CSCI 4963/6963 TOPICS IN KNOWLEDGE GRAPHS
Prepare students for research in knowledge graphs. Teach students how to: Read and find relevant research papers, Present research ideas, Synthesize material, Identify gaps in existing research, Critically review (as one might do for a publication venue) Develop a literature corpus for use in research.
This course will discuss emerging trends in research on semantic technologies, focusing on knowledge representation, management, and modeling, including applications of knowledge graphs and ontologies. This is a seminar course, not a lecture course. Students will give many presentations and lead discussions throughout the course that will help them to understand, conduct, and evaluate academic research while we discuss the emerging trends in semantic technologies. This course is intended to give students a foundation that will allow them to participate in leading edge semantics research and also provide students with an opportunity to produce a research survey. The research survey may serve as a foundation for a related work chapter of a thesis and can also serve as a way to fulfill the research qualifying examination requirement in the CS program. Participants will read relevant papers and learn how to critically review ontology and knowledge graph papers, as well as ontologies and knowledge graphs themselves. They will also use the review to propose a research topic in knowledge graphs that can serve as the basis for their dissertation research, or as an investigation within a project they are currently working on.
Prerequisites: CSCI 2300 (INTRO TO ALGORITHMS) AND either CSCI 6340 or CSCI 4340 (Ontology Engineering)
- Via written papers
- Via oral (individual) presentations
- Via participation in class
- Late submission policy: first time with valid reason – no penalty, otherwise 20% of score deducted each late day.
Attendance at all classes is expected. If you are sick and can not attend, please contact the professor in advance. The class includes many group participation activities and participation in class is included in the final grade evaluation. Missed classes are recorded and will impact grades.
The Rensselaer Handbook of Student Rights and Responsibilities and The Rensselaer Graduate Student Supplement define various forms of Academic Dishonesty and procedures for responding to them. All forms are violations of the trust between students and teachers. Student-teacher relationships are built on trust. For example, students must trust that teachers have made appropriate decisions about the structure and content of the courses they teach, and teachers must trust that the assignments that students turn in are their own performance. Acts that violate this trust undermine the educational process.
The Rensselaer Handbook of Student Rights and Responsibilities and The Rensselaer Graduate Student Supplement define various forms of Academic Dishonesty and you should make yourself familiar with these. In this class, all assignments that are turned in for a grade must represent the student’s own work. In cases where help was received, or teamwork was allowed, a notation on the assignment should indicate your collaboration. Submission of any assignment that is in violation of this policy will result in a penalty. If found in violation of the academic honesty policy, students may be subject to two types of penalty. The instructor administers an academic [grade] penalty and the student is reported to the Dean of Students or the Dean of Graduate Education as appropriate. The first violation results in 0 grade for that assignment. The second violation results in failure of the course. If you have any questions concerning this policy before submitting an assignment, please ask for clarification.
Students with Disabilities
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Course: Topics in Knowledge Graphs