Pesquisa de Doutorado da Veronica

J. Sequeda, D. Allemang and B. Jacob, Knowledge Graphs as a source of trust for LLM-powered enterprise question answering, Web Semantics: Science, Services and Agents on the World Wide Web (2025), doi: https://doi.org/10.1016/j.websem.2024.100858. 1. Introduction These question answering systems that enable to chat with your structured data hold tremendous potential for transforming the way self service and data-driven decision making is executed within enterprises. Self service and data-driven decision making in organizations today is largly made through Business Intelligence (BI) and analytics reporting. Data teams gather the original data, integrate the data, build a SQL data warehouse (i.e. star schemas), and create BI dashboards and reports that are then used by business users and analysts to answer specific questions (i.e. metrics, KPIs) and make decisions. The bottleneck of this approach is that business users are only able to answer questions given the views of existing dashboa...

 A Comprehensive Approach to Assess Trustworthiness and Completeness of Knowledge Graphs  International Journal of Knowledge Engineering, Vol. 10, No. 1, 2024    Abstract Completeness and trustworthiness are two dimensions that are used to assess the quality of KGs. Estimation of the completeness and trustworthiness of a largescale knowledge graph often requires humans to annotate samples from the graph. Estimativa de métricas de qualidade que dependem de interferência humana Nowadays, to reduce the costs of the manual construction of knowledge graphs, many KGs have been constructed automatically from sources with varying degrees of trustworthiness. Therefore, possible noises and conflicts are inevitably introduced in the process of construction, which severely interferes with the quality of constructed KGs.  O processo de construção automática para aumentar a completude pode degradar a confiabilidade. Introduz "fatos" incorretos ou conflitantes. we propose a ne...