A5051961983- Semantic Web and Ontologies
- Rough Sets and Fuzzy Logic
- Logic, Reasoning, and Knowledge
- Fuzzy Logic and Control Systems
- Natural Language Processing Techniques
- Data Quality and Management
- Big Data and Business Intelligence
University of Oxford
2022-2024
TU Wien
2022-2024
Abstract Modern applications combine information from a great variety of sources. Oftentimes, some these sources, like machine-learning systems, are not strictly binary but associated with degree (lack of) confidence in the observation. We propose MV-Datalog and $\mathrm{MV-Datalog}^\pm$ as extensions Datalog $\mathrm{Datalog}^\pm$ , respectively, to fuzzy semantics infinite-valued Łukasiewicz logic $\mathbf{L}$ languages for effectively reasoning scenarios where such uncertain observations...
One of the main challenges in area Neuro-Symbolic AI is to perform logical reasoning presence both neural and symbolic data. This requires combining heterogeneous data sources such as knowledge graphs, model predictions, structured databases, crowd-sourced data, many more. To allow for reasoning, we generalise standard rule-based language Datalog with existential rules (commonly referred tuple-generating dependencies) fuzzy setting, by allowing arbitrary t-norms place classical conjunctions...
One of the main challenges in area Neuro-Symbolic AI is to perform logical reasoning presence both neural and symbolic data. This requires combining heterogeneous data sources such as knowledge graphs, model predictions, structured databases, crowd-sourced data, many more. To allow for reasoning, we generalise standard rule-based language Datalog with existential rules (commonly referred tuple-generating dependencies) fuzzy setting, by allowing arbitrary t-norms place classical conjunctions...
Modern data processing applications often combine information from a variety of complex sources. Oftentimes, some these sources, like Machine-Learning systems or crowd-sourced data, are not strictly binary but associated with degree confidence in the observation. Ideally, reasoning over such should take this additional into account as much possible. To end, we propose extensions Datalog and Datalog+/- to semantics Lukasiewicz logic Ł, one most common fuzzy logics. We show that an extension...
Competitor data constitutes information significantly valuable for many business applications. Meltwater provides users with access to a large Company Information System (CIS), Owler, which contains competitor pairs and other useful about companies. has been seeking practical solution discover more in Owler. The first attempt, fully-manual workflow (called MW_Manual) finding Owler consisted of two manual steps: filtering step that excludes obvious non-competitor company pairs, further...
Modern applications combine information from a great variety of sources. Oftentimes, some these sources, like Machine-Learning systems, are not strictly binary but associated with degree (lack of) confidence in the observation. We propose MV-Datalog and MV-Datalog+- as extensions Datalog Datalog+-, respectively, to fuzzy semantics infinite-valued Lukasiewicz logic L languages for effectively reasoning scenarios where such uncertain observations occur. show that exhibits similar...