Time Ontology in OWL W3C Candidate Recommendation Draft 15 November 2022 More details about this document This version: https://www.w3.org/TR/2022/CRD-owl-time-20221115/ Latest published version: https://www.w3.org/TR/owl-time/ Latest editor's draft:https://w3c.github.io/sdw/time/ History: https://www.w3.org/standards/history/owl-time Commit history Implementation report: https://www.w3.org/2015/s
There are two key characteristics of RDF stores (aka triple stores): the first and by far the most relevant is that they represent, store and query data as a graph. The second is that they are semantic, which is a rather pompous way of saying that they can store not only data but also explicit descriptions of the meaning of that data. The RDF and linked data community often refer to these explicit
Fashionpedia Fashionpedia is a dataset which consists of two parts: (1) an ontology built by fashion experts containing 27 main apparel categories, 19 apparel parts, 294 fine-grained attributes and their relationships; (2) a dataset with 48k everyday and celebrity event fashion images annotated with segmentation masks and their associated per-mask fine-grained attributes, built upon the Fashionped
AWS Database Blog Building a knowledge graph with topic networks in Amazon Neptune This is a guest blog post by By Edward Brown, Head of AI Projects, Eduardo Piairo, Architect, Marcia Oliveira, Lead Data Scientist, and Jack Hampson, CEO at Deeper Insights. We originally developed our Amazon Neptune-based knowledge graph to extract knowledge from a large textual dataset using high-level semantic qu
Knowledge Graphs (KGs) have emerged as a compelling abstraction for organizing the world’s structured knowledge, and as a way to integrate information extracted from multiple data sources. Knowledge graphs have started to play a central role in representing the information extracted using natural language processing and computer vision. Domain knowledge expressed in KGs is being input into machine
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