7. The method of claim 6 , wherein said computing, using the programmed processor, one or more insights for users' preferences comprises: computing, by said processor, an intra-application feature snapshot for each version of each application from one or more built feature evolution models; computing, by said processor, an inter-application feature snapshot for each category of applications in a certain timestamp from said one or more built feature evolution models; and computing, based on a computed an intra-application feature snapshot, a computed inter-application feature snapshot, or both a computed an intra-application feature snapshot and a computed inter-application feature snapshot, an insight extraction rule relating to one or more feature insights for user preferences to be extracted and generated.
7. The method of claim 6 , wherein said computing, using the programmed processor, one or more insights for users' preferences comprises: computing, by said processor, an intra-application feature snapshot for each version of each application from one or more built feature evolution models; computing, by said processor, an inter-application feature snapshot for each category of applications in a certain timestamp from said one or more built feature evolution models; and computing, based on a computed an intra-application feature snapshot, a computed inter-application feature snapshot, or both a computed an intra-application feature snapshot and a computed inter-application feature snapshot, an insight extraction rule relating to one or more feature insights for user preferences to be extracted and generated. 8. The method of claim 7 , wherein said computed one or more insights for users' preferences comprises: a surprising feature, a must-have feature, a failure feature, a co-occurring feature, a continuously-improved feature, a seldom-but-interesting feature.