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Advisor(s)
Abstract(s)
Audiometer systems provide enormous amounts of detailed TV watching data. Several relevant and interdependent factors may influence TV viewers' behavior. In this work we focus on the time factor and derive Temporal Patterns of TV watching, based on panel data. Clustering base attributes are originated from 1440 binary minute-related attributes, capturing the TV watching status (watch/not watch). Since there are around 2500 panel viewers a data reduction procedure is first performed. K-Means algorithm is used to obtain daily clusters of viewers. Weekly patterns are then derived which rely on daily patterns. The obtained solutions are tested for consistency and stability. Temporal TV watching patterns provide new insights concerning Portuguese TV viewers' behavior.
Description
Keywords
Clustering Data reduction People meter data Temporal visualization patterns TV
Citation
DATIA, N.; [et al] – Temporal patterns of TV watching for Portuguese viewers. Portuguese Conference on Artificial Intelligence Location:. Univ Beira Interior, Covilha, Portugal: IEEE, 2005. ISBN 978-0-7803-9365-3. Pp. 151-158.
Publisher
IEEE