1,721,162 research outputs found
The digital world is also about "Ada and the others"|Il mondo digitale è anche di “Ada e le altre”
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Introduction to Anna Vaccarelli's article for the column "Ada and the Others"|Introduzione all’articolo di Anna Vaccarelli per la rubrica “Ada e le altre”
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Higher-order description logics for learning and mining in complex domains
No full textThis short paper summarizes the work I have done over the last years on the use of higher-order Description Logics (DLs) for learning and mining in complex domains. In particular, the work proposes higher-order DLs as a means for metamodeling and metaquerying in Concept Learning and Knowledge Graph Mining, respectively
MASS-CSP: mining with answer set solving for contrast sequential pattern mining
No full textIn this paper, we present MASS-CSP (Mining with Answer Set Solving - Contrast Sequential Patterns), a declarative approach to the Contrast Sequential Pattern Mining (CSPM) task, which is based on the logic-based framework of Answer Set Programming (ASP). The CSPM task focuses on identifying significant differences in frequent sequences relative to specific classes, leading to the concept of a contrast sequential pattern. The article describes how MASS-CSP addresses the CSPM task and related extensions-mining closed, maximal and constrained patterns. Evaluation aims at comparing the basic version of MASS-CSP against the extended versions as regards the size of output and time-memory requirements
Forecasting of electricity price through a functional prediction of sale and purchase curves
No full textThis work proposes a new approach for the prediction of the electricity price based on forecasting aggregated purchase and sale curves. The basic idea is to model the hourly purchase and the sale curves, to predict them and to find the intersection of the predicted curves in order to obtain the predicted equilibrium market price and volume. Modeling and forecasting of purchase and sale curves is performed by means of functional data analysis methods. More specifically, parametric (FAR) and nonparametric (NPFAR) functional autoregressive models are considered and compared to some benchmarks. An appealing feature of the functional approach is that, unlike other methods, it provides insights into the sale and purchase mechanism connected with the price and demand formation process and can therefore be used for the optimization of bidding strategies. An application to the Italian electricity market (IPEX) is also provided, showing that NPFAR models lead to a statistically significant impro..
From human interaction to human-robot interaction: A possible model
No full textThis paper presents the Elementary Pragmatic Model, originally developed for studying human interaction and widely used in psycotherapy, as a starting point for novel AI applications where humans interact with AI agents
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