Topics: Semantic Faceted Browse/Search, Vocabulary, Semantalytics, Inference, Semantic Foundation, Trust, Controlled Vocabulary, Artificial Intelligence, Semantic Web, Semantic Reasoning, Computer Science, Provenance, Use Cases, Web Science, Cutting Edge Technology, Context Modeling, Taxonomy, Knowledge Graph, Linked Data, Schema, Ontology
Course Numbers:
Course Numbers:
- CSCI 6961 - 01, CSCI 4961 - 01
Description:
Prepare students for research in semantic technologies 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 you to understand, conduct, and evaluate academic research while we discuss the emerging trends in semantic technologies. This course will have two primary threads around Ontologies and Knowledge Graphs. 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. Students may also participate in a group project designing, using, and/or evaluating ontology and knowledge graph enabled applications.
Goals:
Prepare students for research in semantic technologies
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)
Teach students how to develop a literature corpus for use in research
Learning Objective:
- Learn to critically review semantic technology papers
Learn to create & deliver technical presentations on research: individually & in groups*
Learn to prepare AND evaluate a research paper review
Learn to prepare research papers about a specific semantic web research question
Learn to find and evaluate related work
Learn to create a related work corpus and annotated bibliography
Assessment Criteria:
- Via written assignments
Via oral (individual and group presentations)
Via participation in class
Via group evaluation
Late submission policy: first time with valid reason – no penalty, otherwise 20% of score deducted each late day.
Most assignments will be due midnight ET Friday (but check each assignment carefully)
Prerequisites:
Basic knowledge of RDF/XML is expected
Basic knowledge of Artificial Intelligence and the Web is expected
Attendance:
Attendance at all classes is expected. If you are sick and can not attend, please contact the professor and TA in advance. Unexcused or missed classes are recorded and will incur an academic grade penalty.
Academic Integrity:
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.
Course: Advanced Semantic Web
Date: to