Entity-based results are becoming an integral part of the search experience. Search-centric companies highly rely on knowledge graphs in providing the necessary information for building rich search experiences. An entity can originate from a structured, semi-structured, or unstructured data source. An entity passes through a series of stages to be onboarded into a knowledge graph and then served as part of a search result. This talk presents the life cycle of an entity including extraction, schema mapping, ingestion, entity resolution, data quality, and publishing. It covers the challenges and approaches employed at each stage. It also introduces some of the different experiences that can be generated for a given entity. Finally, it covers the multilingual aspect of knowledge graphs and the challenges of maintaining them at scale.
#knowledgegraphs #knowledgegraphconference #knowledgegraphschema
The COVID-19 pandemic has mobilized researchers worldwide to investigate many aspects of the outbreak, ranging from case statistics, patient demographics, transportation modeling, epidemiological studies, to viral genome sequencing. Relevant data are produced and publically shared at an unprecede...
This presentation will introduce and detail the current work of the W3C Dataset Exchange Working Group, including detail of the developments in the DCAT (Data Catalog) vocabulary and the proposal for content negotiation by profile (ConnegP) which is being developed by the working group in conjunc...
