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Welcome to the CS5560-Rohithkumar-N-Lab wiki!

Course Objectives, Goals or Learning Outcomes:

The goal of this course is to introduce theoretical and practical aspects of knowledge discovery and management (including Natural Language Processing, Information Extraction/Retrieval, Machine Learning, and Semantic Web) for Big Data. Throughout this course, students will obtain extensive hands-on experiences in the development of intelligent mobile application using semantic techniques and with various tools. Students will be able to apply the concepts and techniques to emerging applications such as question and answering.

Topics:

. Knowledge Engineering for Big Data

. Knowledge Discovery for Big Data

• Natural Language Process (NLP)

• Information Retrieval & Information Extraction

• Machine Learning: Shallow Learning and Deep Learning (Text Classification)

• Tools: Cloudera/Spark MLlib, TensorFlow, CoreNLP, OpenIE

. Knowledge Representation & Processing

• Ontologies and Semantic Web: RDF, RDFS, OWL

• Query, Reasoning with Ontologies (SPARQL, SWRL)

• Tools for Knowledge creation: Protégé, OWL API, Face++, Racer

. Intelligent Applications

• Question and Answering Systems

• Tools: IBM Watson Services, Amazon ML Services, AlchemyAPI