1. Eick : First Lecture COSC 7363 Overview Advanced AI Hyla-Tree Frog History of AI thr. 1995 AI and the Web Traditional Clustering Graph Mining Spatial and Spatio-Temporal Data Mining Reinforcement Learning and Learning to Lean Shape-based Image Retrieval

2. Eick : First Lecture COSC 7363 General Thoughts and Teaching Philosophy I Focus of the course is providing more indepth knowledge in the areas mentioned on the previous slight and to learn how to read, summarize, present, and evaluate scientific papers. Interactive discussion of papers and research topics No cheating! No cheating! No cheating! Teaching Philosophy: You will have to face some criticism; otherwise, you will not learn anything. Learning without exposing yourself to errors is impossible!! If you do not know what you do wrong, it is hard to improve! No matter if you like it are not, you will have to talk a lot in this course. During the course you will make a lot of informal, unstructured presentations. You do Something Feedback Learn

3. Eick : First Lecture COSC 7363 General Thoughts and Teaching Philosophy II No projects and only 2 quizzes first week of March and 3 rd week of April. Learning by doing!! I am aware that most of you are not too experienced in these matters; consequently, my expectations are initially quite low. Not reading papers that will be discussed on a particular day is not acceptable! One objective if this course is to describe what other do in your own words – consequently, no copying from any sources (web or class mates). If you face particular or unusual problems when taking this course: talk to me during my office hours or send me an e-mail. During the course you will also make 2 more formal presentations.

4. Eick : First Lecture COSC 7363 General Thoughts and Teaching Philosophy III You will also get some exposure concerning writing abstracts, summaries, introductions, white paper, and conclusions. Learning to write included to know what people expect concerning what you write and how what you write will be judged. In this course, we will try it several teaching strategies, some of which will be revised or even abandoned as the course progresses. Is a by product you will hopefully get a better understanding on how to conduct a scientific project and on how to summarize and present its results. Occasionally, Dr. Eick will present 10-40 minute lectures that provide background knowledge concerning the papers that will be discussed next.

5. Eick : First Lecture COSC 7363 Topics Covered I.History of AI thr. 1995 – the 1994 Turing Award Lectures II.AI and the Web – how to assess the relevance of webpages? III.Traditional Clustering IV.Shape-based Image Retrieval V.Spatial and Spatio-Temporal Data Mining VI.Reinforcement Learning and Learning to Lean VII. Graph Mining Papers allocation to areas: I: 2; II: 2-4; III:3-4; IV:1; V:3-5 VI:2-3; VII:0-1.

6. Eick : First Lecture COSC 7363 Paper Reading List COSC 7363

7. Eick : First Lecture COSC 7363 Paper Reading List COSC 7363

8. Eick : First Lecture COSC 7363 Teaching Plan Next 5 Weeks Janurary 16: Course Overview (see also http://www2.cs.uh.edu/~ceick/7363/7363.html) http://www2.cs.uh.edu/~ceick/7363/7363.html January 18: (Read) Feigenbaum Paper  How to read a paper January 23: Prepare Slow PaperWalkThrough Page/Brin Paper January 25: Mostly Lecture January 30: Prepare Slow PaperWalk Through ICDM06 Best Research Paper Award Feb. 1: TBDL --- Brin/Page Background?!? Feb. 6: Likely Reddy Turing Award Paper Feb. 8: Student Guided Discussion DBSCAN paper Feb. 13: Student Guided Discussion Silhouette Paper Feb. 15: Student Presentation Langville/Mayer Paper (optional) Feb. 20: On Writing Abstracts, Introductions, Conclusions Feb. 22: Bregman Divergences Paper

9. Eick : First Lecture COSC 7363 Course Activities A lot of informal presentations and discussions 1 formal presentation about a paper covered in the course Writing abstracts, introductions, conclusions and paper reviews --- learning by doing 2 Quizes that ask questions about papers we have read Discussions Learning how to read, summarize, present, and review papers. Background knowledge on ‘how to perform a research project’ and on ‘how to be successful in your research / career’. Discussing many other, entertaining things---such as the ‘Giant Squid’, life of Sergey Brin--- most of which are still related to one of the above activities.

