A Transaction Specification and Management Environment (TSME) is a programmable system that supports: (i) implementation-independent specification of application-specific extended transaction models (ETMs), and (ii) configuration of transaction management mechanisms (TMMs) to enforce specified ETMs. The TSME can ensure correctness and reliability while allowing the functionality required by wor...

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...

The successful adoption of inter-organizational systems (IOS) requires the cooperation of participating firms with complex business and economic relationships. This study examines the impact of inter-organizational relationships on the adoption and diffusion of a category of IOS called Electronic Data Interchange (EDI) that supports the electronic transmission of business documents between two ...

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...

The present paper describes a three stage technique to parse Hindi sentences. In the first stage we create a model with the features of head words of each chunk and their dependency relations. Here, the dependency relations are inter-chunk dependency relations. We have experimentally fixed a feature set for learning this model. In the second stage, we extract the intra-chunk dependency relation...

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...