Semantics, SEO, Social, and What They Mean to Sourcing

This podcast with Dave Copps, CEO of PureDiscovery Corporation, will open your eyes to some thoughts on search and sourcing from the mind of a man who has been thinking about it for almost two decades. Copps’ company “is the creator of BrainSpace, an intelligent software platform that transforms an organization’s documents into a working collective intelligence. PureDiscovery BrainSpace semantically connects people and knowledge in ways and on a scale that simply was not possible before.” As we are really beginning to see, semantic search is becoming the future of the way we source for candidates.

There are two major points to take away from this podcast discussion:

Innovation networks. PureDiscovery’s BrainSpace technology is developing what Copps calls innovation networks, or ‘KnowledgeGraphs.’ Copps says that the marriage of semantic and social will take us from making connections of who-knows-who and progress search to be able to determine, within those connections, who-knows-what. Companies will be able to discover what they know within their employee networks. Of course, this is already being done via internal communication technologies, but adding the semantic layer to these technologies will make discovering this information easier, as we may not always know the various different ways of saying (or searching for) specific keywords.
Seek-and-find search will be reversed. We are in the beginning stages of being able to teach systems how to find us instead of us going out to find knowledge. We will be able to relate to the world based on what it knows, is interested in, and is tied to — either self-elected or with technology automation. With semantic word matching, we’re moving to a world where the information will find us, instead of the other way around. True “passive” search.

Dave Copps is the founder and CEO of PureDiscovery. He has been involved in intelligent document retrieval since 1992. Dave previously co-founded Engenium Corp., the first commercial application of latent semantic analysis, in 1999.