Knowledge Representation and Reasoning (KRR) is a field of AI that deals with capturing knowledge of the world in a form suitable for machines to act on. This helps machines in taking decisions based on the domain knowledge and rules. In this course, we will be looking at KRR from a Semantic Web perspective. Semantic Web technologies are now widely used by several commercial enterprises (Google, Amazon, LinkedIn, IBM, GE) in the form of Knowledge Graphs (semantic descriptions of entities and their relationships) and ontologies. They play a key role in knowledge driven applications across several domains such as life science, geoscience, healthcare, IoT, smart cities etc.
- Course name: Semantic Web
- Course code: CSE632
- Class hours
- Tuesday, 11:30am to 1:00pm
- Thursday, 10:00am to 11:30am
- Class location: C21, Old Academic Building
- Teaching Assistants
- Nihit Jain (firstname.lastname@example.org)
- Aayush Jain (email@example.com)
- Naresh Nunna (firstname.lastname@example.org)
- Akash Gosain (email@example.com)
- Office hours
- TA: Wednesday, 2:30pm to 3:30pm at Library ground floor (send an email beforehand)
- TA: Monday, 2:30pm to 3:30pm at Library ground floor (send an email beforehand)
- Instructor: send an email (firstname.lastname@example.org) for appointment
- Backpack URL: https://www.usebackpack.com/iiitd/w2019/cse632
- Course Logistics pdf
- AI, KRR, and the Semantic Web pdf
- RDF pdf
- Prof. Simpson’s notes on Mathematical Logic
- Raymond M. Smullyan. First-Order Logic. Dover Publications, New York, 1995.
- Uwe Schöning. Logic for Computer Scientists, Birkhäuser, 2008.
- Mordechai Ben-Ari. Mathematical Logic for Computer Science, Springer, 1993.
- Description Logics pdf
- Introduction to OWL pdf
- Designing and Building an Ontology pdf
- Course Project pdf
- Ontology Design Patterns pdf
- Description Logic Reasoning pdf
- Ontology Quality Assessment pdf