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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1answer
72 views

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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1answer
97 views

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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1answer
52 views

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 ...
2
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1answer
80 views

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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0answers
16 views

knowledge data base or model for "terms" containment

I'm looking for an open source database/model that can tell me whether there's a relationship of containment between two general "terms", i.e "dresses" is contained within "...
3
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2answers
1k views

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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0answers
18 views

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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0answers
31 views

Sparse Multi-hot encoding and autoencoders

I'm working with graph neural networks. I have a large graph. Each node has 4 features [A,B,C,D]: 2 categorical with high cardinality: 86k (A) and 148k (B) different features 2 integer with ranges: [...
1
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1answer
68 views

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.