Abstract
The technologies aimed at Web content discovery, retrieval and management face the compelling need of coping with its highly dynamic nature coupled with complex user interactions. This paper analyzes the temporal patterns of the content changes of three major news websites with the objective of
modeling and predicting their dynamics. It has been observed that changes are characterized by a time
dependent behavior with large
fluctuations and significant differences across hours and days. To explain this behavior, we represent the change patterns as time series. The trend and seasonal components of
the observed time series capture the weekly and daily periodicity, whereas the irregular components
take into account the remaining
fluctuations. Models based on trigonometric polynomials and ARMA
components accurately reproduce the dynamics of the empirical change patterns and provide extra-
polations into the future to be used for forecasting.
Lingua originale | English |
---|---|
pagine (da-a) | 115-123 |
Numero di pagine | 9 |
Rivista | Journal of Network and Computer Applications |
Volume | 2015 |
DOI | |
Stato di pubblicazione | Pubblicato - 2015 |
Keywords
- Time series analysis
- Web dynamics