Bridging the Semantic Gap between Sensor Data and High Level Knowledge

Marjan Alirezaie, Amy Loutfi

2013

Abstract

The advance of modeling knowledge in different domains along with the promotion in sensor technology that causes the emergence of data streams are addressing a new problem, namely the semantic gap. The objective of this research is bridging the semantic gap between qualitative knowledge and quantitative raw data, specifically electronic nose data coming from chemical sensors that sniff the gas (odour) in the environment. More precisely, the gap bridging in this research is defined as the process of data stream annotation with high level concepts. We introduce three frameworks implemented or under studies for the task of sensor data annotation for which the effectiveness in the sense of the time complexity and the expressiveness of final explanations are examined. The paper outlines the main contributions of the work, details the progress so far after two year of the thesis work, and provides an outline of planned activities.

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Paper Citation


in Harvard Style

Alirezaie M. and Loutfi A. (2013). Bridging the Semantic Gap between Sensor Data and High Level Knowledge . In Doctoral Consortium - Doctoral Consortium, (IC3K 2013) ISBN Not Available, pages 21-27


in Bibtex Style

@conference{doctoral consortium13,
author={Marjan Alirezaie and Amy Loutfi},
title={Bridging the Semantic Gap between Sensor Data and High Level Knowledge},
booktitle={Doctoral Consortium - Doctoral Consortium, (IC3K 2013)},
year={2013},
pages={21-27},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={Not Available},
}


in EndNote Style

TY - CONF
JO - Doctoral Consortium - Doctoral Consortium, (IC3K 2013)
TI - Bridging the Semantic Gap between Sensor Data and High Level Knowledge
SN - Not Available
AU - Alirezaie M.
AU - Loutfi A.
PY - 2013
SP - 21
EP - 27
DO -