Knowledge Tree
knowledge acquisition
Also known as: knowledge acquisition methods
Facts (36)
Sources
Knowledge Graphs: Opportunities and Challenges - Springer Nature link.springer.com Apr 3, 2023 8 facts
referenceKnowledge acquisition involves modeling and constructing knowledge graphs by importing data from structured sources using mapping languages like R2RML (Rodriguez-Muro and Rezk 2015) or by extracting knowledge from unstructured documents like news, research papers, and patents using relation, entity, or attribute extraction methods (Liu et al. 2020; Yu et al. 2020; Yao et al. 2019).
claimKnowledge acquisition, which involves extracting knowledge from structured and unstructured data, is a critical step in generating knowledge graphs.
claimThe challenges in developing knowledge graphs are categorized into the limitations of five topical technologies: knowledge graph embeddings, knowledge acquisition, knowledge graph completion, knowledge fusion, and knowledge reasoning.
claimExisting knowledge acquisition methods suffer from low accuracy, which results in incomplete or noisy knowledge graphs that hinder downstream AI tasks.
claimMost existing knowledge acquisition methods focus on constructing knowledge graphs using only one specific language.
claimSignificant technical challenges in knowledge graph development involve limitations in five representative technologies: knowledge graph embeddings, knowledge acquisition, knowledge graph completion, knowledge fusion, and knowledge reasoning.
claimResearch on knowledge graphs faces technical challenges, specifically regarding the acquisition of knowledge from multiple sources and the integration of that knowledge into a typical knowledge graph.
referenceThe three primary methods of knowledge acquisition are relation extraction, entity extraction, and attribute extraction, with attribute extraction functioning as a subset of entity extraction (Fu et al. 2019).
Social epistemology - Routledge Encyclopedia of Philosophy rep.routledge.com 3 facts
claimEpistemologists, starting with René Descartes, have often praised exclusive self-reliance in knowledge acquisition as an ideal.
claimSocial epistemology includes branches that study systems and institutions designed to facilitate knowledge transmission and acquisition, as well as collectives like groups or teams acting as epistemic agents.
claimSocial epistemology encompasses the study of the social dimensions of knowledge acquisition and transmission, the evaluation of beliefs and belief-forming mechanisms in their social contexts for their truth-related or veritistic features, and the study of the epistemic significance of other minds.
Naturalized epistemology - Wikipedia en.wikipedia.org 3 facts
perspectiveRoderick Chisholm argues that there are epistemic principles necessary for knowledge acquisition that may not be reducible to natural facts.
claimThe scientific study of knowledge differs from the traditional philosophical study of knowledge by focusing on how humans acquire knowledge rather than relying on speculative analysis.
claimNaturalized epistemology shifts the focus of epistemology away from traditional philosophical questions and towards the empirical processes of knowledge acquisition.
Naturalized epistemology and cognitive science | Intro to... - Fiveable fiveable.me 3 facts
claimEvolutionary epistemology applies evolutionary theory to the study of knowledge acquisition.
claimCognitive science employs experiments, brain imaging, and computer models to explore the processes of knowledge acquisition and information processing.
claimCognitive science examines how cultural and social factors influence cognition and knowledge acquisition.
The Synergy of Symbolic and Connectionist AI in LLM-Empowered ... arxiv.org Jul 11, 2024 2 facts
referenceThomas R. Gruber proposed a translation approach to portable ontology specifications in a 1993 article in Knowledge Acquisition.
perspectiveSymbolic AI faces challenges regarding the labor-intensive nature of knowledge acquisition and its limited adaptability.
Epistemology - Wikipedia en.wikipedia.org 2 facts
claimChun Wei Choo authored the chapter 'Epistemic Virtues and Vices' in the 2016 book 'The Inquiring Organization: How Organizations Acquire Knowledge and Seek Information', published by Oxford University Press.
claimSocial epistemology focuses on knowledge acquisition, transmission, and evaluation within groups, specifically emphasizing how individuals rely on each other when seeking knowledge, whereas traditional epistemology is primarily interested in knowledge possessed by individuals.
Social Epistemology - Stanford Encyclopedia of Philosophy plato.stanford.edu Feb 26, 2001 2 facts
referenceFormal epistemology uses proof-based methods to address questions of knowledge acquisition within a community, including topics like judgment aggregation and testimony.
referenceMona Simion's 2023 paper 'Knowledge and disinformation' analyzes the relationship between knowledge acquisition and the spread of false information.
The Role of Epistemic Communities and Expert Testimonies in ... academia.edu 1 fact
claimExpert testimonies are foundational to knowledge acquisition and belief justification in social epistemology.
Sources of Knowledge: Rationalism, Empiricism, and the Kantian ... press.rebus.community 1 fact
claimRené Descartes categorizes knowledge acquisition into three modes: innate ideas, externally sourced ideas, and ideas constructed by the human mind.
