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Semester 1
Knowledge Graphs (INFR11215)
Subject
Informatics
College
SCE
Credits
10
Normal Year Taken
4
Delivery Session Year
2023/2024
Pre-requisites
As above.
Course Summary
Recent advances in AI have changed the perception of what AI systems can do, from decision sup-port to answering questions. An underlying feature of many AI systems concerns how knowledge is acquired, represented, and reasoned with. Today, knowledge graphs are used extensively by most of the world's leading IT companies, from search engines (e.g., the content of the Google knowledge panel is a tiny fragment of Google's knowledge graph) and chatbots to product recommenders and many applications of AI and data science. This course provides the theory and practice of knowledge graph construction, reasoning, and question answering technologies. The students will analyse case studies to construct knowledge graphs and apply reasoning services on them.
Course Description
In this course, we will cover topics such as:Knowledge graph foundation and standards - RDF (Resource Description Framework) - OWL (Web Ontology Language) - SPARQL (Query Language for RDF and OWL)Knowledge graph construction, embeddings, and completionKnowledge graph reasoning and querying - Tableaux algorithm - Tractable schema reasoning in EL - Tractable query answering in DL-Lite - Semantic parsing The students will be expected to prepare for the lectures by reading related textbook chapters and papers. In addition to lectures, there will be some tutorials, helping students to better understand some concepts and theories.
Assessment Information
Written Exam 80%, Coursework 20%, Practical Exam 0%
Additional Assessment Information
There will be one piece of individual coursework. It will involve the student working on a specific case study where the student will be expected to construct and query a knowledge graph to solve the case study in hand. It will take around 10 hours. The length limit will be around 1000-1200 words.
view the timetable and further details for this course
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