Cristin-resultat-ID: 1536635
Sist endret: 5. januar 2018 16:37
Resultat
Vitenskapelig artikkel
2016

Identifying user habits through data mining on call data records

Bidragsytere:
  • Filippo Maria Bianchi
  • Antonello Rizzi
  • Alireza Sadeghian og
  • Corrado Moiso

Tidsskrift

Engineering Applications of Artificial Intelligence
ISSN 0952-1976
e-ISSN 1873-6769
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2016

Beskrivelse Beskrivelse

Tittel

Identifying user habits through data mining on call data records

Sammendrag

In this paper we propose a frameworks for identifying patterns and regularities in the pseudo-anonymized Call Data Records (CDR) pertaining a generic subscriber of a mobile operator. We face the challenging task of automatically deriving meaningful information from the available data, by using an unsupervised procedure of cluster analysis and without including in the model any a priori knowledge on the applicative context. Clusters mining results are employed for understanding users' habits and to draw their characterizing profiles. We propose two implementations of the data mining procedure; the first is based on a novel system for clusters and knowledge discovery called LD-ABCD, capable of retrieving clusters and, at the same time, to automatically discover for each returned cluster the most appropriate dissimilarity measure (local metric). The second approach instead is based on PROCLUS, the well-know subclustering algorithm. The dataset under analysis contains records characterized only by few features and, consequently, we show how to generate additional fields which describe implicit information hidden in data. Finally, we propose an effective graphical representation of the results of the data-mining procedure, which can be easily understood and employed by analysts for practical applications.

Bidragsytere

Filippo Maria Bianchi

  • Tilknyttet:
    Forfatter
    ved Institutt for fysikk og teknologi ved UiT Norges arktiske universitet

Antonello Rizzi

  • Tilknyttet:
    Forfatter

Alireza Sadeghian

  • Tilknyttet:
    Forfatter

Corrado Moiso

  • Tilknyttet:
    Forfatter
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