582707 Adaptive Information Systems (4-6 ECTS)
T-106.6200 Special course in Software Techniques (4-6 ECTS)
[ Formal Data | Syllabus | Readings | Course Materials | Course Tools ]
Information systems suffer from an inability to satisfy the heterogeneous needs of many users. For example, Web courses present the same static learning material to students with widely differing knowledge of the subject. Most online stores still offer the same selection of "featured items" to customers with different needs and preferences. Virtual museums on the web offer the same "guided tour'' to visitors with very different goals and interests. Health information sites present the same information to readers with different health problems. A remedy for the negative effects of the traditional "one-size-fits-all'' approach is to develop systems with an ability to adapt their behavior to the goals, tasks, interests, and other features of individual users and groups of users. While Adaptive Information systems is a relatively young area, it evolves very fast. More and more commercial Adaptive Information systems become available each year. Starting with a handful or research teams worldwide and a few industrial pioneers such as Amazon.com, adaptation and personalization is now in focus of hundreds of researchers and practitioners.
The goal of the course is to get immersed into the world of the Adaptive Information Systems (AIS). The students in this class will learn about many aspects of AIS, get familiar with key AIS technologies, and explore examples of modern AIS. They will work in group to analyse and compare industrial personalized systems and (for additional credit) develop their own AIS. The students can also explore options to apply modern adaptation and personalization technologies in the context of larger projects. Those who will successfully complete the course will do the first solid step towards possible careers in the personalization industry and research.
The personalization industry is on the rise. In the coming years universities, research labs, and companies will need hundreds of experts who understand adaptive systems and personalization to lead various exciting projects. Leading internet companies such as Google, Yahoo, IBM, Microsoft, Ebay, AOL and others are now already engaged in research and development of various adaptive systems and seek to hire knowlegeable workers.This is your chance to be among the professionals of the new and exciting field.
The number of possible topics is too large to fit a single course. Every semester the instructor communicates with the new class to select a subset of topics to be covered. The full list of possible topics is provided below. Most, but not all of these topics are covered in the main Readings book. Contact the instructor in advance to vote for the topics that you really want to get included and watch the Course Materials pages to see the final list of topics.
I. Modeling Technologies
II. Adaptation Technologies
The course will include one small "midterm" course project (required) and one large group project (optional). You need to complete the smaller project to earn 4 ECTS. The large project is a requirement for those who take the course for 6 ECTS . The small project requires no programming skills. While the large project is programming-oriented, it is not expected that each students who is interested in this option has strong programming skills. Development of AIS requires a range of different skills such as domain analysis, algoritm design, modeling, etc. Each project team will required a range of expertise beyond programming. Students with knowledge of mathematics, statistics, education, psychology, artificial intelligence, etc. are encouraged to explore this option regardless of their programming skills.
Course assessment includes weekly readings, discussions, and projects. The instructor also reserves the right to administer unannounced quizzes if he feels that the students are not pursuing a resonable amount of assigned reading. Your final grade depends on the score you have earned.
After a brief introduction into the field provided by the instructor we will switch to a regular work mode. Every week we focus on one or two topics. Each topic will be presented in the lecture followed by relevant student presentations and a discussion. The practical part of the course include one research paper reading assignment, one analytics project and one large final project, which should be peformed in groups or, as an exception, individually.
Read all assigned chapters (one or two per week). It is your choice whether to read it before or after the lecture, but it should be done no more than 4 days after the class to allow space for discussion. Since reading is not very interactive and hard to measure activity, several additional activities are focused on your readings.
Choose one the core course topic (topic selection should be done by the third lectture). Select a paper on that topic, read, summarize, and (time permitting) present it in class. Topics will be assigned by request on FIFO basis. This project will include several activities for each paper:
Examine a specific group of industrial or research-level personalized systems or one complex adaptive system and present the results in class (about 10-15 min. presentation).
The goal of the final project is to convert the theory you learned in the course into practice. Work in groups or individually to develop a small, but complete adaptive system, which you will present to the instructor at the end of the course. It is expected that you will start your work on the final project at the start of the course, not complete it in a haste over the last week. To motivate your regular work on the project, every week starting from the announced deadline, you need to post at least one brief message into the group Blog summarzing your work towards the project done within a week, as well as any thoughs, doubts, ideas, etc.