1. CS 79995 & CS 69995 ST: Probabilistic Data Management Fall 2016 Xiang Lian Kent State University Kent, OH 44240 xlian@kent.edu 1

2. Probabilistic Data Management An Overview of Probabilistic Data Management Data Uncertainty Model Probabilistic Query Answering Over Probabilistic and Uncertain Databases Probabilistic Graph Databases Data Quality in Probabilistic Databases 2

3. Background Required Probability & statistics (math) Algorithms & data structure Database techniques (e.g., index) You need to be able to look up how to get things done (for example, read papers/surveys from online resources, using digital library, Google, Wikipedia, etc.) 3

4. Skills Required This course is a seminar course for Master & Ph.D. students, in the sense that you need to learn how to do research – Read papers – Do surveys – Write papers (Latex) Tackle research problems – Do experiments – Give presentations & demonstrations – Research collaborations 4

5. Study Group Please form a team with at most 3 team members The workload should be distributed evenly to each team member Each team needs to finish 1 survey + 1 research paper/report + 2 presentations: – A survey on a selected research topic (including a comprehensive reading list on this topic) – A presentation on 1-2 existing research papers in your selected research directions (20-25 minutes) – A paper-like report (including introduction, problem definition, related work, the proposed approaches, experimental evaluation, and conclusions); – A presentation & demonstration on your research paper 5

6. Survey & Research Paper I will post a reading list of papers – It does not include all related works, but only a few typical papers in different research directions – You need to search digital libraries (e.g., ACM portal, IEEE Xplore, etc.) and Google the Web to find more related works in each direction You need to decide which topics/problems you want to study Please make an appointment with me to discuss research directions of your teams (within the first 3 weeks of the semester; on or before Sept. 14) 6

7. Scoring and Grading 5% - Attendance & Questions 60% - Research Projects/Papers – Survey on papers for the selected research topics in recent database conferences/journals (25%) – Code and report for the research project in paper format (including introduction, related works, problem definition, solutions, experiments, and conclusions; 35%) 40% - Presentations – Presentation for 1-2 related works in the selected research direction (20%) – Presentation and demonstration for the proposed research project (20%) 5% - Bonus Points, rated by other team members 7

8. Scoring and Grading (cont'd) A = 90 or higher B = 80 - 89 C = 70 - 79 D = 60 - 69 F = <60 The maximum score you can get is: 110! 8

9. Use of the Textbook No textbooks!! The only resources are papers!! – ACM digital library http://dl.acm.org/ – IEEE Xplore Digital Library http://ieeexplore.ieee.org/Xplore/home.jsp – DBLP http://dblp.uni-trier.de/ – Database Conferences SIGMOD, PVLDB, ICDE, EDBT, CIKM – Database Journals TODS, VLDBJ, TKDE 9

10. The Schedule for the Class 10 I expect to give lectures and introduce the concepts and techniques of probabilistic data management for the first month (September) Then, each team (or student, depending on the available time and the number of teams) will present 1-2 related works in the literature during the class, and meanwhile prepare the survey (October) Finally, each team will start to identify research problems and find solutions. You need to write a report in the paper format, do experiments (comparing with the existing approaches), and present/demonstrate your paper in class (November & December).

11. Advices & Suggestions Tools: – Latex vs. Word Survey – Check "Related Work" sections in most recent papers, and you can obtain more related papers – Read abstract/introductions of papers, and classify papers into different categories (this will help you later to identify problems that have not been solved before) Paper – Even if you are not familiar with some topics, try to read as many related works as possible to understand the general problems and solutions in these topics (you can skip some part, if it is too hard to understand) – Stick to the problem you want to solve, and use any resource you can find to solve the problem (note: DO NOT simply apply previous techniques to your problem, since it is not counted as your contributions!!) 11

12. Advices & Suggestions (cont'd) Do not copy from any sources (even for the survey) – Any form of academic dishonesty will be strictly forbidden and will be punished to the maximum extent – Allowing another student to copy one's work will be treated as an act of academic dishonesty, leading to the same penalty as copying 12

13. Advices & Suggestions (cont'd) If the resulting surveys and papers are of high quality and novel, I highly recommend you to submit them to database conferences or journals After this class, self-motivated, hardworking, and creative students with good performance on surveys/papers may have the chance to join my lab (Big Data Science Research Lab)! 13

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