The traditional use of wild edible plants in pastoral and agro ... link.springer.com Feb 23, 2023 1 fact
claimInnovation is the initial step of knowledge acquisition, while observation, familiarizing oneself with natural resources, and providing help to adults are the first steps of knowledge transmission associated with natural resources.
KR 2026 : 23rd International Conference on Principles of ... - WikiCFP wikicfp.com 1 fact
claimThe 23rd International Conference on Principles of Knowledge Representation and Reasoning (KR 2026) covers research topics including argumentation, belief change, common-sense reasoning, computational aspects of knowledge representation, description logics, ethical considerations in knowledge representation, explanation, abduction and diagnosis, geometric, spatial, and temporal reasoning, inconsistency- and exception-tolerant reasoning, knowledge acquisition, knowledge compilation, automated reasoning, satisfiability and model counting, knowledge representation languages, logic programming, answer set programming, model learning for diagnosis and planning, modeling and reasoning about preferences, modeling constraints and constraint solving, multi- and order-sorted representations and reasoning, non-monotonic logics, ontologies and knowledge-enriched data management, philosophical foundations of knowledge representation, qualitative reasoning, reasoning about actions and change, action languages, reasoning about knowledge, beliefs, and other mental attitudes, reasoning in knowledge graphs, reasoning in multi-agent systems, semantic web, similarity-based and contextual reasoning, and uncertainty and vagueness.
Knowledge Graphs: Opportunities and Challenges - arXiv arxiv.org Mar 24, 2023 1 fact
claimThe technical challenges in the field of knowledge graphs include knowledge graph embeddings, knowledge acquisition, knowledge graph completion, knowledge fusion, and knowledge reasoning.
Call for Papers: Main Track - KR 2026 kr.org 1 fact
claimThe KR 2026 conference accepts submissions on topics including argumentation, belief change, common-sense reasoning, computational aspects of knowledge representation, description logics, ethical considerations in KR, explanation/abduction/diagnosis, geometric/spatial/temporal reasoning, inconsistency- and exception-tolerant reasoning, knowledge acquisition, knowledge compilation/automated reasoning/satisfiability/model counting, knowledge representation languages, logic programming/answer set programming, model learning for diagnosis and planning, modeling and reasoning about preferences, modeling constraints and constraint solving, multi- and order-sorted representations and reasoning, non-monotonic logics, ontologies and knowledge-enriched data management, philosophical foundations of KR, qualitative reasoning, reasoning about actions and change/action languages, reasoning about knowledge/beliefs/mental attitudes, reasoning in knowledge graphs, reasoning in multi-agent systems, semantic web, similarity-based and contextual reasoning, and uncertainty and vagueness.
Combining Knowledge Graphs and Large Language Models - arXiv arxiv.org Jul 9, 2024 1 fact
procedureThe construction of a Knowledge Graph (KG) involves three general steps: knowledge acquisition (collecting information about entities and relations from multi-structured data), knowledge refinement (fixing incomplete triples with additional data), and knowledge evolution (dynamically updating graphs to reflect real-world changes over time).
A Survey of Incorporating Psychological Theories in LLMs - arXiv arxiv.org 1 fact
claimDevelopmental psychology's emphasis on staged learning and knowledge acquisition aligns with curriculum learning and progressive data exposure in LLM training, mirroring human developmental trajectories.
A Survey on the Theory and Mechanism of Large Language Models arxiv.org Mar 12, 2026 1 fact
referenceThe paper 'Understanding LLM behaviors via compression: data generation, knowledge acquisition and scaling laws' (arXiv:2504.09597) discusses data generation, knowledge acquisition, and scaling laws in large language models.
Epistemological Problems of Testimony plato.stanford.edu Apr 1, 2021 1 fact
claimJohn Hardwig argued in 1985 that epistemic dependence is a fundamental feature of knowledge acquisition, meaning individuals must rely on others for much of what they know.
The Synergy of Symbolic and Connectionist AI in LLM ... arxiv.org 1 fact
perspectiveConnectionist AI is criticized for its black-box nature and lack of interpretability, while symbolic AI faces challenges regarding labor-intensive knowledge acquisition and limited adaptability.
Opportunities and Challenges with Knowledge Graphs briancartergroup.com Oct 5, 2024 1 fact
claimKnowledge graph development faces technical challenges, specifically regarding knowledge graph embeddings and knowledge acquisition, according to the article 'Opportunities and Challenges with Knowledge Graphs'.
Knowledge Graphs: Opportunities and Challenges dl.acm.org 1 fact
claimThe authors of the paper 'Knowledge Graphs: Opportunities and Challenges' identify knowledge acquisition as a severe technical challenge in the field of knowledge graphs.