10. Eick : First Lecture COSC 7363 Forms of Covering Papers in the Course Papers will be discussed, presented in many different forms in this course: Slow Walk Through (I only plan to have 3 of those!!) Guided Walk Through Other Walk Throughs (I did not consider yet!) By answering a given set of quesitons. Just Discussion 1-Page (5-page) Summary of a Paper Professional Powerpoint Presentation Profession Paper Review (  April 2007) …

11. Eick : First Lecture COSC 7363 Slow Walk Throughs Used for the first two “AI and the web” papers Paper will be discussed paragraph by paragraph Very slow!! Therefore, there will be only 2-4 of those… Course participants are responsible for sections of the paper. Responsibilities include: –Lead discussion –Present short summaries for boring sections to speed up things –Ask questions about things they do not understand –Prepare review questions for the other students that will be discussed either immediately or after a delay. Everybody should read the paper carefully including the sections you are not responsible for. It might be a good idea to create brief summaries for the read sections and to capture, what you do not understand, in form of questions. If you finished reading the paper try to come up with your own evaluation of the paper We will not only discuss the contents of the paper, but also address the question “why an author writes a paper in a particular way” and “how the presentation of the discussed paper could be improved / made more convincing. Additionally, issues on how to write a paper will be discussed during slow walk throughs --- these matters are Dr. Eick’s responsibility..

12. Eick : First Lecture COSC 7363 Sergey Brin CV (Сергей Михайлович Брин) (see also http://en.wikipedia.org/wiki/Sergey_Brin )http://en.wikipedia.org/wiki/Sergey_Brin Sergey Brin is co-founder and President, Technology at Google. Originally a native of Moscow, he received a bachelor of science degree with honors in mathematics and computer science from the University of Maryland at College Park. He is currently on leave from the Ph.D. program in computer science at Stanford University, where he received his master's degree. Sergey is a recipient of a National Science Foundation Graduate Fellowship as well as an honorary MBA from Instituto de Empresa. It was at Stanford that he met Larry Page and worked on the project that became Google. Together they founded Google Inc. in 1998, and Sergey continues to share responsibility for day-to-day operations with Larry Page and Eric Schmidt.Instituto de Empresa Sergey's research interests include search engines, information extraction from unstructured sources, and data mining of large text collections and scientific data. He has published more than a dozen academic papers and has been a featured speaker at several international academic, business and technology forums, including the World Economic Forum and the Technology, Entertainment and Design Conference. He has shared his views on the technology industry and the future of search on the Charlie Rose Show, CNBC, and CNNfn. In 2004, he and Larry Page were named "Persons of the Week" by ABC World News Tonight. See also http://money.cnn.com/magazines/fortune/fortune_archive/2006/10/02/8387489/index.htm?postv ersion=2006100210 for more about Google’s work philosophy. http://money.cnn.com/magazines/fortune/fortune_archive/2006/10/02/8387489/index.htm?postv ersion=2006100210 Sergey

13. Eick : First Lecture COSC 7363 Assignments Tong Slow Walk Through.Remark: scheduled for Tu., January 30, 2007 1. 2. 3. 4. 5.

14. Eick : First Lecture COSC 7363 On Exploring Boundaries There is always a limit on what you can still do / cannot do. However, these boundaries are dynamic and can be changed through training Analogy: Training for an Olympic Marathon… Several of the papers we will read will be not easy to understand If you read the papers we discuss in the course now you will understand 25% of the contents; hopefully, on May 1, 2007 you will understand 70% of the papers discussed… You should believe into yourself that you can extend and challenge these boundaries. A statement like “I will never understand this paper is not practical” is not productive… Being not afraid of boundaries is particularly important for personal growth and research.

15. Eick : First Lecture COSC 7363 Analogy: Training to win a Medal at an Olympic Marathon You need to have some basic talent to have a chance --- but a lot of people have talent… You have to be committed and have to believe that you have a chance You have to have some luck At least 50% depends on the training you do. Dilemma: –If you train too hard you get injured –If you train a little you have no chance –Marathon training is about extending your boundaries without getting hurt... –To be successful you need a coach (or even a team of coaches) What you can do today What you can do in a year

16. Eick : First Lecture COSC 7363 Some Ingredients for Success Talent Self Confidence and Commitment Persistance Training Luck Time, Money, Food, Friends, Place to live, …

17. Eick : First Lecture COSC 7363 Another Example: Finding the Giant Squid Story: http://www.msnbc.msn.com/id/9503272/http://www.msnbc.msn.com/id/9503272/ On sperm whales: http://www.oceanicresearch.org/spermwhales.htmhttp://www.oceanicresearch.org/spermwhales.htm Another Sperm Whale Photo: http://nmml.afsc.noaa.gov/gallery/cetaceans/pm-13_sperm.htmhttp://nmml.afsc.noaa.gov/gallery/cetaceans/pm-13_sperm.htm We knew that sperm whales fed on the squid, and we knew when and how deep they dived,” Kubodera said. “So we used them to lead us to the squid.” Giant Squid Sperm Whale 18 meters Kubodera said catching the squid on film was the result of 10 years of sleuthing. 10 meters