knowledge graph

DevOps

Jun 16, 2025 · Artificial Intelligence

Unlock AI’s Real‑World Power: 6 Must‑Have MCP Tools with Hands‑On Code

This article reviews six open‑source MCP servers—Bright Data, Graphiti, GitIngest, Terminal, Code Executor, and MindsDB—showing how each extends large language models with web scraping, long‑term memory, code navigation, command‑line control, sandboxed Python execution, and multi‑source data integration, complete with practical code examples.

AI toolsMCPcode execution

0 likes · 9 min read

Unlock AI’s Real‑World Power: 6 Must‑Have MCP Tools with Hands‑On Code

Sohu Tech Products

Jun 11, 2025 · Artificial Intelligence

How DeepSeek and TiDB AI Are Redefining Data Engines for the Large‑Model Era

This article explores DeepSeek's open‑source large‑model breakthroughs, PingCAP's AI‑enhanced database roadmap, TiDB.AI's retrieval‑augmented generation framework, the unified TiDB data engine, and practical Q&A insights on knowledge‑graph construction, vector search, and AI‑driven SQL generation.

AIDeepSeekRAG

0 likes · 15 min read

How DeepSeek and TiDB AI Are Redefining Data Engines for the Large‑Model Era

DataFunSummit

Jun 2, 2025 · Artificial Intelligence

Enterprise Knowledge Brain Powered by Large Models and Knowledge Graphs

This article explains how the rapid development of large language models and knowledge graph technologies creates new opportunities for enterprise knowledge management, outlines the challenges of massive unstructured data, describes the architecture and core data flow of a corporate knowledge brain, and showcases key technologies and real‑world applications.

AI architectureLarge Modelsdata integration

0 likes · 13 min read

Enterprise Knowledge Brain Powered by Large Models and Knowledge Graphs

DataFunSummit

May 17, 2025 · Artificial Intelligence

Integrating Knowledge Graphs with DeepSeek AI for Enterprise Knowledge Management

This presentation explores how combining knowledge graphs with DeepSeek large‑model agents can revolutionize enterprise knowledge management, detailing DeepSeek’s technical strengths, the graph‑model complementarity paradigm, various knowledge types, practical frameworks, case studies, and future outlooks for AI‑enhanced intelligent systems.

Artificial IntelligenceDeepSeekEnterprise Knowledge Management

0 likes · 23 min read

Integrating Knowledge Graphs with DeepSeek AI for Enterprise Knowledge Management

DataFunSummit

May 13, 2025 · Artificial Intelligence

Integrating Large Language Models and Knowledge Graphs for Financial Applications: Challenges, Solutions, and Future Directions

This talk explores the technical challenges of applying large language models and knowledge graphs in finance, discusses solutions such as RAG enhancements, graph‑guided retrieval, multimodal extensions, and presents future research directions including multimodal graph integration, agentic systems, and decision‑making applications.

AIAgentic SystemsFinance

0 likes · 33 min read

Integrating Large Language Models and Knowledge Graphs for Financial Applications: Challenges, Solutions, and Future Directions

AntTech

May 6, 2025 · Information Security

Security Risk Detection for HarmonyOS ArkTS Code: Architecture, Analysis Framework, and Future Directions

This article presents a comprehensive overview of the security challenges in HarmonyOS native ArkTS applications and describes the design and implementation of a specialized static analysis framework—including source extraction, data‑flow and inter‑function analysis, knowledge‑graph construction, and risk inference engine—while also outlining integration into development pipelines and future research directions.

ArkTSSecurityStatic Analysis

0 likes · 17 min read

Security Risk Detection for HarmonyOS ArkTS Code: Architecture, Analysis Framework, and Future Directions

DataFunSummit

Apr 21, 2025 · Artificial Intelligence

Deep Integration of Knowledge Graphs and Large Language Models: Methods, Applications, and Future Directions

This article explores how knowledge graphs can be tightly integrated with large language models through prompt engineering, fine‑tuning, retrieval‑augmented generation, reasoning collaboration, and knowledge agents, outlining technical pathways, practical implementations, and future research directions across AI domains.

