Dialogue with Amit Sheth
Dialogue with Amit Sheth
Thoughts on the development and future of the web, machine learning, and how to improve relational connection.
Teodora Petkova asks probing questions.
_(a) we can scalably create and maintain ontologies (what we also called WorldModel and roughly the same as what many refer to as a knowledge graph today) in a largely automated manner by assimilating structured data and knowledge from multiple sources;
(b) we can use these ontologies/knowledge graph in conjunction with lexical/linguistic techniques and machine learning for better information extraction, semantic annotation, and semantic enrichment; and
(c) we can build rich semantic applications, including semantic search/browsing/personalization/advertisement which also encompasses an associated dynamically-built rich media reference object (what some today call an information box but with relevant information and knowledge from an ontology/knowledge graph and other related context)._
#webhistory #conceptualrelationship #contextualrelationship
#dataandthought #machinelearning
Originally shared by Teodora Petkova
From processing big data to processing human experience in a meaningful way
I am honoured, thrilled and truly excited to get to share this Dialogue with Dr. Amit Sheth where he was kind and patient enough to answer all my questions about the semantic web, the cognition and understanding processes, the semantic web technologies applications and many more.
I also got to asking things like:
* What is most hard for algorithms to mimic when it comes to cognition
* What do machines have to do with collective intelligence?
* What is your favourite paradox in computing
:)
Enjoy the Dialogue and and let’s keep walking the semantic web talk.
http://www.teodorapetkova.com/dialogues/a-dialogue-with-dr-amit-sheth/
Thoughts on the development and future of the web, machine learning, and how to improve relational connection.
Teodora Petkova asks probing questions.
_(a) we can scalably create and maintain ontologies (what we also called WorldModel and roughly the same as what many refer to as a knowledge graph today) in a largely automated manner by assimilating structured data and knowledge from multiple sources;
(b) we can use these ontologies/knowledge graph in conjunction with lexical/linguistic techniques and machine learning for better information extraction, semantic annotation, and semantic enrichment; and
(c) we can build rich semantic applications, including semantic search/browsing/personalization/advertisement which also encompasses an associated dynamically-built rich media reference object (what some today call an information box but with relevant information and knowledge from an ontology/knowledge graph and other related context)._
#webhistory #conceptualrelationship #contextualrelationship
#dataandthought #machinelearning
Originally shared by Teodora Petkova
From processing big data to processing human experience in a meaningful way
I am honoured, thrilled and truly excited to get to share this Dialogue with Dr. Amit Sheth where he was kind and patient enough to answer all my questions about the semantic web, the cognition and understanding processes, the semantic web technologies applications and many more.
I also got to asking things like:
* What is most hard for algorithms to mimic when it comes to cognition
* What do machines have to do with collective intelligence?
* What is your favourite paradox in computing
:)
Enjoy the Dialogue and and let’s keep walking the semantic web talk.
http://www.teodorapetkova.com/dialogues/a-dialogue-with-dr-amit-sheth/
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