Probabilistic abstraction of uncertain temporal data for multiple subjects

Michael Ramati, Yuval Shahar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Several Systems have been designed to solve the task of abstraction of time-stamped raw data into domain-specific meaningful concepts and patterns. All approaches had to some degree severe limitations in their treatment of incompleteness and uncertainty that typically underlie the raw data, on which the temporal reasoning is performed, and have generally narrowed their interest to a single subject. We have designed a new probability-oriented methodology to overcome these conceptual limitations. The new method includes also a practical parallel computational model that is geared specifically for implementing our probabilistic approach.

Original languageEnglish
Title of host publicationAbstraction, Reformulation and Approximation - 6th International Symposium, SARA 2005, Proceedings
PublisherSpringer Verlag
Pages305-312
ISBN (Print)3540278729, 9783540278726
DOIs
StatePublished - 1 Jan 2005
Event6th International Symposium on Abstraction, Reformulation and Approximation, SARA 2005 - Airth Castle, Scotland, United Kingdom
Duration: 26 Jul 200529 Jul 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3607 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Symposium on Abstraction, Reformulation and Approximation, SARA 2005
Country/TerritoryUnited Kingdom
CityAirth Castle, Scotland
Period26/07/0529/07/05

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