NDLI: Bayesian approach to sensor-based context awareness

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Bayesian approach to sensor-based context awareness

Content Provider	Springer Nature Link
Author	Korpipää, Panu Koskinen, Miika Peltola, Johannes Mäkelä, Satu Marja Seppänen, Tapio
Copyright Year	2003
Abstract	The usability of a mobile device and services can be enhanced by context awareness. The aim of this experiment was to expand the set of generally recognizable constituents of context concerning personal mobile device usage. Naive Bayesian networks were applied to classify the contexts of a mobile device user in her normal daily activities. The distinguishing feature of this experiment in comparison to earlier context recognition research is the use of a naive Bayes framework, and an extensive set of audio features derived partly from the algorithms of the upcoming MPEG-7 standard. The classification was based mainly on audio features measured in a home scenario. The classification results indicate that with a resolution of one second in segments of 5–30 seconds, situations can be extracted fairly well, but most of the contexts are likely to be valid only in a restricted scenario. Naive Bayes framework is feasible for context recognition. In real world conditions, the recognition accuracy using leave-one-out cross validation was 87% of true positives and 95% of true negatives, averaged over nine eight-minute scenarios containing 17 segments of different lengths and nine different contexts. Respectively, the reference accuracies measured by testing with training data were 88% and 95%, suggesting that the model was capable of covering the variability introduced in the data on purpose. Reference recognition accuracy in controlled conditions was 96% and 100%, respectively. However, from the applicability viewpoint, generalization remains a problem, as from a wider perspective almost any feature may refer to many possible real world situations.
Starting Page	113
Ending Page	124
Page Count	12
File Format	PDF
ISSN	16174909
Journal	Personal Technologies
Volume Number	7
Issue Number	2
Language	English
Publisher	Springer-Verlag
Publisher Date	2003-01-01
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Audio context Bayesian networks Context awareness Context recognition Mobile computing Sensor
Content Type	Text
Resource Type	Article
Subject	Management Science and Operations Research Library and Information Sciences Computer Science Applications Hardware and Architecture

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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