Questions tagged [knowledge-graph]
For questions related to the concept of a knowledge graph, which is a knowledge base represented as a graph that accumulates and conveys knowledge of the real world, where nodes represent entities and edges represent relations between those entities.
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Convert specific domain knowledge text to a knowledge graph
As part of this semester assignment , I'm working on a project that aims to to represent the knowledge in "PMBOK 6th edition, section 11: Project Risk Management (page 395 -> 458)" and the knowledge ...
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Does ChatGPT imply that the direction of knowledge graph is unpromising?
In this question I asked about the role of knowledge graphs in the future, and in this answer I found that If curation and annotation are not sufficient, the knowledge base maybe cannot apply in AI.
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Are there methods which represent entire knowledge graphs in one embedding vector?
In a knowledge graph, embedding vectors can be learned for nodes (node embedding) and edges (edge embeddings). Is there a method to learn one single embedding vector for the entire knowledge graph?
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What are other types of knowledge bases except entity-entric KB?
I learned a term entity-centric knowledge base, then I wonder what the non entity-centric knowledge graphs are?
I googled by keys words "entity-centric knowledge base vs" and got some ...
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Knowledge graph progress from 2012 to 2022?
I watched this lecture by professor Xin Wang, and a picture in the beginning interested me:
The confusing thing is that this lecture was delivered on Sep. 19, 2022, but it seems from the diagram ...
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How to model graph node as priority list over a visual scene in neuro-symbolic AI?
Suppose if we have a visual scene graph and we model each component in the scene as a node of a graph and edges which are relationship between the visual scene components. Some of the nodes are like ...
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What are knowledge graph embeddings?
What are knowledge graph embeddings? How are they useful? Are there any extensive reviews on the subject to know all the details? Note that I am asking this question just to give a quick overview of ...
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Is graph embedding linear in its maintaining of graph geometry?
It is claimed that the main goal of graph embedding methods is to pack every node's properties into a vector with a smaller dimension, so node similarity in the original complex irregular spaces can ...
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What are the differences between a knowledge base and a knowledge graph?
During my readings, I have seen many authors using the two terms interchangeably, i.e. as if they refer to the same thing. However, we all know about Google's first quotation of "knowledge graph&...
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What is meant by the rank of the scoring function here?
I've been reading the paper Reinforcement Knowledge Graph Reasoning for Explainable Recommendation (by Yikun Xian et al.) lately, and I don't understand a particular section:
Specifically, the ...
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Why can't pure KG embedding methods discover multi-hop relations paths?
According to Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
pure KG embedding methods lack the ability to discover multi-hop relational paths.
Why is it so?
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Which reward function works for recommendation systems using knowledge graphs?
I've been reading this paper on recommendation systems using reinforcement learning (RL) and knowledge graphs (KGs).
To give some background, the graph has several (finitely many) entities, of which ...
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What are multi-hop relational paths?
What are multi-hop relational paths in the context of knowledge graphs (KGs)?
I tried looking it up online, but didn't find a simple explanation.
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