Explain the concept of representation. How does probabilistic reasoning handle uncertainty in knowledge representation?
What is ontology? How can it be used in knowledge engineering?
Explain how predicates can be used for knowledge representation and reasoning with examples.
What is semantic web? What are the major challenges in sematic web?
What are RDF and linked data? What are the principles of linked data?
Differentiate between classification and clustering. Explain four stages of case based reasoning.
Write short notes on (any two):
a) Linear classifier
b) Parsing
c) Description logic
Attempt any TWO questions
[2x10=20]Why knowledge acquisition is required? Explain the knowledge acquisition process in detail.
What is the role of POS tagging in natural language processing? How NER can be used for information extraction process? Explain.
What are support vectors and margins? How these concepts are used in Support Vector Machines to classify the datasets? Explain in detail.