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Clustering is an important tool for analyzing gene expression data. Many clustering algorithms have been proposed for the analysis of gene expression data. In this article we have clustered real life gene expression data via K-Means which is one of clustering algorithms. Also, we have proposed a new method determining the initial cluster centers for K-means. We have compared results of our method...
There are a diverse set of products for a particular type on the internet. When any user tries to find out best product among a certain type it is very much difficult to do it manually go through every one of them. That's why manually searching is not very efficient. In that scenario, recommendation system plays a great important role to recommend the best products. In this study, we develop a recommendation...
How to reduce the computation time and how to improve the quality of the clustering result are the two major research issues. Although several efficient and effective clustering algorithms have been presented, none of which is perfect. As such, an effective clustering algorithm, which is based on the prediction of searching information to determine the search directions at later iterations and employs...
With advances in technology, high volumes of a wide variety of valuable data of different veracity can be easily collected or generated at a high velocity in the current era of big data. Embedded in these big data are implicit, previously unknown and potentially useful information. Hence, fast and scalable big data science and engineering solutions that mine and discover knowledge from these big data...
The problem faced by the company is how to determine potential customers and apply CRM (Customer Relationship Management) in order to perform the right marketing strategy, so it can bring benefits to the company. This research aims to perform clustering and profiling customer by using the model of Recency Frequency and Monetary (RFM) to provide customer relationship management (CRM) recommendation...
The article focuses on the results of the research into scientific publications of the All-Russian Institute for Scientific and Technical Information of the Russian Academy of Sciences database (VINITI Database RAS) in different fields. The purpose of operation was to increase partition accuracy on the directions of large volumes of scientific data. This analysis was carried out on summaries of scientific...
The approaching of big data era makes traditional data storage methods could not accomplish the mass tasks of analysis, managing and mining. While the rise of cloud computing brings new life to parallel improvement of data mining algorithms. Its efficient programming model, massive storage capacity and powerful computing capabilities provide a broad platform for the development of data mining. Hadoop...
The rapid development of the Internet has brought great convenience to users, but it also brought a lot of troubles to the users' information privacy exposure. This study selects the basic information of 300 users on FACEBOOK social media to cluster analysis. The data sets of users are divided into five groups by experiment, and the clustering results are classified and then discussed. By the analysis...
Utilizing data for segmentation analysis can bring a streamlined way to get potential insight as of decision making support in a business organization. Using appropriate data analytical technique help the organizations in profiling their customer segments accurately. The result brings an effective marketing strategy. However, there are times in doing data analytic, the organization needs another variable...
There is no previous research that compares the results of k-means, CLOPE clustering and Latent Dirichlet Allocation (LDA) topic modeling algorithms for detecting trending topics on tweets. Since not all tweets contain hashtags, we considered three training data feature sets: hashtags, keywords and keywords + hashtags in this study. Our proposed methodology proved that CLOPE can also be used in a...
Telecommunications fraud, a new type of crime, is showing a rising trend in recent years. However, research from data mining perspectives to detect such frauds is scarce, especially with the behavioral sequences considered. Though the call detail records (CDRs) in telecommunication is generally a snapshot, the history of a caller/callee can be treated as sequences. Indeed, the historical calling sequences...
The last years, huge masses of data are produced or extracted by computational systems and independent electronic devices. To exploit this resource, novel methods must be employed or the established ones may be altered in order to confront the issues that arise. One of the most fruitful techniques, in order to locate and use information from data sources is clustering, and k-means is a successful...
In the world today, the security of the computer system is of great importance, And in the last few years, there have seen an affected growth in the amount of intrusions that intrusion detection has become the dominant of current information security. Firewalls cannot provide complete protection. Applying on a firewall system alone is not enough to prevent a corporate network from all types of network...
Micro array data play a vital role in simultaneously monitoring the expression profile of large number of genes that are specified with various experimental conditions. In bioinformatics research, the recognition of co-expressed and coherent patterns is a major objective in micro array data analysis. The K-means clustering algorithm is gaining popularity in the knowledge discovery domain for effectively...
Classification is a central problem in the fields of data mining and machine learning. Using a training set of labeled instances, the task is to build a model (classifier) that can be used to predict the class of new unlabelled instances. Data preparation is crucial to the data mining process, and its focus is to improve the fitness of the training data for the learning algorithms to produce more...
Crimes are a social irritation and cost our society deeply in several ways. Any research that can help in solving crimes quickly will pay for itself. About 10% of the criminals commit about 50% of the crimes [9]. The system is trained by feeding previous years record of crimes taken from legitimate online portal of India listing various crimes such as murder, kidnapping and abduction, dacoits, robbery,...
The volume of academic paper submissions and publications is growing at an ever increasing rate. While this flood of research promises progress in various fields, the sheer volume of output inherently increases the amount of noise. We present a system to automatically separate papers with a high from those with a low likelihood of gaining citations as a means to quickly find high impact, high quality...
Currently there are many techniques based on information technology and communication aimed at assessing the performance of students. Data mining applied in the educational field (educational data mining) is one of the most popular techniques that are used to provide feedback with regard to the teaching-learning process. In recent years there have been a large number of open source applications in...
The criminal behavior is a disorderliness that is a combined result of social and economic aspects. The crime rate has expanded and the activities of criminals have broaden in last few decades due to better communication system and transport. Crimes cause terror and damage our community enormously in several means. In cities and towns the crime trends rises due to fast developmental activities and...
Need of effective and efficient Intrusion Detection System, used the concept of hybrid approach in Iintrusion Detection System where many combination of different techniques has been used so far. In this paper, proposed hybrid approach which is the combination of Fuzzy C-Mean (FCM), a clustering technique and Support Vector Machines (SVM) will be compared with K-Means and SVM, K-Means and Naïve bayes,...
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