Representing Features and Contexts in a Data Library

Panu Korpipää, Juha Pärkkä, Luc Cluitmans

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

Abstract

Context data library consists of data in different levels of abstraction; raw data, features, contexts and annotatated target contexts. Raw data is compacted by extracting features and/or context atoms, which represent the data in an abstracted form. This paper discusses structure, naming, and format for feature and context data. The representation is compatible with annotation data format. Represented with the same format, features and annotated target contexts can together be straightforwardly used for evaluating the results of context recognition methods, and for visualising the data at different levels of abstraction.
Original languageEnglish
Title of host publicationBenchmarks and a Database for Context Recognition: Pervasive 2004 Workshop Proceedings
Place of PublicationZurich
Pages32-37
Publication statusPublished - 2004
MoE publication typeA4 Article in a conference publication
EventBenchmarks and a database for context recognition: held in conjuction with the 2nd International Conference on Pervasive Computing, PERVASIVE 2004 - Linz/Vienna, Austria
Duration: 18 Apr 200423 Apr 2004

Conference

ConferenceBenchmarks and a database for context recognition: held in conjuction with the 2nd International Conference on Pervasive Computing, PERVASIVE 2004
CountryAustria
CityLinz/Vienna
Period18/04/0423/04/04

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Korpipää, P., Pärkkä, J., & Cluitmans, L. (2004). Representing Features and Contexts in a Data Library. In Benchmarks and a Database for Context Recognition: Pervasive 2004 Workshop Proceedings (pp. 32-37). Zurich.
Korpipää, Panu ; Pärkkä, Juha ; Cluitmans, Luc. / Representing Features and Contexts in a Data Library. Benchmarks and a Database for Context Recognition: Pervasive 2004 Workshop Proceedings. Zurich, 2004. pp. 32-37
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note = "T3SU00172",
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Korpipää, P, Pärkkä, J & Cluitmans, L 2004, Representing Features and Contexts in a Data Library. in Benchmarks and a Database for Context Recognition: Pervasive 2004 Workshop Proceedings. Zurich, pp. 32-37, Benchmarks and a database for context recognition: held in conjuction with the 2nd International Conference on Pervasive Computing, PERVASIVE 2004, Linz/Vienna, Austria, 18/04/04.

Representing Features and Contexts in a Data Library. / Korpipää, Panu; Pärkkä, Juha; Cluitmans, Luc.

Benchmarks and a Database for Context Recognition: Pervasive 2004 Workshop Proceedings. Zurich, 2004. p. 32-37.

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

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N2 - Context data library consists of data in different levels of abstraction; raw data, features, contexts and annotatated target contexts. Raw data is compacted by extracting features and/or context atoms, which represent the data in an abstracted form. This paper discusses structure, naming, and format for feature and context data. The representation is compatible with annotation data format. Represented with the same format, features and annotated target contexts can together be straightforwardly used for evaluating the results of context recognition methods, and for visualising the data at different levels of abstraction.

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Korpipää P, Pärkkä J, Cluitmans L. Representing Features and Contexts in a Data Library. In Benchmarks and a Database for Context Recognition: Pervasive 2004 Workshop Proceedings. Zurich. 2004. p. 32-37