2014/12/26 by Marjan Alirezaie, Alirezaie, Marjan, Amy Loutfi +1
Computer Science · #Advanced Database Systems and Queries #Artificial Intelligence (cs.AI) #Data Management and Algorithms #FOS: Computer and information sciences #Semantic Web and Ontologies #cs.AI
paper · pdf · doi:10.48550/arxiv.1412.7961
ARCOE-Logic 2014 Workshop Notes, pp. 1-12
arxiv created 2014/12/26 · openalex publication_date 2014/12/26 · arxiv updated 2014/12/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper an ontological representation and reasoning paradigm has been proposed for interpretation of time-series signals. The signals come from sensors observing a smart environment. The signal chosen for the annotation process is a set of unintuitive and complex gas sensor data. The ontology of this paradigm is inspired form the SSN ontology (Semantic Sensor Network) and used for representation of both the sensor data and the contextual information. The interpretation process is mainly done by an incremental ASP solver which as input receives a logic program that is generated from the contents of the ontology. The contextual information together with high level domain knowledge given in the ontology are used to infer explanations (answer sets) for changes in the ambient air detected by the gas sensors.