Knowledge Tree
Relations (1)
related 2.58 — strongly supporting 5 facts
Scalability is identified as a primary technical challenge in the construction and maintenance of a Knowledge Graph [1], [2], and [3]. Furthermore, system design choices such as data focus [4] and update strategies [5] are explicitly linked to the scalability of Knowledge Graph implementations.
Facts (5)
Sources
Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org 3 facts
claimSuccinctness in a knowledge graph requires a high focus of data, such as on a single domain, and the exclusion of unnecessary information to improve resource consumption, scalability, and system availability.
claimKnowledge graph-specific approaches have limitations regarding scalability to many sources, support for incremental updates, metadata management, ontology management, entity resolution and fusion, and quality assurance.
claimRecomputing a knowledge graph from scratch for every update results in redundant computation, which limits scalability as the number and size of input sources increase.
What are the challenges in maintaining a knowledge graph? - Milvus milvus.io 1 fact
claimMaintaining a knowledge graph requires addressing a multifaceted set of challenges, specifically data quality, scalability, semantic complexity, and security.
LLM-empowered knowledge graph construction: A survey - arXiv arxiv.org 1 fact
claimTraditional Knowledge Graph construction paradigms face three enduring challenges: scalability and data sparsity due to the failure of rule-based and supervised systems to generalize across domains; expert dependency and rigidity because schema and ontology design require substantial human intervention and lack adaptability; and pipeline fragmentation where disjoint handling of construction stages causes cumulative error propagation.