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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

Labeling, indexing, ease of discovery, and ease of access are essential if end-users are to find and benefit from the collection. My favorite approach to TAM creation and to modern data management in general is AI and machine learning (ML). Tagging and annotating those subcomponents and subsets (i.e.,

Strategy 266
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KDD 2020 Opens Call for Papers

Data Science 101

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). KDD 2020 welcomes submissions on all aspects of knowledge discovery and data mining, from theoretical research on emerging topics to papers describing the design and implementation of systems for practical tasks. 1989 to be exact. 22-27, 2020.

KDD 81
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GraphDB in Action: Navigating Knowledge About Living Spaces, Cyber-physical Environments and Skies 

Ontotext

Buildings That Almost Think For Themselves About Their Occupants The first paper we are very excited to talk about is Knowledge Discovery Approach to Understand Occupant Experience in Cross-Domain Semantic Digital Twins by Alex Donkers, Bauke de Vries and Dujuan Yang.

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KDD 2020 Call for Research, Applied Data Science Papers

KDnuggets

ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26 th Annual Conference in San Diego.

KDD 48
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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

Lance Paine, founder of Semantic Partners, took the ball from Sumit to talk about “why you’re not ready for knowledge graphs”. He outlined the challenges of working effectively with AI and machine learning, where knowledge graphs are a differentiator.

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Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Several factors are driving the adoption of knowledge graphs. Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs.

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Fundamentals of Data Mining

Data Science 101

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining. He possesses great interest in machine learning, astronomy and history.