who copies the work and the one whose work is being copied, unless the latter can prove his/her work has been copied unwittingly. Furthermore, inclusion of others' works or results without citation in assignments and reports is also regarded as plagiarism with similar penalty to the offender. A student caught plagiarizing during tests or examinations will be reported to the Faculty Office and appropriate disciplinary authorities for further action, in addition to failing the course.

====== Resources ======

  -[[http://pajek.imfm.si/doku.php|Pajek, a network analysis and visualization program.]]
  -[[http://vlado.fmf.uni-lj.si/pub/networks/data/default.htm|Package for Large Network Analysis]]
  -[[http://www.analytictech.com/downloaduc6.htm|UCINET 6]]
  -[[http://www.analytictech.com/Netdraw/netdraw.htm|Netdraw]]
  -[[http://stat.gamma.rug.nl/stocnet/|StOCNET]]

===== Social Networks-Theory Graph Theory =====
  * http://www.cs.purdue.edu/homes/neville/courses/aaai08-tutorial.html \\
  * http://cs.stanford.edu/people/jure/icml09networks/ \\
  * http://www.ofcom.org.uk/advice/media_literacy/medlitpub/medlitpubrss/socialnetworking/report.pdf \\

===== Graph Mining =====
  * http://www.cs.cmu.edu/~deepay/mywww/papers/csur06.pdf \\
  * http://cs.stanford.edu/people/jure/talks/www08tutorial/ \\
  * http://www.xifengyan.net/tutorial/KDD08_graph_partI.pdf \\
  * http://www.xifengyan.net/tutorial/KDD08_graph_partII.pdf

===== Link Analysis===== 
  * http://analytics.ijs.si/events/Tutorial-TextMiningLinkAnalysis-KDD2007-SanJose-Aug2007/ \\
  * http://www.sigkdd.org/explorations/issues/7-2-2005-12/1-Getoor.pdf \\
  * http://www.ncjrs.gov/pdffiles1/nij/grants/219552.pdf \\
  * http://delab.csd.auth.gr/~dimitris/papers/ENVO07LARskm.pdf

===== Learning to Rank===== 
  * http://www2009.org/pdf/T7A-LEARNING%20TO%20RANK%20TUTORIAL.pdf\\
  * http://radlinski.org/papers/LearningToRank_NESCAI08.pdf\\
  * http://www.aclweb.org/anthology/P/P09/P09-5005.pdf\\
  * http://www.cse.iitb.ac.in/~soumen/doc/www2007/TutorialSlides.pdf

===== Recommender Systems===== 
  * http://en.wikipedia.org/wiki/Recommender_system
  * http://www.deitel.com/ResourceCenters/Web20/RecommenderSystems/RecommenderSystemsTutorialsandWebcasts/tabid/1313/Default.aspx
  * http://www.computer.org/portal/web/csdl/doi/10.1109/TKDE.2005.99
  * http://www.springerlink.com/content/n881136032u8k111/
  * http://www.csd.abdn.ac.uk/~jmasthof/Publications/WPRSIUI07.pdf

===== Q & A =====
  * http://lml.bas.bg/ranlp2005/tutorials/magnini.ppt \\
  * http://tcc.itc.it/research/textec/topics/question-answering/Tut-Prager.ppt \\
  * http://en.wikipedia.org/wiki/Question_answering \\
  * http://trec.nist.gov/pubs/trec9/papers/webclopedia.pdf \\
  * http://domino.watson.ibm.com/library/CyberDig.nsf/papers/D12791EAA13BB952852575A1004A055C/$File/rc24789.pdf \\
  * http://www.umiacs.umd.edu/~jimmylin/publications/Lin_Katz_EACL2003_tutorial.pdf \\
  * http://answers.yahoo.com/ \\
  * http://zhidao.baidu.com/ \\
  * http://wenda.tianya.cn/wenda/ \\
  * http://hk.knowledge.yahoo.com/ \\

===== Human Computation/Social Games  =====
  * http://www.gwap.com/gwap/ \\
  * http://www.cs.cmu.edu/~biglou/ \\

===== Opinion Mining/Sentiment Analysis  =====
  * http://www.cs.uic.edu/~liub/FBS/opinion-mining-sentiment-analysis.pdf \\
  * http://www.cs.cornell.edu/home/llee/omsa/omsa-published.pdf \\
  * http://www.cs.cmu.edu/~wcohen/10-802/sentiment-sep-4.ppt \\

===== Visualization =====
  -[[http://manyeyes.alphaworks.ibm.com/manyeyes/|Many Eyes Visualization]]

===== Programming =====
  -[[http://networkx.lanl.gov/|NetworkX, a Python package for complex networks]]
  -[[http://www.wolfram.com/|Mathematica from Wolfram]]
    -[[http://demonstrations.wolfram.com/|Wolfram Demonstrations]]

===== Midterm Evaluation Sign-up Sheet =====
  * The time slots are for Thursday, November 8, 2012.
  * The venue is in HSH Room 1022 (seminar room).
  * Please enter all team members' name in the slot in either the A.M. or the P.M. table.
  * Instructions
    - Put the name of all your team members under the "Real name" column.
    - Select at least one slot from either the A.M. or P.M. table.
    - Press "Submit".
    - Make sure it does not conflict with others.

<doodle Midterm Project Evaluation AM>
^ 9:30 ^ 9:45 ^ 10:00 ^ 10:15 ^ 10:30 ^ 10:45 ^ 11:00 ^ 11:15 ^ 11:30 ^ 11:45 ^
</doodle>

<doodle Midterm Project Evaluation PM>
^ 12:30 ^ 12:45 ^ 1:00 ^ 1:15 ^ 1:30 ^ 1:45 ^ 2:00 ^ 2:15 ^ 2:30 ^ 2:45 ^ 3:00 ^
</doodle>

===== Final Project Presentation Sign-up Sheet =====
  * The time slots are for Tuesday, December 4, 2012.
  * The venue is in KKB 101 (classroom).
  * Please enter all team members' name in the slot in either the Session 1 or the Session 2 table.
  * Instructions
    - Put the name of all your team members under the "Real name" column.
    - Select at least one slot from either the Session 1 or Session 2 table.
    - Press "Submit".
    - Make sure it does not conflict with others.

<doodle Final Project Presentation Session 1>
^ 9:00 ^ 9:15 ^ 9:30 ^ 9:45 ^ 10:00 ^ 10:15 ^ 10:30 ^ 10:45 ^ 11:00 ^ 
</doodle>

<doodle Final Project Presentation Session 2>
^ 11:15 ^ 11:30 ^ 11:45 ^ 12:00 ^ 12:15 ^ 12:30 ^ 12:45 ^ 13:00 ^ 13:15 ^ 13:30 ^ 
</doodle>
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