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Post Processing Method that Acts on Two-dimensional Clusters of User Data to Produce Dead Bands and Improve Classification

Topics: Data Mining; e-Business and e-Commerce; Knowledge Management; Learning User Profiles; Metadata and Metamodeling; Multimedia and User Interfaces; Personalized Web Sites and Services; Searching and Browsing; Social Media Analytics; User Modeling; Web Information Filtering and Retrieval

Authors: David Adrian Sanders and Alexander Gegov

Affiliation: University of Portsmouth, United Kingdom

Keyword(s): User Information, Post Processing, 2-D Clusters, Data, Mining, Dead Bands, Set.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; e-Business and e-Commerce ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Metadata and Metamodeling ; Multimedia and User Interfaces ; Ontologies and the Semantic Web ; Personalized Web Sites and Services ; Searching and Browsing ; Sensor Networks ; Signal Processing ; Social Media Analytics ; Society, e-Business and e-Government ; Soft Computing ; User Modeling ; Web Information Systems and Technologies ; Web Interfaces and Applications

Abstract: A post processing method is described that acts on two-dimensional clusters of data produced from a data mining system. Dead bands are automatically created that further define the clusters. This was achieved by defining data within the dead bands as NOT belonging to either cluster. The three clusters produced were definitely YES, definitely NO and a new set of DON’T KNOW. The creation of the new set improved the accuracy of decisions made about the data remaining in YES and NO clusters. The introduction of the dead bands was achieved by either setting a radius during the learning process or by setting a straight line boundary. Each radius (or line) was calculated during the learning process by considering the twodimensional position of each of the users within each cluster of dimensions. A radius line (or straight line) was then introduced so that the 80% of users within a particular dimension who were nearest to the origin (or edge) were placed into a set. The other 20% we re outside the radius line (or straight line) and not recorded as being part of the set. If the two lines did not overlap, then this sometimes created a dead-band that contained users with less certain results and that in turn increased the accuracy of the other sets. Two case studies are presented as examples of that improvement. (More)

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Paper citation in several formats:
Adrian Sanders, D. and Gegov, A. (2015). Post Processing Method that Acts on Two-dimensional Clusters of User Data to Produce Dead Bands and Improve Classification. In Proceedings of the 11th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-106-9; ISSN 2184-3252, SciTePress, pages 267-272. DOI: 10.5220/0005473202670272

@conference{webist15,
author={David {Adrian Sanders}. and Alexander Gegov.},
title={Post Processing Method that Acts on Two-dimensional Clusters of User Data to Produce Dead Bands and Improve Classification},
booktitle={Proceedings of the 11th International Conference on Web Information Systems and Technologies - WEBIST},
year={2015},
pages={267-272},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005473202670272},
isbn={978-989-758-106-9},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Web Information Systems and Technologies - WEBIST
TI - Post Processing Method that Acts on Two-dimensional Clusters of User Data to Produce Dead Bands and Improve Classification
SN - 978-989-758-106-9
IS - 2184-3252
AU - Adrian Sanders, D.
AU - Gegov, A.
PY - 2015
SP - 267
EP - 272
DO - 10.5220/0005473202670272
PB - SciTePress