Pesquisa de Doutorado da Veronica

Arijit Khan. 2023. Knowledge Graphs Querying. SIGMOD Rec. 52, 2 (June 2023), 18–29. https://doi.org/10.1145/3615952.3615956 ABSTRACT Querying KGs is critical in web search, question answering (QA), semantic search, personal assistants, fact checking, and recommendation. [Sistemas / tarefas onde consulta aos KGs é usada] First, research on KG querying has been conducted by several communities, such as databases, data mining, semantic web, machine learning, information retrieval, and natural language processing (NLP), with different focus and terminologies; and also in diverse topics ranging from graph databases, query languages, join algorithms, graph patterns matching, to more sophisticated KG embedding and natural language questions (NLQs). [Diversas perspectivas sobre os problemas que as consultas em KG trazem] Second, many recent advances on KG and query embedding, multimodal KG, and KG-QA come from deep learning, IR, NLP, and computer vision domains.  [De quais comunidades estão se

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 central c