2008/03/04 by Marco Franciosi, Franciosi, Marco, Giulia Menconi +1
Computer Science · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Multimedia (cs.MM) #Neural Networks and Applications #Time Series Analysis and Forecasting #cs.IR #cs.MM
paper · pdf · doi:10.48550/arxiv.0803.0405
Keywords: multimedia mining, trend, entropy, Zipf law
arxiv created 2008/03/04 · openalex publication_date 2008/03/04 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We show an analysis of multi-dimensional time series via entropy and statistical linguistic techniques. We define three markers encoding the behavior of the series, after it has been translated into a multi-dimensional symbolic sequence. The leading component and the trend of the series with respect to a mobile window analysis result from the entropy analysis and label the dynamical evolution of the series. The diversification formalizes the differentiation in the use of recurrent patterns, from a Zipf law point of view. These markers are the starting point of further analysis such as classification or clustering of large database of multi-dimensional time series, prediction of future behavior and attribution of new data. We also present an application to economic data. We deal with measurements of money investments of some business companies in advertising market for different media sources.