Today's episode is a break from our normal flow, and a tribute to a great person and a legendary SEO
In Knowledge Connexions 2020, we had the honor and the privilege of hosting Hamlet Batista, alongside Dawn Anderson, David Amerland, Jason Barnard, and Andrea Volpini
This great group of people shared their insights on "Knowledge Graphs and SEO: The next chapter"
It is with deep sadness that we have learned that Hamlet Batista passed away in January 2021
Though our encounter was brief, we can only attest to the opinions of everyone who knew him: Hamlet was deeply knowledgeable and a pleasure to work with.
We share the insights of this panel on the interplay between semantic technology, SEO, and knowledge graphs with the community, as a tribute to Hamlet Batista's memory
---- Workshop Description ---
A talk by Dawn Anderson (Bertey), David Amerland (Davidamerland.com), Jason Barnard (Kalicube), Hamlet Batista (RankSense) & Andrea Volpini (Wordlift).
“Knowledge Graph” is an overloaded term.
Today Knowledge Graphs are becoming mainstream, and as this happens, more and more people associate Knowledge Graphs with data models, semantics, knowledge management, and ontologies
For many other people, however, Knowledge Graphs still mean Google Search Info Boxes, panels, SERPs, and SEO (Search Engine Optimization).
They are all right.
The term Knowledge Graph was introduced by Google to signify the huge improvement that semantic technology brought to its search engine.
Over time, the extended search capabilities and components enabled by semantic technology have become namesakes for Knowledge Graph.
While the term Knowledge Graph has more meanings than this, it’s useful to return to the source.
The evolution of Knowledge Graph-powered Google search now extends to voice, assimilates information from JSON-LD markup beyond Wikipedia, and advances the state of the art in NLP (Natural Language Processing).
Let’s explore how this influences, and is influenced by, advances in semantic technology, where the evolution of SEO is headed, and what this means for knowledge graphs at large.
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