AIRetrieval-Augmented Generationknowledge graph

0 likes · 23 min read

Deep Integration of Knowledge Graphs and Large Language Models: Methods, Applications, and Future Directions

DevOps

Apr 20, 2025 · Artificial Intelligence

Building a Medical Knowledge Base with RAG: A Step‑by‑Step Example

This article demonstrates how to construct an AI‑powered medical knowledge base for diabetes treatment by preprocessing literature, performing semantic chunking, generating BioBERT embeddings, storing them in a FAISS vector database, and using a RAG framework together with a knowledge graph to retrieve and generate accurate answers.

BioBERTMedical AIRAG

0 likes · 12 min read

Building a Medical Knowledge Base with RAG: A Step‑by‑Step Example

AntTech

Feb 27, 2025 · Artificial Intelligence

Entity Contrastive Learning via Multi-Token Parallel Prediction for Knowledge Graph Completion

Researchers from Ant Group and Zhejiang University propose K-ON, a multi-token parallel prediction method that enables large language models to perceive knowledge graph entities through entity-level contrastive learning, achieving superior performance, lower cost, and higher efficiency on KG completion benchmarks.

AI researchK-ONMulti-Token Prediction

0 likes · 8 min read

Entity Contrastive Learning via Multi-Token Parallel Prediction for Knowledge Graph Completion

AntTech

Feb 26, 2025 · Artificial Intelligence

Ant Group’s 18 Accepted Papers at AAAI 2025: Summaries and Highlights

This article presents concise English summaries of the 18 Ant Group papers accepted at AAAI 2025, covering topics such as privacy‑preserving large‑model tuning, knowledge‑graph integration, AI‑generated image detection, multi‑task learning, generative retrieval, role‑playing evaluation, and video hallucination mitigation.

AAAI 2025AI evaluationVideo Hallucination

0 likes · 29 min read

Ant Group’s 18 Accepted Papers at AAAI 2025: Summaries and Highlights

DataFunSummit

Jan 30, 2025 · Databases

Mature Practices for Building Risk‑Control Knowledge Graphs on NebulaGraph and Leveraging Large Language Models

This article explains how NebulaGraph’s large‑scale graph database can be used to construct real‑time risk‑control knowledge graphs, describes practical applications such as community detection and path analysis, and explores how large language models enhance graph queries through Text‑to‑GQL, agents, exploration chains, and semi‑structured knowledge extraction.

AILLMNebulaGraph

0 likes · 11 min read

Mature Practices for Building Risk‑Control Knowledge Graphs on NebulaGraph and Leveraging Large Language Models

360 Tech Engineering

Nov 15, 2024 · Artificial Intelligence

Advances in Multimodal Large Models and Document Understanding Presented at the 2024 Global Machine Learning Conference (Beijing)

At the 2024 Global Machine Learning Conference in Beijing, 360 AI Research Institute showcased cutting‑edge multimodal large‑model research, fine‑grained open‑world object detection, and document understanding technologies, highlighting open‑source releases, real‑world deployments, and competitive achievements in AI competitions.

AI researchDocument UnderstandingLarge Models

0 likes · 7 min read

Advances in Multimodal Large Models and Document Understanding Presented at the 2024 Global Machine Learning Conference (Beijing)

AntTech

Nov 13, 2024 · Information Security

Ant Group’s Large‑Model‑Based Security Parallel Plane and Intelligent Threat Detection System

The article details Ant Group’s AI‑driven security parallel plane and intelligent threat detection system, its DKCF‑based architecture, key modules for data correlation, unknown threat discovery, alarm reduction, and knowledge‑graph integration, and its recognition in the 2024 AI Pioneer Case Collection.

AI securityAnt GroupDKCF

0 likes · 5 min read

Ant Group’s Large‑Model‑Based Security Parallel Plane and Intelligent Threat Detection System

DataFunSummit

Nov 9, 2024 · Artificial Intelligence

GraphRAG: Using Graph Structures to Enhance Retrieval‑Augmented Generation – Challenges, Methods, and Product Deployments

This article introduces GraphRAG, explains the limitations of traditional RAG, outlines four major challenges (fine‑grained retrieval, global context, similarity vs relevance, and macro‑level reasoning), describes GraphRAG’s graph‑based retrieval strategies, showcases comparative experiments, and presents NebulaGraph’s GenAI Suite and RAG products along with future research directions.

