Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Alevizos, Elias"'
We present a system for Complex Event Recognition (CER) based on automata. While multiple such systems have been described in the literature, they typically suffer from a lack of clear and denotational semantics, a limitation which often leads to con
Externí odkaz:
http://arxiv.org/abs/2407.02884
Autor:
Akasiadis, Charilaos, Kladis, Evgenios, Michelioudakis, Evangelos, Alevizos, Elias, Artikis, Alexander
Early Time-Series Classification (ETSC) is the task of predicting the class of incoming time-series by observing as few measurements as possible. Such methods can be employed to obtain classification forecasts in many time-critical applications. Howe
Externí odkaz:
http://arxiv.org/abs/2203.01628
We propose an automaton model which is a combination of symbolic and register automata, i.e., we enrich symbolic automata with memory. We call such automata Symbolic Register Automata (SRA). SRA extend the expressive power of symbolic automata, by al
Externí odkaz:
http://arxiv.org/abs/2110.04032
Complex Event Recognition (CER) systems have become popular in the past two decades due to their ability to "instantly" detect patterns on real-time streams of events. However, there is a lack of methods for forecasting when a pattern might occur bef
Externí odkaz:
http://arxiv.org/abs/2109.00287
Autor:
Akasiadis, Charilaos, Ponce-de-Leon, Miguel, Montagud, Arnau, Michelioudakis, Evangelos, Atsidakou, Alexia, Alevizos, Elias, Artikis, Alexander, Valencia, Alfonso, Paliouras, Georgios
Computational systems and methods are often being used in biological research, including the understanding of cancer and the development of treatments. Simulations of tumor growth and its response to different drugs are of particular importance, but
Externí odkaz:
http://arxiv.org/abs/2103.14132
Publikováno v:
LPAR-22.Proc. 57(2018) 16-35
Complex Event Processing (CEP) systems have appeared in abundance during the last two decades. Their purpose is to detect in real-time interesting patterns upon a stream of events and to inform an analyst for the occurrence of such patterns in a time
Externí odkaz:
http://arxiv.org/abs/1901.01826
We present a system for online probabilistic event forecasting. We assume that a user is interested in detecting and forecasting event patterns, given in the form of regular expressions. Our system can consume streams of events and forecast when the
Externí odkaz:
http://arxiv.org/abs/1804.10388
We propose an automaton model which is a combination of symbolic and register automata, i.e., we enrich symbolic automata with memory. We call such automata Register Match Automata (RMA). RMA extend the expressive power of symbolic automata, by allow
Externí odkaz:
http://arxiv.org/abs/1804.09999
Autor:
Alevizos, Elias, Artikis, Alexander, Katzouris, Nikos, Michelioudakis, Evangelos, Paliouras, Georgios
The Complex Event Recognition (CER) group is a research team, affiliated with the National Centre of Scientific Research "Demokritos" in Greece. The CER group works towards advanced and efficient methods for the recognition of complex events in a mul
Externí odkaz:
http://arxiv.org/abs/1802.04086
Complex Event Recognition applications exhibit various types of uncertainty, ranging from incomplete and erroneous data streams to imperfect complex event patterns. We review Complex Event Recognition techniques that handle, to some extent, uncertain
Externí odkaz:
http://arxiv.org/abs/1702.06379