Methods from Artificial Intelligence (AI) form the basis for many advanced information systems. These techniques address problems that are difficult to solve or not efficiently solvable with conventional techniques. Building on the undergraduate curriculum this unit introduces the student to advanced AI methods and their applications in information systems.
Minimum total expected workload equals 12 hours per week comprising:
(a.) Contact hours for on-campus students:
(b.) Additional requirements (all students):
See also Unit timetable information
Completion of the Bachelor of Computer Science or equivalent to the entry requirements for the Honours program. Students must also have enrolment approval from the Honours Coordinator.
Ingrid Zukerman
Consultation hours: Wed 3-4
Lachlan Andrew
Consultation hours: Tue 3-4
Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through the Student Evaluation of Teaching and Units (SETU) survey. The University’s student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.
For more information on Monash’s educational strategy, see:
www.monash.edu.au/about/monash-directions/ and on student evaluations, see: www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html
Students have appreciated the variety of topics and the introduction to Minimum Message Length (MML) and Machine Learning.
If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp
| Week | Activities | Assessment |
|---|---|---|
| 0 | No formal assessment or activities are undertaken in week 0 | |
| 1 | Introduction to Language Technology and User Modeling | |
| 2 | Revision: Probability and Machine learning | |
| 3 | Document retrieval | Assignment 1 handed out |
| 4 | Recommender systems | |
| 5 | Dialogue systems I | Assignment 1 due and Assignment 2 handed out |
| 6 | Dialogue systems II (POMDPs) | |
| 7 | Hidden Markov models | Assignment 2 due |
| 8 | Dynamic programming | Assignment 3 handed out |
| 9 | Clustering | |
| 10 | Challenges of clustering | Assignment 3 due and Assignment 4 handed out |
| 11 | Feature selection | |
| 12 | Putting it all together -- identifying electric loads | Assignment 4 due |
| SWOT VAC | No formal assessment is undertaken in SWOT VAC | |
| Examination period | LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/ academic/education/assessment/ assessment-in-coursework-policy.html |
*Unit Schedule details will be maintained and communicated to you via your learning system.
Assignment and Examination, relative weight depending on topic composition. When no exam is given students will be expected to demonstrate their knowledge by solving practical problems and maybe required to give an oral report.
| Assessment Task | Value | Due Date |
|---|---|---|
| Assignment 1 - Document retrieval and recommender systems | 15% | Week 5 |
| Assignment 2 - Dialogue systems | 15% | Week 7 |
| Assignment 3 - Hidden Markov models | 15% | Week 10 |
| Assignment 4 - Clustering | 15% | Week 12 |
| Examination 1 | 40% | To be advised |
Faculty Policy - Unit Assessment Hurdles (http://intranet.monash.edu.au/infotech/resources/staff/edgov/policies/assessment-examinations/assessment-hurdles.html)
Academic Integrity - Please see resources and tutorials at http://www.monash.edu/library/skills/resources/tutorials/academic-integrity/
Further details will be provided in the assignment handout.
Further details will be provided in the assignment handout.
Further details will be provided in the assignment handout.
Further details will be provided in the assignment handout.
Additional reading:
Natural Language Processing for Online Applications (2nd Edition), Peter Jackson and Isabelle Moulinier, John Benjamins Publishing 2007
Speech and Language Processing, Daniel Jurafsky and James H. Martin, Prentice Hall 2009
Introduction to Machine Learning (3rd Edition), Ethem Alpaydin, MIT Press 2014
Artificial Intelligence: A Modern Approach (3rd Edition), StuartRussell and Peter Norvig, Prentice Hall 2010
Monash Library Unit Reading List (if applicable to the unit)
http://readinglists.lib.monash.edu/index.html
Types of feedback you can expect to receive in this unit are:
Submission must be made by the due date otherwise penalties will be enforced.
You must negotiate any extensions formally with your campus unit leader via the in-semester special consideration process: http://www.monash.edu.au/exams/special-consideration.html
Resubmission is not possible.
It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/student-academic-integrity-managing-plagiarism-collusion-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an electronic submission). Please note that it is your responsibility to retain copies of your assessments.
If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.
Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: www.policy.monash.edu.au/policy-bank/academic/education/index.html
Important student resources including Faculty policies are located at http://intranet.monash.edu.au/infotech/resources/students/
The University provides many different kinds of support services for you. Contact your tutor if you need advice and see the range of services available at http://www.monash.edu.au/students. For Malaysia see http://www.monash.edu.my/Student-services, and for South Africa see http://www.monash.ac.za/current/.
The Monash University Library provides a range of services, resources and programs that enable you to save time and be more effective in your learning and research. Go to www.lib.monash.edu.au or the library tab in my.monash portal for more information. At Malaysia, visit the Library and Learning Commons at http://www.lib.monash.edu.my/. At South Africa visit http://www.lib.monash.ac.za/.