With the ever-growing database sizes, we have enormous quantities of data, but unfortunately we c... more With the ever-growing database sizes, we have enormous quantities of data, but unfortunately we cannot use raw data in our day-today reasoning/decisions. We desperately need knowledge. This knowledge is in most cases in the gathered data, but the extraction of it is a very time and resources consuming operation. Association rule mining is a central problem in discovering knowledge. It finds interesting association or correlation relationships among a large set of data items. The paper presents some considerations about distributed association rules mining together with a comparison between three representative distributed algorithms, namely CDA, FDM and DDM. The compared algorithms are presented together with some experimental data that leads to the final conclusions.
2021 16th International Conference on Engineering of Modern Electric Systems (EMES), 2021
We are currently witnessing an impetuous development of blockchain technology in various fields l... more We are currently witnessing an impetuous development of blockchain technology in various fields like business, supply chains, or personal identity protection. Another technology that is becoming more widespread is the Internet of Things (IoT), which can be found in a lot of smart applications. In this paper, we aim to study how blockchain finds its utility in IoT applications. Finally, we analyze comparatively the reliability and availability of centralized and decentralized blockchain oracle mechanisms that provide data from IoT devices.
Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05), 2005
Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt... more Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. The Apriori [1], [2], [3] algorithm is the first algorithm which uses the Apriori property to prune the search space. Later Han, J. ...
Abstract. With the huge amount of information available online, the World Wide Web is a fertile a... more Abstract. With the huge amount of information available online, the World Wide Web is a fertile area for data mining. Application of data mining techniques to the World Wide Web, referred to as Web mining, has been the focus of several recent research projects and papers. In ...
Association rule mining is a central problem in discovering knowledge. It findsinteresting associ... more Association rule mining is a central problem in discovering knowledge. It findsinteresting association or correlation relationships among a large set of data items. In this paper,the horizon of frequent pattern mining is expanded by extending single-level algorithmsfor mining multilevel ...
Abstract: Finding frequent itemsets is one of the most investigated fields of database mining. Th... more Abstract: Finding frequent itemsets is one of the most investigated fields of database mining. The classic association mining based on a uniform support misses interesting patterns of low support or suffers from the bottleneck of itemset generation. A better solution is to exploit ...
2009 3rd International Workshop on Soft Computing Applications, 2009
Abstract There are two basic ways in which the basic procedures can be speeded up: speeding up e... more Abstract There are two basic ways in which the basic procedures can be speeded up: speeding up each addition and reducing the number of additions required. Faster addition can be achieved through the use of progressively faster adders (carry-ripple adder, carry-complete full ...
2007 2nd International Workshop on Soft Computing Applications, 2007
Abstract In this paper, we propose a genetic algorithms procedure for solving optimal danger co... more Abstract In this paper, we propose a genetic algorithms procedure for solving optimal danger control system design where choices on the type of components to be used and their assembly configuration are driven by reliability objective with the economic costs associated to the ...
2007 2nd International Workshop on Soft Computing Applications, 2007
Abstract - Finding frequent itemsets is one of the most investigated fields of data mining. In th... more Abstract - Finding frequent itemsets is one of the most investigated fields of data mining. In this paper, the horizon of frequent pattern mining is expanded by extending single-level algorithms for mining multi-level frequent patterns. There are presented two algorithms that extract ...
Abstract: The paper is the result of the authors' activities concerning the testing and the ... more Abstract: The paper is the result of the authors' activities concerning the testing and the design for testability for digital systems. In the beginning of this paper we analyze some of the properties of patterns generated by a Multiple Input Signature Register (MISR). The results of this ...
2009 3rd International Workshop on Soft Computing Applications, 2009
Abstract-The problem of deriving association rules from data was first formulated in [9] and is c... more Abstract-The problem of deriving association rules from data was first formulated in [9] and is called the market-basket problem. This paper presents an efficient version of APRIORI algorithm for mining multi-level association rules in large databases to solve market-basket ...
Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05), 2005
With the widespread computerization in business, government, and science, the efficient and effec... more With the widespread computerization in business, government, and science, the efficient and effective discovery of interesting information from large databases becomes essential. Previous studies on data mining have been focused on the discovery of knowledge at single ...
