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In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large dataset. While generating frequent item sets from a large dataset using association rule mining, computer takes too much time. This can be improved by using artificial bee colony algorithm (ABC). The Artificial bee colony algorithm is an optimization algorithm based on the foraging...
Depression a latest epidemic of modern era has always drawn the attention of researcher's to find & evaluate the level, causes & prevention. According to psychiatrists it's not a psychological disorder but it creates the stimulation & simulation of co-ordination failure. The worst case of the leading depression level may contemplates a person to attempt suicide, loss of energy,...
Nosocomial Infections (NI) have been the major causes of morbidity and mortality of patients in intensive care units (ICUs) particularly in developing countries. Intensive surveillance and preventive measures is an effective element to fight against NI. Based on the temporal data recorded daily in the intensive care unit (ICU) and the help of some physicians, we plan to develop a Clinical Dynamic...
Proteins perform most important biochemical reactions in organisms, such as the catalysis, signal transduction, and transport of nutrients. The urgent need of automatic annotation is due to the advent of high-throughput sequencing techniques in the post-genomic era. Proteins consist of domains which are elementary building units of protein folding, function, and evolution. The evidence of protein...
This article proposes a simple frequent pattern mining algorithm using link structure. The “LinkRuleMiner” has a distinct feature that it has a very limited and precisely predictable main memory cost and runs very quickly in memory based settings. Moreover, it can be scaled up to very large databases using database partitioning. This article analyzes the coloring process of dyeing unit using newly...
This paper presents a relational compound collaborative filtering (RCCF) recommendation system architecture, which integrated the behaviors associated mechanism and recommendation system to calculate the area associated values and the corresponding region of the recommended items rating, resulting in top-N list of the recommended item values. This system can avoid interested items in the MU¡¦s opposite...
In continuous Speech Recognition, for the problem of recognizing speaker's voice completely and accurately is difficult, and could not understand the meaning even if the machine could identify the voice completely. The improved algorithm is proposed innovatively based on association logic Apriori algorithm. The algorithm divide database into correlated partitions and locate the voice condition in...
In this paper, we present a Failure Prediction System (FPS) using a novel algorithm that extracts frequent anomalous behaviors based on multi-scale trend analysis of multiple network parameters. The proposed Correlation Analysis Across Parameters algorithm (CAAP) utilizes multiple levels of timescale analysis to reveal the frequent anomalous behaviors. The CAAP philosophy is that failures usually...
Time Related Association rule mining is a kind of sequence pattern mining for sequential databases. In this paper, a method of Generalized Association Rule Mining using Genetic Network Programming (GNP) with MBFP(Multi-Branch and Full-Pathes) processing mechanism has been introduced in order to find time related sequential rules more efficiently. GNP represents solutions as directed graph structures,...
To gain the competitive advantage in today's age of technology, growing data and to bear the competitive pressure, making strong decisions according to customer's need and market trend has become very important. With huge amount of data on internet, web data mining has become very significant. Web Usage helps companies to produce productive information pertaining to the future of their business function...
For Enterprise, how to discover the useful data, fresh knowledge and information in order to help decision makers quickly and accurately from the data ocean is an important question, this gives theorists and practitioners' new research direction. SJEP simulation algorithm which based on the logistics information platform can help maker decisions quickly and accurately to achieve the control of the...
This paper introduces improving rate and proposes the incremental mining algorithm with the weighted model for optimizing association rules based on CBA mining algorithm. The risk analysis of the strong association rules is proposed for trend forecasting. And the risk degree of the lost rules based on the incremental mining is also analyzed. Comparing with the traditional algorithm, the improved algorithm...
We propose here an efficient data mining algorithm to hide collaborative recommendation association rules when the database is updated, i.e., when a new data set is added to the original database. For a given predicted item, a collaborative recommendation association rule set [10] is the smallest association rule set that makes the same recommendation as the entire association rule set by confidence...
In dynamic databases, new transactions are appended as time advances. This may introduce new association rules and some existing association rules would become invalid. Thus, the maintenance of association rules for dynamic databases is an important problem. In this paper, probability-based incremental association rule discovery algorithm is proposed to deal with this problem. The proposed algorithm...
A new predictive modelling approach known as associative classification, integrating association mining and classification into single system is being discussed as a better alternative for predictive analytics. Our paper investigates the performance issues of significant associative classifiers likes CMAR and CPAR. Performance comparisons observe that CPAR achieves improved performance as compared...
This paper introduces improving rate and proposes the incremental mining algorithm for optimizing association rules based on CBA mining algorithm. Comparing with the traditional algorithm, the improved algorithm is fast, efficient in incremental data mining and can find trends in association rules. The decision making reliability is enhanced by the association rules obtained from the improved algorithm...
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