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Knowledge graphs: A practical review of the research landscape
Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …
Graph of thoughts: Solving elaborate problems with large language models
Abstract We introduce Graph of Thoughts (GoT): a framework that advances prompting
capabilities in large language models (LLMs) beyond those offered by paradigms such as …
capabilities in large language models (LLMs) beyond those offered by paradigms such as …
[HTML][HTML] Construction of knowledge graphs: Current state and challenges
With Knowledge Graphs (KGs) at the center of numerous applications such as recommender
systems and question-answering, the need for generalized pipelines to construct and …
systems and question-answering, the need for generalized pipelines to construct and …
Graph pattern matching in GQL and SQL/PGQ
As graph databases become widespread, the International Organization for Standardization
(ISO) and International Electrotechnical Commission (IEC) have approved a project to create …
(ISO) and International Electrotechnical Commission (IEC) have approved a project to create …
Sebs: A serverless benchmark suite for function-as-a-service computing
Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud
services, and serverless functions have immediately become a new middleware for building …
services, and serverless functions have immediately become a new middleware for building …
Pg-schema: Schemas for property graphs
Property graphs have reached a high level of maturity, witnessed by multiple robust graph
database systems as well as the ongoing ISO standardization effort aiming at creating a new …
database systems as well as the ongoing ISO standardization effort aiming at creating a new …
Sisa: Set-centric instruction set architecture for graph mining on processing-in-memory systems
Simple graph algorithms such as PageRank have been the target of numerous hardware
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …
Promoting knowledge elaboration, socially shared regulation, and group performance in collaborative learning: An automated assessment and feedback approach …
Online collaborative learning is implemented extensively in higher education. Nevertheless,
it remains challenging to help learners achieve high-level group performance, knowledge …
it remains challenging to help learners achieve high-level group performance, knowledge …
Parallel and distributed graph neural networks: An in-depth concurrency analysis
Graph neural networks (GNNs) are among the most powerful tools in deep learning. They
routinely solve complex problems on unstructured networks, such as node classification …
routinely solve complex problems on unstructured networks, such as node classification …
A new approach for active automata learning based on apartness
We present L#, a new and simple approach to active automata learning. Instead of focusing
on equivalence of observations, like the L∗ algorithm and its descendants, L# takes a …
on equivalence of observations, like the L∗ algorithm and its descendants, L# takes a …