Referências extraídas do artigo sobre controvérsias na WD indicado pelo professor Altigran na defesa de proposta D. Artz and Y. Gil. A survey of trust in computer science and the semantic web. Journal ofWeb Semantics, 5(2), 2010. Abstract Trust is an integral component in many kinds of human interaction, allowing people to act under uncertainty and with the risk of negative consequences. For example, exchanging money for a service, giving access to your property, and choosing between conflicting sources of information all may utilize some form of trust. In computer science, trust is a widely used term whose definition differs among researchers and application areas. Trust is an essential component of the vision for the Semantic Web, where both new problems and new applications of trust are being studied. This paper gives an overview of existing trust research in computer science and the Semantic Web [Confiar a ponto de agir, mesmo assumindo riscos] 1. Introduction Trust is a centr...
Postagens
A Álgebra de Contra Domínio permite encontrar relações entre entidades, entre alegações ou entre entidades e alegações que podem não estar materializadas no grafo através de arestas. Mas é possível representar explicitamente na resposta. A Álgebra de Contra Domínio para valores de datas no Contexto Temporal que comentei é a Allen's Interval Algebra. Esta cobre as relações possíveis entre períodos de tempo. Existem extensões que incluem não só o intervalo mas também um momento no tempo. James F. Allen: Maintaining Knowledge about Temporal Intervals. Commun. ACM 26(11): 832-843 (1983) Em relação ao Contradomínio para valores de formas espaciais do Contexto de Localização a mais antiga que encontrei foi Region Connection Calculus. Esta trata a relação entre duas formas e existem extensões (ou outras algebras) que tratam ponto, reta, 3D, ... Randell, D.A.; Cui, Z; Cohn, A.G. (1992). "A spatial logic based on regions and connection". 3rd Int. Conf. on Knowledge Representa...
Dando uma googada https://iep.utm.edu/truth/ There are two commonly accepted constraints on truth and falsehood: Every proposition is true or false. [Law of the Excluded Middle.] No proposition is both true and false. [Law of Non-contradiction.] What is the difference between a truth-maker and a truth bearer? Truth-bearers are either true or false; truth-makers are not since, not being representations, they cannot be said to be true, nor can they be said to be false . That's a second difference. Truth-bearers are 'bipolar,' either true or false; truth-makers are 'unipolar': all of them obtain. What are considered truth bearers? A variety of truth bearers are considered – statements, beliefs, claims, assumptions, hypotheses, propositions, sentences, and utterances . When I speak of a fact . . . I mean the kind of thing that makes a proposition true or false. (Russe...
Keynote on Youtube -> https://youtu.be/DZ6NlcW4YV8?si=4Z5zDA1Vx_D10GKz No Intelligence Without Knowledge Katja Hose TU Wien, Austria Abstract. Knowledge graphs and graph data in general are becoming more and more essential components of intelligent systems. This does not only include native graph data, such as social networks or Linked Data on the Web. The flexibility of the graph model and its ability to store data relationships explicitly enables the integration and exploitation of data from very diverse sources. However, to truly exploit their potential, it becomes crucial to provide intelligent systems with verifiable knowledge, reliable facts, patterns, and a deeper understanding of the underlying domains. This talk will therefore chart a number of challenges for exploiting graphs to manage and bring meaning to large amounts of heterogeneous data and discuss opportunities with, without, and for artificial intelligence emerging from research situated at the confluence of data m...
https://arxiv.org/pdf/2308.06374.pdf community on LLMs (parametric knowledge) and Knowledge Graphs (explicit knowledge) [sub simbólico (embeddings) x simbólico] Introduction era of Knowledge Computing, in which the notion of reasoning within KR is broadened to many computation tasks based on various knowledge representations. [Modelos de Linguagem com Representação do Conhecimento] widely used knowledge representation languages, such as RDF [121] and OWL [55], at web scale, using which the large-scale knowledge bases are then more widely known as KGs [123], due to their helpful graph structures, enabling the both logical reasoning and graph-based learning. [Algoritmos de grafo independentes de domínio] Some works use LLMs to augment KGs for, e.g., knowledge extraction, KG construction, and refinement, while others use KGs to augment LLMs for, e.g., training and prompt learning, or knowledge augmentation. [Seria possível usar LLM para completar as respostas unknown em um KG?] Common Deb...
PREMISSAS (1) Pergunta potencialmente incompleta (OK) a) Qual capital Brasil? graph query (?v1, capital de, Brasil) ... incompleta em relação ao contexto temporal e proveniência b) Qual capital Brasil HOJE? graph query id1 (?v1, capital de, Brasil), (id1, período, HOJE) ... completa em relação ao contexto temporal e incompleta em relação a proveniência c) Qual capital Brasil HOJE de acordo com a Lei Federal? graph query id1 (?v1, capital de, Brasil), (id1, período, HOJE), (id1, fonte, ?v2), (?v2, tipo, Lei Federal) ... completa em relação ao contexto temporal e a proveniência Abordagem: Interagir em caso de pergunta incompleta? NÃO. O usuário pode ter assumido um contexto implícito e saberia completar caso questionado mas talvez nem o usuário saiba completar o contexto da pergunta (caso da Betina). Responder sem Interagir ( One-Shot/Stateless ), completar o Contexto que foi mapeado e fornecer uma ÚNICA resposta composta por todas as Alegações Co...