Knowledge Representation: Semantics and Data Structures

This lecture covers the representation of semantics in information retrieval and data mining, emphasizing the importance of explicit knowledge representation. It discusses the agreement on data structures, database schemas, and the well-understood meaning of data values. The lecture also explores the challenges of searching for data on the web, the limitations of HTML for encoding data semantics, and the benefits of schema-less data. It delves into the concept of semi-structured data, XML as a document markup language, and the use of ontologies to overcome semantic heterogeneity. Additionally, it explains the RDF framework, resource description, and the classification of RDF resources. The lecture concludes with an overview of popular ontologies and knowledge bases like WordNet, WikiData, Google Knowledge Graph, and Schema.org.

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