Abundant Unspecified Profile Corresponding During Mobile Social Networks
Utilizing the reasoning processing technology, a new cellular movie loading structure, known as AMES-Cloud,
which has two main parts: AMoV (adaptive cellular movie streaming) and ESoV (efﬁcient public movie sharing)? AMoV
and ESoV build a personal broker to offer movie loading services efﬁciently for each cellular customer. For a given
customer, AMoV lets her undercover broker adaptively adjust her stream ﬂow with a scalable movie programming technique
in accordance with the reviews of link quality. Likewise, ESoV watches the online community communications among
cellular users, and their personal providers try to prefetch movie content in advance. We apply a model of the AMES-Cloud
structure to show its performance. It is shown that the personal providers in the atmosphere can effectively offer the flexible
loading, and perform movie discussing (i.e., prefetching) in accordance with the online community analysis.. We ﬁrst
recommend an precise Comparison-based Proﬁle Related method (eCPM) which runs between two parties, an initiator and a
-responder. The eCPM enable the initiator to acquire the comparison-based matching outcome about a speciﬁed feature in
their proﬁles, while stop their feature values from exposure. We then recommend an implied Comparison-based Proﬁle
Related method (iCPM) which allows the initiator to straight acquire some information instead of the evaluation outcome
from the -responder. The information unique to customer proﬁle can be separated into multiple groups by the -responder.
The initiator unquestioningly selects the involved category which is unknown to the -responder.
Keywords: AMES, AMOV, ESOV, ECPM, ICPM.