James Phare’s Post

Semantic modeling and synchronicity How to approach building semantic knowledge models? Where do you start when you want to build an ontology? Equally good questions, asked by many of us. In a twist of synchronicity, these exact questions have also been asked by two members of the Connected Data London team indepndently of each other, with just a few hours difference. As Jérémy Ravenel relates, starting from the top isn’t usually the best idea. Like in many things, if you want to build something grounded, you’ve got to work bottom up. Top-down is good for conceptualizing but nothing beats the deep analysis of the data you’ve got. For Veronika Heimsbakk, it's a virtuous circle. Identify scope, information sources, timeframe and milestones. Ask Competency Questions. Draw initial concepts. Start your own modeling process. Consider established ontologies. Discover the need for axioms and/or constraints. Populate. Rinse. Repeat. Jérémy and Veronika will be sharing their data modeling experience with the world on December 11-13 in Connected Data London. Join them and the rest of our lineup which we'll be revealing in full shortly. Until we do, benefit from Early Bird ticket price! https://lnkd.in/d7nMP9sH Link to Jérémy's and Veronika's posts in the comments #KnowledgeGraphs #DataModeling #DataScience #SemTech #EmergingTech #FOMO

#KNIME is coming to Washington, D.C. later this month for the #Geospatial Symposium that will take place on July 23 - 24. 🌍 🤓 One day earlier, we'll be co-throwing a #DataConnect event in Arlington, along with Dr. Mengxi Zhang, in which we will discuss and show how to enrich #datanalytics with #GenAI, and how to leverage geospatial analytics in KNIME. ⬇ Check the link below to learn more about this event! Oh! And before I forget! If you are a geospatial researcher, and interested in #lowcode, don't miss out on the paper that we co-authored with Harvard University researchers Lingbo Liu, Xiaokang Fu, and Wendy Guan ➡ https://lnkd.in/eE9c_rCh https://lnkd.in/ev67uUrB

Hi All, Please provide your valuable inputs to this post by Sahil Garg!

Evolution of Graph Algorithms: Benefits and Challenges Graphs are the most native format to represent data, they have the built-in structure to store the contextual information and enable data analysts to get better answers for their queries, data engineers to easily extend their ecosystem, and data scientists to build enhanced models. With Graphs, we can make better-informed decisions. In this presentation, you will learn about the evolution of Graphs with a review on knowledge graphs, path-finding, clustering, and recommendation algorithms, how they are built, and their use cases. Also, we will review the challenges we face as processing more data comes with a cost, and how they are solved in different faces of the machine learning lifecycle. Join us for a 1-hour tour of Graph. Key Topics * Historical timeline of Graph * The use cases for multiple industries * Knowledge graphs, path-finding algorithms, clustering, and recommendation algorithms * Graph Neural Networks * The challenges with GNNs, sampling, calculating loss functions, embeddings. #Analytics #DataScience #AI #MachineLearning #FlashbackFriday https://lnkd.in/dK9VskTD Speaker: Ebru Cucen: Data Consultant | Mentor / Coach, Graph Aware | OpenCredo Ebru has a passion for Machine Learning and she is on a mission to make Graph Machine Learning easy to be understood and accessible by everyone, and to share the implementations in different fields. She is the author of the book "Connecting the Dots: Harness the Power of Graphs & ML". Building on her BSc in Mathematics, Ebru has over 20 years of experience with a wide perspective in multiple business domains, including Finance, Environmental, Social, and Governance (ESG), Pharma, Retail, and Transportation. Hands-on, she has been involved in the end-to-end design, building and delivery of scalable fault-tolerant cloud-native solutions. With a more recent focus on data engineering, graphs and ML/AI, she looks to combine the best of both worlds - gaining new and fresh insights, delivered through stable, reliable solutions. --- Connected Data London 2024 has been announced! December 11-13, etc Venues St. Paul’s, City of London If you liked this video, check #CDL24 for more Presentations, Keynotes, Masterclasses, and Workshops on cutting-edge topics from industry leaders and innovators: https://lnkd.in/dQUzWtex

A standards-based knowledge graph shares data across systems in a trusted way, via a data model that's logically consistent from upper ontology, to domain ontology, to domain object

🌟 Excited to share our latest blog post on "GuideWalk - Heterogeneous Data Fusion for Enhanced Learning - A Multiclass Document Classification Case" 🌟 In this post, we delve into the prime challenge of efficiently extracting information from large-scale, heterogeneous data, focusing specifically on text data and its exceptional place among diverse data types. The blog covers a new embedding method based on the graph structure of meaningful sentences, aiming to construct an embedding vector that encapsulates syntactic, semantic, and hidden content elements. The proposed method's success is tested in classification problems, particularly in text classification, showcasing significantly better results compared to well-known algorithms. Read the full post on arXiv at: https://bit.ly/3Wo0GDk #MachineLearning #DataFusion #TextClassification #DataScience #InformationExtraction

Overwhelmed by your #backup data? Great news! #Cohesity Gaia has a new visual explorer feature that can instantly identify hidden thematic structures across your backup. With these themes, you can ask more informed and targeted questions, gathering hidden insights you need to get your job done.

Overwhelmed by your #backup data? Great news! #Cohesity Gaia has a new visual explorer feature that can instantly identify hidden thematic structures across your backup. With these themes, you can ask more informed and targeted questions, gathering hidden insights you need to get your job done.

Overwhelmed by your #backup data? Great news! #Cohesity Gaia has a new visual explorer feature that can instantly identify hidden thematic structures across your backup. With these themes, you can ask more informed and targeted questions, gathering hidden insights you need to get your job done.

Overwhelmed by your #backup data? Great news! #Cohesity Gaia has a new visual explorer feature that can instantly identify hidden thematic structures across your backup. With these themes, you can ask more informed and targeted questions, gathering hidden insights you need to get your job done.