Overview of Machine Learning for Knowledge Graphs | AISC

Published on ● Video Link: https://www.youtube.com/watch?v=fCrG8pNZxrE



Duration: 53:43
2,278 views
48


For slides and more information on the paper, visit https://ai.science/e/overview-of-machine-learning-for-knowledge-graphs--KHft50zEJrtt5SrFwqOa

Speaker: Nausheen Fatma; Discussion Facilitator: Xiyang Chen, Nabila Abraham

Motivation:
This session will give an overview of machine learning in knowledge graph, areas of applications and current state of the art methods. We will mainly draw materials from two overview papers: A Survey on Knowledge Graphs: Representation, Acquisition and Applications by Ji et al and Knowledge Graphs by Hogan et al, both published in 2020.




Other Videos By LLMs Explained - Aggregate Intellect - AI.SCIENCE


2020-10-13Some Salient Issues with Saliency Models | AISC
2020-10-13The Messy Side of AI Products | AISC
2020-10-09Human Aware AI: Reducing Transportation Energy of a City by Influencing Individual Behaviour
2020-10-08Policy Priority Inference: Simulations for Government Strategy | AISC
2020-10-07Inferring the 3D Standing Spine Posture from 2D Radiographs | AISC
2020-10-06Knowledge Extraction from Multimodal & Multilingual sources | AISC
2020-10-01Camera Depth of Field Manipulation for Pre- and Post-Image Capture | AISC
2020-09-30[MOREL] Unsupervised Video Object Segmentation for Deep Reinforcement Learning
2020-09-29Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial | AISC
2020-09-29Overview: Machine Learning for Quantum Matter Research | AISC
2020-09-25Overview of Machine Learning for Knowledge Graphs | AISC
2020-09-24Integrating Physics into Machine Learning Models for Scientific Discovery | AISC
2020-09-24Applications of Blockchain to IoT Security | AISC
2020-09-24Human-Technology Systems for Intelligent Civil Infrastructure Operation and Maintenance | AISC
2020-09-23The AI Design Sprint -- setting your AI Initiative up for delivery success! | AISC
2020-09-23explainX - Explainable AI for model developers | AISC
2020-09-22Statistical Issues in Agent-Based Models | AISC
2020-09-22Layerwise Learning for Quantum Neural Networks | AISC
2020-09-17Survival regression with AFT model in XGBoost | AISC
2020-09-17Detecting Off-Topic Spoken Response with NLP | AISC
2020-09-16Defining your AI Value Model for Product Success (and Profit) | AISC