Introducing dead bands within two-dimensional clusters of user data to improve data classification

David Adrian Sanders; Jorge Bergasa-Suso; Rinat Khusainov; Alexander Emilov Gegov; Simon David Chester; Nils Christian Bausch

doi:10.1109/HSI.2016.7529602

Introducing dead bands within two-dimensional clusters of user data to improve data classification

David Adrian Sanders, Jorge Bergasa-Suso, Rinat Khusainov, Alexander Emilov Gegov, Simon David Chester, Nils Christian Bausch

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Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Methods are described to create more accurate sub sets of user data by introducing dead bands into data clusters. User data is collected and then mined. That produces clusters of data. Dead bands are then generated to delineate and describe the data in the clusters more accurately. This is accomplished by classifying data inside the newly created dead bands as NOT being in either of two or more clusters. For example, three clusters are generated from two. If the two were YES and NO then another set of DON’T KNOW is introduced. The new set improves the precision of choices made using data in the YES and the NO clusters. Dead bands are introduced by establishing a radius from the corners of the clusters or by establishing a horizontal or vertical line in parallel with the edges of the clusters. Each radius or encompasses 80% of user data nearest to the corner or edge of the data set. 20% are outside and excluded from their original set. If lines do not overlap, then a dead-band is created to contain user data that is not as confident. That increases the likelihood of accurate decisions being made about the new sets of user data. Case studies are described to show that.

Original language	English
Title of host publication	Proceedings of the 9th International Conference on Human Systems Interaction (HSI)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	14-20
Number of pages	7
ISBN (Electronic)	978-1-5090-1729-4
ISBN (Print)	978-1-5090-1730-0
DOIs	https://doi.org/10.1109/HSI.2016.7529602
Publication status	Published - Aug 2016
Event	9th International Conference on Human System Interactions: HSI 2016 - University of Portsmouth, Portsmouth, United Kingdom Duration: 6 Jul 2016 → 8 Jul 2016

Conference

Conference	9th International Conference on Human System Interactions
Abbreviated title	HSI 2016
Country/Territory	United Kingdom
City	Portsmouth
Period	6/07/16 → 8/07/16

Keywords

user information
set
dead bands
mining
data
clusters
post processing

Access to Document

10.1109/HSI.2016.7529602

Introducing_dead_bands
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Accepted author manuscript (Post-print), 695 KB

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9th International Conference on Human System Interactions
David Sanders (Presented paper)
7 Jul 2016
Activity: Participating in or organising an event types › Participation in conference

Cite this

Sanders, D. A., Bergasa-Suso, J., Khusainov, R., Gegov, A. E., Chester, S. D., & Bausch, N. C. (2016). Introducing dead bands within two-dimensional clusters of user data to improve data classification. In Proceedings of the 9th International Conference on Human Systems Interaction (HSI) (pp. 14-20). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HSI.2016.7529602

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abstract = "Methods are described to create more accurate sub sets of user data by introducing dead bands into data clusters. User data is collected and then mined. That produces clusters of data. Dead bands are then generated to delineate and describe the data in the clusters more accurately. This is accomplished by classifying data inside the newly created dead bands as NOT being in either of two or more clusters. For example, three clusters are generated from two. If the two were YES and NO then another set of DON{\textquoteright}T KNOW is introduced. The new set improves the precision of choices made using data in the YES and the NO clusters. Dead bands are introduced by establishing a radius from the corners of the clusters or by establishing a horizontal or vertical line in parallel with the edges of the clusters. Each radius or encompasses 80% of user data nearest to the corner or edge of the data set. 20% are outside and excluded from their original set. If lines do not overlap, then a dead-band is created to contain user data that is not as confident. That increases the likelihood of accurate decisions being made about the new sets of user data. Case studies are described to show that.",

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author = "Sanders, {David Adrian} and Jorge Bergasa-Suso and Rinat Khusainov and Gegov, {Alexander Emilov} and Chester, {Simon David} and Bausch, {Nils Christian}",

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Sanders, DA, Bergasa-Suso, J, Khusainov, R , Gegov, AE, Chester, SD & Bausch, NC 2016, Introducing dead bands within two-dimensional clusters of user data to improve data classification. in Proceedings of the 9th International Conference on Human Systems Interaction (HSI). Institute of Electrical and Electronics Engineers Inc., pp. 14-20, 9th International Conference on Human System Interactions, Portsmouth, United Kingdom, 6/07/16. https://doi.org/10.1109/HSI.2016.7529602

Introducing dead bands within two-dimensional clusters of user data to improve data classification. / Sanders, David Adrian; Bergasa-Suso, Jorge; Khusainov, Rinat et al.
Proceedings of the 9th International Conference on Human Systems Interaction (HSI). Institute of Electrical and Electronics Engineers Inc., 2016. p. 14-20.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Methods are described to create more accurate sub sets of user data by introducing dead bands into data clusters. User data is collected and then mined. That produces clusters of data. Dead bands are then generated to delineate and describe the data in the clusters more accurately. This is accomplished by classifying data inside the newly created dead bands as NOT being in either of two or more clusters. For example, three clusters are generated from two. If the two were YES and NO then another set of DON’T KNOW is introduced. The new set improves the precision of choices made using data in the YES and the NO clusters. Dead bands are introduced by establishing a radius from the corners of the clusters or by establishing a horizontal or vertical line in parallel with the edges of the clusters. Each radius or encompasses 80% of user data nearest to the corner or edge of the data set. 20% are outside and excluded from their original set. If lines do not overlap, then a dead-band is created to contain user data that is not as confident. That increases the likelihood of accurate decisions being made about the new sets of user data. Case studies are described to show that.

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Sanders DA, Bergasa-Suso J, Khusainov R , Gegov AE, Chester SD, Bausch NC. Introducing dead bands within two-dimensional clusters of user data to improve data classification. In Proceedings of the 9th International Conference on Human Systems Interaction (HSI). Institute of Electrical and Electronics Engineers Inc. 2016. p. 14-20 Epub 2016 Aug 4. doi: 10.1109/HSI.2016.7529602

Introducing dead bands within two-dimensional clusters of user data to improve data classification

Abstract

Conference

Keywords

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Projects

Ways to assist in using the Internet (Third Research Project)

Activities

9th International Conference on Human System Interactions

Cite this