
doi: 10.1007/11495772_62
Sequential pattern mining is an important task for Web usage mining. In this paper we generalize it to the problem of mining context based patterns, where context attributes may be introduced both for describing the complete sequence (e.g. characterizing user profiles) and for each element inside this sequence (describing circumstances for succeeding transactions). Such patterns provide information about circumstances associated with the discovered patterns what is not present in the traditional patterns. Their usefulness is illustrated by an example of analysing e-bank customer behaviour.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
