Modeling Real Estate Ecosystem with Cherre’s Knowledge Graph
Cherre CTO Ron Bekkerman, will speak at the Knowledge Graph Conference in May. During his session, Dr. Bekkerman will cover Cherre’s knowledge graph and how the graph is a model of the entire US real estate ecosystem. He will also present parallel algorithms for entity resolution and disambiguation in Cherre’s knowledge graph, and outline our current work on assessing entity similarities using (temporal) node embedding.
Cherre’s knowledge graph incorporates hundreds of millions of entities such as properties, addresses, individual and commercial owners, lenders, brokers, estate managers, lawyers etc. as nodes – while the edges are various types of connections between the entities. A wealth of attributes are associated with each entity. Cherre’s knowledge graph is a closed-world graph: it allows inferring an absence of connection between two entities if there is no edge between them in the graph. Furthermore, Cherre’s graph is temporal: edges and nodes are being added and deleted on a timely basis. Some of the main challenges in constructing a closed-world graph from noisy data sources are entity resolution and disambiguation.
To learn more about Cherre’s knowledge graph, register for the virtual conference.
May 4 – 7, 2020
New York, NY