Adele Howe
Office: 446 CS Building

Jaime Ruiz
Office: 464 CS Building

Class Time and Place:
Monday 12:00pm-2:00pm. AI Lab

Researchers need to keep up on the literature in their area. Their interests persist over long periods of time but their information needs morph as they read papers and conduct their own research projects. Often they share documents with colleagues, either informally via email or formally via portals such as citeulike. Although researchers employ a variety of tools (search engines, digests, alerts, bib tools, etc.), it is difficult to find one that incorporates all of the capabilities.

We have been developing a computational framework to allow researchers to find, rate and organize documents by their own topics as well as follow topics from colleagues. The framework supports refining and learning about topics and maintaining a personal repository.

The CS793 will focus on extending the capabilities of this framework by reading relevant literature and constructing and evaluating new components for it. Some components of interest are:

  • query reformulation
  • adaptive user interfaces
  • document collaborative filtering
  • information extraction/Named Entity Recognition from research papers
  • Document organization
  • repository and topic visualization
  • topic discovery

The goal will be one or more conference papers in areas of artificial intelligence and human computer interaction.


Consent from the instructors.


Here are the formally graded elements of the course and associated weighting: TBD

Semester grades are determined by the weighted sum of points earned in each of these areas. A subjective curve (set by the instructor) is used to map points onto grades. Typically, the curve is set such that the class mean gets an B, one standard deviation above the mean is an A, one deviation below is a C, and so forth. However, the instructor retains the right to move the curve either direction. If the entire class is strong, the mean might be better than a B. Conversely, if the class as a whole is weak, the mean might be below a B...

Exams and projects will be done individually and grades assigned on an individual basis. Further, students not already familiar with the CSU Honor Pledge should review this clear and simple pledge and always adhere to it.

Late and Makeup Policy

No late materials will be accepted.

Important Dates

Literature Review10%
Research Paper40%
Poster Session50%

In Class Participation

All students taking this course are expected to participate actively.

Professional Conduct

All students are expected to conduct themselves professionally. We (the instructors and GTAs) assume you are familiar with the policies in the student information sheet for the department. Additionally, you are computing professionals, albeit perhaps just starting. You should be familiar with the code of conduct for the primary professional society, ACM. You can read the ACM Code of Conduct HERE.

We work to maintain an environment supportive of learning in the classroom and laboratory. Towards that end, we require that you be courteous to and respectful of your fellow participants (i.e., classmates, instructors, GTAs and any tutors). In particular:

  • Please turn off the ring on your cell phone. If you are expecting an emergency call, sit near the door and slide out discretely to take it.
  • In class use of electronic devices in general, and laptops specifically, is permitted as a courtesy so that you may better participate and learn. If at any time the instructor judges that an electronic device is becoming a distraction the student may be asked to to turn it off and put it away.
  • All exams and quizzes are to be done without the aid of notes of any kind. Laptops and all other electronic devices must be shut and put away during exams and quizzes.