In computing system capacity planning, transaction inter-arrival times are assumed to be exponentially distributed. Said another way, given bunch of samples with the average inter-arrival time of 10ms, more of the samples will have an inter-arrival times less then 10ms than greater than 10ms. With a normal distribution you’re likely to see just as many samples greater than and also less than th...

We analyze fundamental characteristics of the inter-firm transaction network through the data of 800,000 Japanese firms. We find that there exists a hierarchical structure and a negative degree correlation in this transaction network. We also find that this undirected network is a scale-free network. We bring to light these characteristics of the network and discuss why there is an important ne...

This paper identifies the basic services required from a communication subsystem to support transaction processing in a distributed, reliable, reconfigurable, and replicated database environment. These services include multicasting, remote procedure calls (RPC), inexpensive datagram services, and efficient local interprocess communication (IPC). We show the evolution of the various versions of ...

Data mining applications in financial sectors are very common since investors can apply the resultant rules to make profits. Profit mining algorithms in particular, such as PRMiner, can generate profit rules that meet the expectations of investors regarding profit, risk, and win rate. However, most of such algorithms are not efficient due to the long processing time involving going through the ...

1 Inadequacy in association rule mining for stock movement prediction Among all the data mining problems, discovering association rules from large databases is probably the most signiicant contribution from the database community to the eld 1, 2, 5, 9, 10, 7]. The most often cited application of association rules is market basket analysis using transaction databases from supermarkets and depart...

Traditional association rules are mostly mining intratransaction associations i.e., associations among items within the same transaction where the idea behind the transaction could be the items bought by the same customer. In our work, we utilize the framework of inter-transaction association rules, which associate events across a window of transaction. The new association relationship breaks t...

For customer transaction database, the support (customer support) of the sequential pattern is defined as the fraction of the customers supporting the sequence. We define new forms of the mining patterns, called cyclic patterns, as an extension to the sequential pattern mining by introducing a new parameter, the repetition support. For customer transaction database, the repetition support speci...

Rare events prediction is a very interesting and critical issue that has been approached within various contexts by research areas, such as statistics and machine learning. Data mining has provided a set of tools to treat this problem when the size as well as the inherent features of the data, such as noise, randomness and special data types, become an issue for the traditional methods. Transac...

In this paper we propose a data mining technique for the efficient prediction of rare events, such as heat waves, network intrusions and engine failures, using inter transactional patterns. Data mining is a research area that attempts to assist the decision makers with a set of tools to treat a wide range of real world problems that the traditional statistical and mathematical approaches are no...