knowledge representation

DataFunTalk

Jul 17, 2024 · Databases

From DIKW to Distributed Data Warebase: Letting Data Emerge as Intelligence

This article explores the DIKW hierarchy, explains how data evolves into information, knowledge, and wisdom, examines traditional data models and products, critiques existing multi‑system architectures, and proposes a new distributed Data Warebase that unifies structured, semi‑structured, and vectorized knowledge to enable intelligent data-driven applications.

Artificial IntelligenceDIKWData Systems

0 likes · 24 min read

From DIKW to Distributed Data Warebase: Letting Data Emerge as Intelligence

DataFunTalk

Sep 8, 2023 · Artificial Intelligence

Knowledge Processing in the Era of Large Models: New Opportunities and New Challenges

This article examines how large language models and knowledge graphs complement each other, discussing their respective strengths, integration techniques such as prompt engineering and knowledge editing, and outlining future research directions for building large knowledge models that combine linguistic understanding with structured knowledge representation.

AIKnowledge GraphsModel alignment

0 likes · 27 min read

Knowledge Processing in the Era of Large Models: New Opportunities and New Challenges

DataFunTalk

Aug 11, 2022 · Databases

Fundamentals of Knowledge Graphs, Graph Databases, and Their Applications in AI and Big Data

This article introduces the basic concepts of knowledge graphs, explores their research dimensions across knowledge engineering, natural language processing, databases and machine learning, discusses graph database storage models and their integration with artificial intelligence and big data, and presents related projects and real‑world case studies.

Artificial IntelligenceRDFbig data

0 likes · 13 min read

Fundamentals of Knowledge Graphs, Graph Databases, and Their Applications in AI and Big Data

DataFunTalk

May 15, 2021 · Artificial Intelligence

Knowledge Graph Course Syllabus Overview

This teaching plan outlines a comprehensive Knowledge Graph course covering fundamentals, representation, storage, extraction, reasoning, fusion, question answering, graph algorithms, and emerging technologies across nine detailed chapters, including language integration, ontology matching, and multimodal extensions.

Artificial Intelligencecourse syllabusfusion

0 likes · 4 min read

Knowledge Graph Course Syllabus Overview

Architecture Digest

May 13, 2019 · Artificial Intelligence

Enterprise Knowledge Graphs: Development Trends, Use Cases, Database Selection, and Implementation Practices

This article outlines the evolution of knowledge graphs, describes typical enterprise application scenarios, compares graph database options such as Neo4j, Cayley and Dgraph, and presents a six‑step methodology for building, storing, and applying knowledge graphs in large‑scale business environments.

Enterprise AISemantic Searchdata integration

0 likes · 13 min read

Enterprise Knowledge Graphs: Development Trends, Use Cases, Database Selection, and Implementation Practices

Qunar Tech Salon

Nov 29, 2015 · Artificial Intelligence

From Symbolic Semantics to Vector Representations: Deep Learning for Natural Language Understanding

The article reviews symbolic knowledge bases such as WordNet, ConceptNet and FrameNet, explains how deep learning replaces them with vector‑based semantic representations, and discusses encoder‑decoder RNNs, attention mechanisms, and future directions for truly understanding language through experiential learning.

Deep LearningNatural Language ProcessingRNN

0 likes · 12 min read

From Symbolic Semantics to Vector Representations: Deep Learning for Natural Language Understanding