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Opinion mining is one of the new concepts of data mining. As World Wide Web is growing at higher rate, this has resulted in enormous increase in online communications. The online communication data consist of feedback, comments and reviews on particular topic that are posted on internet by internet users. Sentiment analysis is a sub-domain of opinion mining where the analysis is focused on the extraction...
In this paper, we propose learning analytic tasks to understand the learning process in a smart classroom. Learning analytics can extract knowledge from a course to better understand students and their learning processes. The learning analytic tasks must evaluate different aspects in the course: the teaching and learning process, the student performance, and the pedagogical practices, among other...
Big Data generated in exabytes per year has become a watchword of today's research. They are exceptionally afar from the capability of commonly used software tools and also beyond the handling possibility of the single machine architecture. Facing this challenge has activated a requisite to reexamine the data management options. The new avenues of NoSQL Big Data compared to the traditional forms has...
Innovation in the public-sector refers to the development of important improvements in the public administration and their corresponding services. One of such public services is the social security, of which central process has been the information security of their offered services. The aim of the present study has been the analysis of the trends and the discovery of behavioural patterns in the attacks...
Chronic pelvic pain is a common clinical condition with negative consequences in many aspects of women's life. The clinical presentation is heterogeneous and the involvement of several body systems impairs the identification of the exact etiology of the problem. At the same time, a clinical treatment of good quality depends on the professional and the learning process is slow. The goal of this paper...
Mechanical and electrical equipments are widely used in industry. Existing electro-hydraulic mixing equipments mainly use expert systems for fault diagnasis. However, in order to increase the accuracy of diagnasis, the expert systems have to acquire more knowledge. And diagnosis system will bring great uncertainty due to limited knowledge. Furthermore, existing fault diagnosis system has the disadvantages...
With the continuous expansion of the data stream applications, the data stream frequent pattern mining is becoming a hot research topic in the field of data mining, the domestic and foreign scholars put forward a large number of data stream frequent itemsets mining algorithms. This paper improves the related definitions of frequent itemsets and sliding windows, classifies sliding windows from data...
Random sampling could enhance classification performance by selecting many representative samples to be included in the training dataset. The representative samples usually include the samples located at the border of each class or cluster. In this paper, a new sampling algorithm has been proposed which enforces the training sample to include the border points between classes. Considering a point...
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...
Data mining algorithms are used to analyze and discover useful information from data. This paper presents an experiment that applies Combinatorial Testing (CT) to five data mining algorithms implemented in an open-source data mining software called WEKA. For each algorithm, we first run the algorithm with 51 datasets to study the impact different datasets have on the test coverage. We select one dataset...
In today's competitive environment, having a customer oriented approach is inevitable for organizations. At this point, in order to achieve customer satisfaction, customer relationship management (CRM) targets to provide products and services which meet customer expectation. Data which is collected about customers is an important source to determine their needs. Therefore, analysis is made to determine...
There is a worldwide trend towards the integration of renewable energy in the form of distributed generation, leading to the formation of microgrids. Connection of these sources introduces new issues in the operation and management of distribution systems. An important issue is that of islanding, where the microgrid remains energized locally while isolated from the main grid. It is important to detect...
Searching useful information without fault from the Web becomes an increasingly difficult task, since the volume of Web data rapidly grows. With the growth rate, unexpected faults of Web service composition may occur in different levels at runtime. These faults are to be identified from Web Log files. The common causes of faults in Web services execution are rectified by fault diagnosis technique...
Medical image analysis is a pioneer research domain due to the challenges posed by different kinds of images and the complexities in attaining the accurate prediction of abnormalities presence. Brain MRI classification into normal and abnormal has received increasing attention because of the high level of difficulty in handling those huge numbers of images. Recently, many computational techniques...
Large amounts of data gets accumulated and stored in the databases in day to day life that are high dimensional in nature. The data mining task is used to excavate the useful information from the high dimensional data. To classify or cluster the high dimensional data, the dimensionality of the data needs to be reduced. Feature selection is used to select the features that are relevant to the analysis...
Now a days people are enjoying the world of data because size and amount of the data has tremendously increased which acts like an invitation to Big data. But some of the classifier techniques like Support Vector Machine (SVM) is not able to handle the huge amount of data due to it's excessive memory requirement and unreasonable complexity in algorithm tough it is one of the most popularly used classifier...
This paper presents, simulate, access and applies the proposed for data classification of medical dataset with aims to classify patients based on medical history. This modified data classification algorithm was formulated using k-Means algorithm. The simulation has been performed by using Real and artificial datasets on MATLAB 7.7.0 and showed that increasing the accuracy of data classification of...
As there is a exponential growth of social networks and due to large usage of social media, there is a increasing demand for data in the web for the users which leads to recent trends and ideas in the field of research. The users will be eagerly using these data for the future purpose and get information about the opinions of others thus there is a need of automatic summarization of opinion of the...
In recent years, type II diabetes has become a serious disease that threaten the health and mind of human. Efficient predictive modeling is required for medical researchers and practitioners. This study proposes a type II diabetes prediction model based on random forest which aims at analyzing some readily available indicators (age, weight, waist, hip, etc.) effects on diabetes and discovering some...
Kidney disease is become a popular disease in around the world. The prediction of kidney disease is highly complex task while handling huge dataset. The kidney disease dataset contain patients information such as age, blood Pressure levels, albumin, sugar, counts of red blood cells etc., in the dataset there may be some missing values in some features that values may be important to predict kidney...
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