# Tag Info

Accepted

### What are knowledge graph embeddings?

Knowledge graph embeddings (KGE) are embeddings created in the context of a knowledge graph (KG), which can be viewed as a visual/graphical representation of a knowledge base, where nodes are entities ...
• 35k
Accepted

### Which reward function works for recommendation systems using knowledge graphs?

I found the answer further into the paper (section 3.2 Formulation as Markov Decision Process)! I'll post it here for everyone. Given any user, there is no pre-known targeted item in the KGRE-Rec ...
• 1,011
1 vote
Accepted

### What are multi-hop relational paths?

Before trying to explain this term in your context, let me briefly describe the term in other contexts. In computer networking, the term "hop" refers to a node (e.g. a router) that a packet goes ...
• 35k
1 vote

### What are the differences between a knowledge base and a knowledge graph?

What is a knowledge graph? Appendix A.3 "Knowledge Graphs": 2012 Onwards of the survey Knowledge Graphs (which is probably the most extensive survey on KGs) states that knowledge graphs have ...
• 35k
1 vote

### What are the differences between a knowledge base and a knowledge graph?

Based on the related Wikipedia, a knowledge base (KB) is: a technology used to store complex structured and unstructured information used by a computer system. The initial use of the term was in ...
• 1,683
1 vote
Accepted

### What is meant by the rank of the scoring function here?

$\text{rank}(f((r,e)|u))$ in $A_t(u)$ means to compute the value of scoring function $f$ for all pairs $(r,e)\in A_t$ which are conditioned by $u$, then sort them in a descending order. The rank of ...
• 1,683
1 vote
Accepted

### Why can't pure KG embedding methods discover multi-hop relations paths?

To put this insert to context, we should take at least this much of text from the paper: One line of research focuses on making recommendations using knowledge graph embedding models, such as ...
• 927

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