With the ever-growing database sizes, we have enormous quantities of data, but unfortunately we c... more With the ever-growing database sizes, we have enormous quantities of data, but unfortunately we cannot use raw data in our day-today reasoning/decisions. We desperately need knowledge. This knowledge is in most cases in the gathered data, but the extraction of it is a very time and resources consuming operation. Association rule mining is a central problem in discovering knowledge. It finds interesting association or correlation relationships among a large set of data items. The paper presents some considerations about distributed association rules mining together with a comparison between three representative distributed algorithms, namely CDA, FDM and DDM. The compared algorithms are presented together with some experimental data that leads to the final conclusions.
2021 16th International Conference on Engineering of Modern Electric Systems (EMES), 2021
We are currently witnessing an impetuous development of blockchain technology in various fields l... more We are currently witnessing an impetuous development of blockchain technology in various fields like business, supply chains, or personal identity protection. Another technology that is becoming more widespread is the Internet of Things (IoT), which can be found in a lot of smart applications. In this paper, we aim to study how blockchain finds its utility in IoT applications. Finally, we analyze comparatively the reliability and availability of centralized and decentralized blockchain oracle mechanisms that provide data from IoT devices.
Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05), 2005
Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt... more Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. The Apriori [1], [2], [3] algorithm is the first algorithm which uses the Apriori property to prune the search space. Later Han, J. ...
Abstract. With the huge amount of information available online, the World Wide Web is a fertile a... more Abstract. With the huge amount of information available online, the World Wide Web is a fertile area for data mining. Application of data mining techniques to the World Wide Web, referred to as Web mining, has been the focus of several recent research projects and papers. In ...
Association rule mining is a central problem in discovering knowledge. It findsinteresting associ... more Association rule mining is a central problem in discovering knowledge. It findsinteresting association or correlation relationships among a large set of data items. In this paper,the horizon of frequent pattern mining is expanded by extending single-level algorithmsfor mining multilevel ...
Abstract: Finding frequent itemsets is one of the most investigated fields of database mining. Th... more Abstract: Finding frequent itemsets is one of the most investigated fields of database mining. The classic association mining based on a uniform support misses interesting patterns of low support or suffers from the bottleneck of itemset generation. A better solution is to exploit ...
2009 3rd International Workshop on Soft Computing Applications, 2009
Abstract There are two basic ways in which the basic procedures can be speeded up: speeding up e... more Abstract There are two basic ways in which the basic procedures can be speeded up: speeding up each addition and reducing the number of additions required. Faster addition can be achieved through the use of progressively faster adders (carry-ripple adder, carry-complete full ...
2007 2nd International Workshop on Soft Computing Applications, 2007
Abstract In this paper, we propose a genetic algorithms procedure for solving optimal danger co... more Abstract In this paper, we propose a genetic algorithms procedure for solving optimal danger control system design where choices on the type of components to be used and their assembly configuration are driven by reliability objective with the economic costs associated to the ...
2007 2nd International Workshop on Soft Computing Applications, 2007
Abstract - Finding frequent itemsets is one of the most investigated fields of data mining. In th... more Abstract - Finding frequent itemsets is one of the most investigated fields of data mining. In this paper, the horizon of frequent pattern mining is expanded by extending single-level algorithms for mining multi-level frequent patterns. There are presented two algorithms that extract ...
Abstract: The paper is the result of the authors' activities concerning the testing and the ... more Abstract: The paper is the result of the authors' activities concerning the testing and the design for testability for digital systems. In the beginning of this paper we analyze some of the properties of patterns generated by a Multiple Input Signature Register (MISR). The results of this ...
2009 3rd International Workshop on Soft Computing Applications, 2009
Abstract-The problem of deriving association rules from data was first formulated in [9] and is c... more Abstract-The problem of deriving association rules from data was first formulated in [9] and is called the market-basket problem. This paper presents an efficient version of APRIORI algorithm for mining multi-level association rules in large databases to solve market-basket ...
Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05), 2005
With the widespread computerization in business, government, and science, the efficient and effec... more With the widespread computerization in business, government, and science, the efficient and effective discovery of interesting information from large databases becomes essential. Previous studies on data mining have been focused on the discovery of knowledge at single ...
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