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| - | ====== CSCI5733 Social Computing ====== | ||
| - | [ [[:teaching:csci5733:discussions:2013|Discussion Forum]] | [[:teaching:csci5733:blogs:2013|Blogs]] ] | ||
| - | ==== Breaking News ==== | ||
| - | * <hi #ffff00>**September 2, 2013**.</hi> The new semester begins. | ||
| - | |||
| - | ==== Extra Credit Assignments ==== | ||
| - | |||
| - | ===== 20013-14 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 CSCI5733: </b></font></html> No member of the CSCI5733 community shall take unfair advantage of any other member of the CSCI5733 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 | Yuanyuan Man | | ||
| - | ^ 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]]\\ | | | ||
| - | | 12 | 27/11 | Human Computation & Crowdsourcing\\ \\ 1. [[http://www.cse.cuhk.edu.hk/~king/PUB/csci5070/CSCI5070-08-Crowdsourcing.pdf|08-Crowdsourcing.pdf]] | Midterm Review | | | | ||
| - | | 13 | 4/12 | Wrap Up\\ \\ Project Presentations | | | [[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===== | ||
| - | |||
| - | ====== Examination Matters ====== | ||
| - | |||
| - | |||
| - | ===== Examination Schedule ===== | ||
| - | | ^ Time ^ Venue ^ Notes ^ | ||
| - | ^ Midterm Examination\\ TBA | TBA | TBA | TBA | | ||
| - | ^ Midterm Examination\\ TBA | 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 ^ | ||
| - | | TBA | TBA | TBA | TBA | | ||
| - | |||
| - | -Assignments (TBA) | ||
| - | -Written assignments | ||
| - | -Optional quizzes | ||
| - | -Midterm Examination (TBA) | ||
| - | - Project (TBA) | ||
| - | - Report (TBA) | ||
| - | - Presentations (TBA) | ||
| - | -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 ===== | ||
| - | |||
| - | ===== Final Project Presentation Sign-up Sheet ===== | ||
| - | |||
