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Final Week - Ticket Specials!
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Masterclass + Conference Bundle:


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Join Us to Hear From These Awesome Speakers:
  • Amit Weitzner from Timbr AI
    Kirell Benzi
    from Kirelion
  • Mayank Kejriwal from USC Center for Knowledge Graphs
  • Mark Grover from Lyft / Amundsen.io
  • Eran Avidan from Intel
  • Paco Nathan from Derwen Ai
  • François Scharffe from KGC and The Data Chefs
  • Nathan Benaich from Air Street Capital
  • Panos Alexopoulos from TextKernel
  • Gary Marcus from Robust AI
  • Dan McCreary from Optum
  • Michael Atkin from The Enterprise Knowledge Graph Foundation
  • Teresa Tung from Accenture
  • Steven Gustafson from Noonum
  • Isabelle Augenstein from University of Copenhagen
  • Fabio Petroni from Facebook AI Research
  • Giuseppe Futia from Politecnico di Torino
  • Ben Gardner from AstraZeneca
  • Andrea Volpini from Wordlift
  • Amit Weitzner from Timbr.ai (Gold sponsor)
  • Kendall Clark from Stardog (Diamond sponsor)
  • Dave Duggal at Enterprise Web (Gold sponsor)
  • David Amerland, best-selling author of SEO Help 
  • Dawn Anderson from Bertey
  • Hamlet Batista from RankSense
  • Jason Barnard from KaliKube
  • Tom Plasterer from AstraZeneca
  • Katariina Kari from Zolando
  • Laurent Alquier from Johnson & Johnson
  • Veronika Heimsbakk from CapGemini
  • Michiel Hildebrand from Spinque
Workshops & Masterclasses
  • Executive Roundtable: Knowledge Graph Adoption in the Enterprise
  • KG 101: Hands-on Coding in Python
  • AI + Knowledge - A Match Made in Heaven?
  • From Databases to Platforms: The Evolution of Graph Databases
  • Flawless Semantic Modeling in OWL and SKOS: Theory and Practice
  • Knowledge Graphs and SEO: The Next Chapter
  • From Knowledge graphs to AI-powered SEO: Theory and Practice
  • Validating Semantic Knowledge Graphs using SHACL
Workshop: Knowledge Graph Adoption in the Enterprise
with Michael Atkin, Teresa Tung, Laurent Alquier, Thomas Deely, Ben Gardner, Steven Gustafson, Tom Plasterer
Limited Availability Only

Are you trying to figure out personalization, customer insights, fraud detection, knowledge management, regulatory reporting, digital transformation or other business problems which involve understanding multiple data sets? 

Join our executive roundtable on enterprise graph adoption on Nov 30th. Featuring two panels with breakouts and networking with fellow executives over 2 hours: covering business problems and implementation challenges with Michael Atkin, Tom Plasterer, Stephen Gustafson, Teresa Tung, Laurent Alquier, Ben Gardner and more.  Leave with valuable insights which you can apply to your work and share with your colleagues.

Masterclass: KG 101 with Paco Nathan & Francois Scharffe
Have you ever wanted to build a knowledge graph? François Scharffe and Paco Nathan present a 2-hour hands-on tutorial during #KnowCon2020, based on open source libraries – if you can write 20 lines of Python, you have the prerequisites. 

Core topics include using namespaces and controlled vocabularies to construct a graph, serialization in both JSON-LD and N3 triples, running SPARQL queries in #rdflib, graph algorithms in #networkx, and graph visualization in #pyvis.

We’ll show use of related natural language libraries and tools to extend and enrich graphs, and also discuss engineering trade-offs throughout the course. Coding examples are based on a new open source Python library with classes and utilities for managing knowledge graphs, which hopefully can serve as starting points for your use case implementations.

Masterclass: AI + Knowledge - a match made in heaven?

with Nathan Beinach, Isabelle Augenstein, Katariina Kari, Fabio Petroni, and Giuseppe Futia.

What does graph have to do with machine learning? A lot, actually--and it goes both ways.

The information contained in graphs can boost the efficiency of machine learning approaches, and machine learning, in turn, can help bootstrap and populate knowledge graphs.

Amazon, Alibaba, Apple and Twitter are just some of the organizations using this in production, and advancing the state of the art. Already, more than 20% of the research published in top AI conferences is graph-related.

Join the 2-hour “AI + Knowledge - a match made in heaven?” workshop at #KnowCon2020 to explore the intersection of graph + ML through expert discussion and audience Q&A and interaction. 

Learn what types of problems that can be addressed with these techniques, where they can be used in production, and what is state-of-the-art practice. We’ll also dive into major roadblocks / goals, strategies for addressing them, potential outcomes, and key players. 

Masterclass: Knowledge Graphs and SEO: The next chapter
with Andrea Volpini, Dawn Anderson, David Amerland, Jason Barnard, and Hamlet Batista.

Interested to develop a long-tail SEO strategy, and scale traffic on an enterprise website with a schema.org knowledge graph? Join Andrea Volpini on Dec 1 at #KnowCon2020 for a 2-hour lecture-based workshop on semantic SEO, structured linked data, and NLP/NLG (natural language generation). This workshop is designed for marketers, SEOs, content creators, information architects, and data scientists who are interested to understand and leverage modern SEO strategies. 

For hands-on practice, you’ll also want to check out Andrea’s follow-up masterclass on Dec 2. Participants will form small teams to work run a "search intent investigation" using Python against and the knowledge graph of a reference website. Each team will then use NLP to highlight new untapped search opportunities, and see how to reverse-engineer the results of Google Search for a given query. Lastly, teams will assemble a web page in WordPress to attract traffic, using machine-generated content created using Google's T5 Text-to-Text Transfer Transformer Model.  

Workshop: Semantic Data Modeling
with Panos Alexopoulos

Join Panos Alexopoulos on Dec 1 for a masterclass introduction to semantic data modeling, focused on avoiding bad practices while developing ontologies, taxonomies and knowledge graphs. Learn how to design conceptual models that are machine interpretable right from the beginning. Some knowledge of OWL/SKOS are desirable, but not essential.

For those who do have familiarity OWL/SKOS, check out Panos’ follow-up masterclass on Dec 2. This will include guided practice of modeling in Protege, and will cover such topics as: when to use SKOS and when OWL, how to properly model subclasses, parts and other semantic relations, how to make and document modeling decisions, how to deal with vagueness, and more. These exercises are designed to challenge conventional wisdom and sharpen your semantic modeling skills.
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