Applied artificial intelligence group

Research classification (Frascati)
Head of the research group
Doctoral students
Keyword
automated commonsense reasoning
ontology based reasoning
AI methods in spatial data analysis
recommender systems
logic-based software systems
Overview
The Applied AI Group conducts research inapplication of AI methods in various fieldsand systems. We investigate applicabilityof machine learning, ontology based reasoning, automated theorem provers, knowledgediscovery and other AI methods for solvingdigitalisation problems of different industrialand governmental stakeholders.Our previous research has been concentratedon building software development methodsand tools (e.g. CoCoViLa) with AI components,basically with program synthesis and ontologybased knowledge representation components.During a number of decades several softwaretools that facilitate AI techniques have beendeveloped by the group. The following is a listof tools that are still in use or under development:‚ CoCoViLa – a visual model-based software development environment –http://cocovila.github.io/‚ WhiteDB – a lightweight NoSQL database library – http://whitedb.org/‚ GKC – a discussion tool on large knowledgebases – https://github.com/tammet/gkcCurrently we work on topics such as application of AI methods in spatial data analysis,using machine learning for risk managementin e-commerce and for public service delivery.
Important results
Järv, P.; Tammet, T.; Verrev, M.; Draheim, D. (2023). Large-scale commonsense knowledge for default logic reasoning. SN Computer Science, 4 (550), 14 pp. DOI: 10.1007/s42979-023-01963-2
Tammet, T.; Järv, P.; Verrev, M.; Draheim, D. (2023). An experimental pipeline for automated reasoning in natural language (short paper). In: Pientka, Brigitte; Tinelli, Cesare (Ed.). Automated Deduction –CADE 29 : 29th International Conference on Automated Deduction, Rome, Italy, July 1–4, 2023, Proceedings. (509−521). Cham: Springer. (Lecture Notes in Computer Science; 14132). DOI: 10.1007/978-3-031-38499-8_29
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