AIGraphRAGRetrieval-Augmented Generation

0 likes · 16 min read

GraphRAG: Using Graph Structures to Enhance Retrieval‑Augmented Generation – Challenges, Methods, and Product Deployments

DataFunSummit

Oct 25, 2024 · Artificial Intelligence

Progress and Standardization of Large Model + Data Intelligence Applications by the China Academy of Information and Communications Technology

This article reviews the China Academy of Information and Communications Technology's advancements in large‑model‑driven data intelligence, covering development trends, key deployment technologies such as prompt engineering, fine‑tuning and RAG, emerging application paradigms, challenges, and a series of newly drafted standards to guide industry adoption.

AIRAGStandardization

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Progress and Standardization of Large Model + Data Intelligence Applications by the China Academy of Information and Communications Technology

DataFunSummit

Oct 18, 2024 · Artificial Intelligence

Building Efficient RAG Applications with a Small Team: Insights from PingCAP AI Lab

This article details how PingCAP's three‑person AI Lab leveraged Retrieval‑Augmented Generation (RAG) techniques—including basic RAG, fine‑tuned embeddings, re‑ranking, graph RAG, and agent‑based RAG—to create scalable, multilingual document‑question answering services while addressing large‑scale documentation challenges, model limitations, and user feedback loops.

Fine-tuningLLMRAG

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Building Efficient RAG Applications with a Small Team: Insights from PingCAP AI Lab

JD Retail Technology

Oct 15, 2024 · Artificial Intelligence

Large‑Model‑Driven Evolution of E‑commerce Search and Recommendation at JD Retail

The article examines how large language models are reshaping JD Retail's e‑commerce search and recommendation pipelines, detailing industry evolution, technical challenges such as knowledge hallucination, intent understanding, personalization, cost, and safety, and presenting JD's end‑to‑end AIGC architecture, data preprocessing, alignment, evaluation, and next‑generation AI search solutions.

AILarge Modelse‑commerce

0 likes · 36 min read

Large‑Model‑Driven Evolution of E‑commerce Search and Recommendation at JD Retail

DataFunTalk

Oct 4, 2024 · Artificial Intelligence

Building a Commercial Intelligence Assistant with Baidu's Wenxin Large Model: Methods, Optimizations, and Future Outlook

This article shares the exploration and practice of using Baidu's Wenxin large model to build a commercial intelligence assistant, highlighting its impact on business revenue and user experience, code generation, knowledge graph integration, database query optimization, and visual analytics for enhanced data analysis.

AI for enterpriseBusiness IntelligenceSQL generation

0 likes · 17 min read

Building a Commercial Intelligence Assistant with Baidu's Wenxin Large Model: Methods, Optimizations, and Future Outlook

DataFunSummit

Sep 27, 2024 · Artificial Intelligence

Advances in Educational Large Language Models for Youth Programming and Personalized Learning

The presentation by Dr. Su Yu outlines challenges such as data sparsity and delayed learning effects in AI‑driven education, introduces three technical breakthroughs—domain‑specific LLM training, small‑knowledge learning via hierarchical knowledge graphs, and reinforcement‑based cognitive recommendation—and showcases product applications like the Frog Programming Platform, AI Programming Learning Machine, and digital‑human AI recorded courses.

AI Educationknowledge graphlarge language models

0 likes · 18 min read

Advances in Educational Large Language Models for Youth Programming and Personalized Learning

58 Tech

Sep 23, 2024 · Artificial Intelligence

Enhancing Commercial Search with Knowledge Graphs and Large‑Model Techniques

This article describes how a commercial search platform iteratively upgrades its system by structuring business knowledge into a knowledge graph, applying multi‑stage entity extraction (CRF, Electra‑CRF, GLM‑3, OCR), and leveraging large language models to improve relevance, user experience, and revenue.

AINLPcommercial search

0 likes · 14 min read