Knowledge Graph (KG) is one of the important branches of knowledge engineering. It structurally describes concepts and their relationships in the physical world in symbolic form.
From its emergence to the present, knowledge graphs have spawned many independent research directions, and have played an irreplaceable and important role in many practical engineering projects and large-scale systems.
Today, knowledge graphs have become an increasingly popular research direction in cognition and artificial intelligence, and are highly valued by academia and industry.
This time I compiled 130 pages of knowledge graph review papers + 152 + knowledge graph papers + 2 sections of "Knowledge Graph---Research, Overview and Future Application Scenarios" explained by top experts (including 52 pages of courseware) , which is systematic Sorting out the knowledge map is worth collecting.
Scan the QR code to reply to "Knowledge Graph"
Get a 130-page pdf review + a collection of 152 papers + 2 courses
Overview introduction
The review is a "Knowledge Graph" review paper co-written by 18 scholars, which describes the methods of creating, enriching, quality assessment, refinement and publishing of knowledge graphs. It has 130 pages of pdf.
This comprehensive introduction to knowledge graphs: describes their basic data model and how to query them; discusses representations related to schema, identity, and context; introduces the various techniques that can be used to create and enrich graph-structured data; and provides insights into practice An overview of existing knowledge graphs.
Scan the QR code to reply to "Knowledge Graph"
Get the 130-page pdf review summary
paper
And I also compiled a collection of 152 knowledge graph papers (including classic papers, CCF2023, AAAI2023 knowledge graph papers), all in pdf format, which is very convenient.
Scan the QR code to reply to "Knowledge Graph"
Get a 130-page pdf review + a collection of 152 knowledge graph papers
Course content
In addition, I also specially invited two top experts to give you two sessions of "Knowledge Graph Research, Overview and Future Application Scenarios" , which lasted 2 hours and were full of useful information.
0.01 unlocks 2 sections "Knowledge Graph Research, Overview and Future Application Scenarios"
Get a 130-page pdf review + a collection of 152 knowledge map papers + a 52-page courseware
The first course: Basic research and future applications of knowledge graph and multi-modal technology
1. Background and Application
• Definition
• Application Scenarios
2. Classification of knowledge graph
• Classification by scene
• Classification by time
3. Knowledge graph construction
• Where does knowledge come from?
• Knowledge graph completion
4. Knowledge Representation Learning
• How is knowledge known by the computer?
5. Graph API Service
• API Service
6. Summary and learning path
Lesson 2: Overview of knowledge graph and application scenarios (live broadcast at 20:00 on September 26th)
1. Basic research on knowledge graphs
2. Basic research on multimodality
3. Future research and application of large models and knowledge graphs
4. Future direction
0.01 unlocks 2 sections "Knowledge Graph Research, Overview and Future Application Scenarios"
Get a 130-page pdf review + a collection of 152 knowledge map papers + a 52-page courseware
