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In this paper, we design a five-sided educational data mining framework (5S-EDMF) to analyze college students' diligence and effectiveness of study, and to recommend learning resource accordingly. We noticed data collected from students' E-learning activities to reveal a lot about the attitudes and behaviors of students online as well as offline. This provides us an additional valuable tool to access...
The cumulative growth of data from various sources has led to the era of big data. Big Data analytics give rise opportunities in designing of competitive offer packages for customers to provide reliable services, but analysis must be accurate and timely for successful decision making. For testing and analyzing Big Data, various statistical methods are developed. Traditional statistical analysis focuses...
Stock market is basically nonlinear in nature and the research on stock market is one of the most important issues in recent years. People invest in stock market based on some prediction. For predict, the stock market prices people search such methods and tools which will increase their profits, while minimize their risks. Prediction plays a very important role in stock market business which is very...
Data mining techniques have been proposed to predict mortality for ICU patients using their demographic data, measurements and notes from doctors and nurses. Most of these techniques suffer from two main drawbacks. First, they model the mortality prediction problem as a binary classification problem, while ignoring the time of death as continuous values. Second, they use topic models to analyze the...
Data mining and analytics have played an important role in knowledge discovery and decision making/supports in the process industry over the past several decades. As a computational engine to data mining and analytics, machine learning serves as basic tools for information extraction, data pattern recognition and predictions. From the perspective of machine learning, this paper provides a review on...
In recent years, online social networks have gained tremendous popularity because of the massive number of online users, the fast spread of information, and strong inter-personal influence. However, due to the high complexity of the user interaction and the real-time changing of the online social networks, it is still a big challenge to model the spreading process of the information delicately and,...
Due to the rapid development of network information, e-commerce has entered the era of big data. From these large data mining the useful information has a high commercial value, especially for short life cycle products, improve it in each stage of life cycle prediction ability, in addition to some of the conventional data mining model depends on the specific data mining platform, and can't realize...
Investigating human mobility patterns and comprehending the social dynamics that govern people movements is of high interest for multiple aspects and reasons. Location-based services, mobile network management, and urban planning are just few of the several applications that benefit fromthis kind of assessment. This work focuses on the stochasticanalysis of spatiotemporal and social network data in...
Educational Data mining is a varied subject and unwary research field which are supposed taken care of the tremendous data which are arising in the educational field. The exploring data is formed as a data set and then various computational techniques are applied to derive an interesting pattern out of it with which further analysis, decisions can be done for the re-modeling of learning pattern, enhancement...
In terms of the retail commodity sale forecast, people did more in particular aspect with commodity's single sale attribute such as the sale volume, the sale money, the season factor, but all has not considered the most important factor-profit, the profit is the key factor of retail enterprises winning the survival and development. However, such a one-sided analysis is not conducive to assist the...
Education helps people develop as individuals. It not only helps build social skills but also enhances the problem solving and decision making skills of individuals. With the growing number of schools, colleges and universities around the globe, education now has taken new dimension. The main focus of higher Educational Institutes is to improve the overall quality and effectiveness of education. Predicting...
The data streams in many applications are characterized by imbalanced class distribution. The pattern in data streams may also change over time and therefore, the classification model should be adjusted to maintain performance. Hence, a new set of labeled samples should be provided which is not an easy task, since labeling is expensive and time consuming. In this paper, we propose Reduced Labeled...
In order to explain the reason of the high underpricing rate of IPO and to judge whether there exists IPO underpricing, combined with China's specific policy system, this paper classified the IPO first-day underpricing or discount and constructed a classifier by using the decision tree modeling under the multiple influence factors. The numbers listed in this article refer to the data of initial public...
In the 21st Century, China's mobile communications has a huge space for development. The emergence of independent of the 4th generation mobile communication technology provides an unprecedented opportunity for the development of China's mobile communications. As the world's largest telecom operator, China Mobile Communications Corporation has become the leader of promoting China's 4th generation mobile...
As data become big and complex, it is also more challenging to data scientists to extract useful information in a timely fashion. Although many tools and packages are available to them, it is crucial to have a high productive and scalable big data analytics platform to carry out their daily work productively. The objective for our work is to build such a productive data analytics cloud platform by...
Data Analysis is key to understand the importance of accumulated data over a period of time. The importance of the accumulated data is understood by the data analyst over period of time. The authors had shown the importance of the data collected of the higher education by finding the new and un-identified facts using the statistically techniques. The authors found that the regression techniques could...
In a regular retail shop the behavior of customers may yield a lot to the shop assistant. However, when it comes to online shopping it is not possible to see and analyze customer behavior such as facial mimics, products they check or touch etc. In this case, clickstreams or the mouse movements of e-customers may provide some hints about their buying behavior. In this study, we have presented a model...
Based on the state of the art of process mining, we can conclude that quality characteristics (failure rate metrics or loops) are poorly represented or absent in most predictive models that can be found in the literature. The main goal of this present research work is to analyze how to learn prediction model defining failure as response variable. A model of this type can be used for active real-time-controlling...
This work is based upon the results of an evaluation process applied over data mining techniques, in order to find the most adequate ones to extract classification rules from first-year students' academic and demographic data in relation with their academic performance. As a result of this, the formulation of a predictive model for academic performance is presented; model whose construction was achieved...
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