BCA Knowledge Engineering

bcasemester 8Elective

This course offers detailed concept about knowledge representation, logic, reasoning and principles. It includes introduction, knowledge acquisition, knowledge representation and reasoning. It does not entirely focus on theoretical concept but also strongly focuses on practical skill based learning.

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Chapter Wise Notes Question Banks Syllabus Chapter Wise Questions Viva Practical

Unit 1:Introduction

Overview of data. Information and knowledge, Knowledge engineering and Knowledge management, Artificial intelligence use in knowledge Engineering, Knowledge based system and its applications

Unit 2:Knowledge Acquisition

Information gathering, Information retrieval, Applications of Natural Language processing (Morphology, lexicon, syntax and semantics; Parsing, POS tagging, named entity tagging)

Unit 3:Machine Learning

Machine Learning and its applications, Supervised and unsupervised learning, Classification and clustering, Classification algorithms (Linear classifiers; nearest neighbor; Support Vector Machines; Decision tree; Random forest; Neural networks; Case based reasoning)

Unit 4:Knowledge representation and reasoning

Proposition logic, predicate logic and reasoning, Knowledge representation languages, Non-monotonic reasoning, Probabilistic reasoning

Unit 5:Ontology Engineering

Overview to Ontology, Classifications of ontology, Methodology use in Ontology, Ontology VS Language

Unit 6:Knowledge Sharing

Information Distribution and Integration, Semantic web and its applications (RDF and linked data; Description logic; Web Ontology language), Social web and semantics