Context-Aware Applications - Guide to Cloud Computing for Business and Technology Managers - page 499

• A selection of recommendation(s) and consequent action(s) conform-
ing with the situational constraints judged via the business logic and
other constraints sensed via the context
• Enabling successful closure of the interaction (answering to a query,
qualifying an objection, closing an order, etc.)
23.1 Decision Patterns as Context
This chapter discusses location-based services applications as a particu-
lar example of context-aware applications. But, context-aware applications
can significantly enhance the efficiency and effectiveness of even routinely
occurring transactions. This is because most end-user applications' effective-
ness and performance can be enhanced by transforming them from a bare
transaction to a transaction clothed by a surround of a context formed as an
aggregate of all relevant decision patterns utilized in the past.
The decision patterns contributing to a transaction's context include the
following:
• Characteristic and sundry details associated with the transaction
under consideration
• Profiles of similar or proximate transactions in the immediately
prior week or month or 6 months or last year or last season
• Profiles of similar or proximate transactions in same or adjacent or
other geographical regions
• Profiles of similar or proximate transactions in same or adjacent or
other product groups or customer groups
To generate the context, the relevant decision patterns can either be dis-
cerned or discovered by mining the relevant pools or streams of primarily
the transaction data. Or they could be augmented or substituted by conjec-
turing or formulating decision patterns that explain the existence of these
characteristic pattern(s) (in the pools or streams of primarily the transaction
data). In the next subsection we look at function-specific decision patterns
with particular focus on financial decision patterns.
Thus, generation of context itself is critically dependent on
employing big data and mobilized applications, which in turn
needs cloud computing as a prerequisite.