نتایج جستجو برای: banking industry and sliding window
تعداد نتایج: 16871873 فیلتر نتایج به سال:
Objectives The recent shift, from merely traditional approach providing only financial services to the new trend implying banks can be considered as business partners meeting their whole financial needs and creating a win-win relationship, in customers’ opinion towards banks has made banks try to apply banking marketing strategies to help attract more customers and respond to their needs. Hence...
High utility pattern (HUP) mining over data streams has become a challenging research issue in data mining. The existing sliding window-based HUP mining algorithms over stream data suffer from the level-wise candidate generationand-test problem. Therefore, they need a large amount of execution time and memory. Moreover, their data structures are not suitable for interactive mining. To solve the...
In an evolving Nigerian banking industry, strategies are being adopted by the major players in order to achieve their long-term organizational goals-profitability and survival. In the light of this belief, much emphasis is being laid on the computerization of their banking operations. Within the last decade, the Nigerian banking industry has been at the forefront of computerization. This is wit...
Many organisations are starting to use social media for business purposes, although some industries are more advanced than others. This paper looks at the banking industry, and focuses specifically on how senior executives in this industry perceive social media and its value. Hence this paper is an exploratory interpretive study of the attitudes of senior banking executives to social media. Ass...
Clustering queries over sliding windows require maintaining cluster memberships that change as windows slide. To address this, the Generic 2-phase Continuous Summarization framework (G2CS) utilizes a generation based window maintenance approach where windows are maintained over different time intervals. It provides algorithm independent and efficient sliding mechanisms for clustering queries wh...
Sliding-window analysis has widely been used to uncover synonymous (silent, d(S)) and nonsynonymous (replacement, d(N)) rate variation along the protein sequence and to detect regions of a protein under selective constraint (indicated by d(N)d(S)). The approach compares two or more protein-coding genes and plots estimates d(/\)(S) and d(/\)(N) fro...
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