Wednesday: 11AM to 12PM
Thursday: 11:00AM to 12:00PM
|Class Time and Location||Wednesday 5:45PM to 8:45PM|
Mon. 1 to 3PM
Wed. 1 5o 3PM.
This research seminar course introduces state-of-the art algorithms on the detection of anomalous or emerging events and other relevant patterns in the mobile context and/or data mining of spatial temporal, textual, or social media data. Examples of applications include disease outbreaks detection using public health data, such as hospital visits and medication sales; detection and prediction of crime events using historical crime record and streaming twitter data; and crowdsourcing human mobility and social media data to detect traffic congestion, air pollution, and power leakage events. More applications include the detection of computer network viruses, computer intrusions, malicious android applications, faked receipts and financial documents, Twitter robot accounts, new business hotspots, human right violations, Healthcare fraud activities, and etc.
The first 10 class sessions will be lectures, and the following class sessions will be mainly student presentations and discussions. There will be no exams. The grade distribution is as follows:
There are three options:
Each team is allowed to have up to 2 members. The final project report must have at least 10 pages for teams of size 2 (6 pages for teams of size 1) and follow IEEE two-column style format, with the font name Times New Roman and size 10.
Submission deadline: To be announced.
|Student Name||Paper Title|
Late Submission Policy:
Assignments must be submitted before the class on the specified due date (Monday of designated week). A penalty of 30% will be deducted from your score for the first 24-hour period if your assignment is late. A penalty of 70% will be deducted from your score for >= 24-hour period. Assignments submitted more than 3 days late will not be assessed and will score as a zero (0). Weekend days will be counted. For assignments, you are encouraged to type your answers.
Policy on Cheating:
Cheating in an exam will result in an E grade for the course. Further, the students involved will be referred to the Dean's office for disciplinary action.
Homework problems are meant to be individual exercises; you must do these by yourself. Any of the following actions will be considered as cheating.
Cheating in a homework exercise will result in the following penalty for all the students involved.
Students who cheat in two or more homeworks will receive an E grade for the course. The names of such students will also be forwarded to the Dean's office for disciplinary action.
Class attendance is required and checked. Each case of missing class without a proper explanation will cause 20% less from your final numerical grade. If you miss a class, it is your responsibility to find out the material covered in the class. There will absolutely no makeup classes. Only in specific, unavoidable situations students are allowed to excuse absences from class: 1) personal emergencies, including, but not limited to, illness of the student or of a dependent of the student, or death in the family [Require doctor's note]; 2) religious observances that prevent the student from attending class; 3) participation in University-sponsored activities, approved by the appropriate University authority, such as intercollegiate athletic competitions, activities approved by academic units, including artistic performances, academic field trips, and special events connected with coursework; 4) government-required activities, such as military assignments, jury duty, or court appearances; and 5) any other absence that the professor approves.