Towards Activity Recognition Using Probabilistic Description Logics

Helaoui, Rim ; Riboni, Daniele ; Niepert, Mathias ; Bettini, Claudio ; Stuckenschmidt, Heiner

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Document Type: Conference or workshop publication
Year of publication: 2012
Book title: Activity context representation: techniques and languages : papers from the 2012 AAAI Workshop ; [held Monday, July 23, 2012 in Toronto, Ontario, Canada]
The title of a journal, publication series: Technical report / Association for the Advancement of Artificial Intelligence. WS
Volume: 12-05
Page range: 26-31
Date of the conference: July 23rd, 2012
Place of publication: Palo Alto, Calif.
Publishing house: AAAI Press
ISBN: 978-1-57735-570-0
Publication language: English
Institution: School of Business Informatics and Mathematics > Praktische Informatik II (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: A major challenge of pervasive context-aware computing and intelligent environments resides in the acquisition and modelling of rich and heterogeneous context data. Decisive aspects of this information are the ongoing human activities at different degrees of granularity. We conjecture that ontology-based activity models are key to support interoperable multilevel activity representation and recognition. In this paper, we report on an initial investigation about the application of probabilistic description logics (DLs) to a framework for the recognition of multilevel activities in intelligent environments. In particular, being based on Log-linear DLs, our approach leverages the potential of highly expressive description logics with probabilistic reasoning in one unified framework. While we believe that this approach is very promising, our preliminary investigation suggests that challenging research issues remain open, including extensive support for temporal reasoning, and optimizations to reduce the computational cost.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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