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The effective bandwidth management in multi-service computer networks such as university networks has become a challenge in recent years. The growth of internet traffic and limitation of bandwidth resources persuade the information technology (IT) managers to focus on effective bandwidth allocation policies. One of the important issues discussed in this domain is how to assign the bandwidth fairly...
An approach based on decision rules algorithm and multi-features was proposed for desertification monitoring in Turpan Oasis using SPOT images. At first, the common methods such as principal component transformation, tasseled cap transformation and minimum noise fraction transformation were used to extract spectral feature, and vegetation index as well as wetness index were also calculated. Elevation...
The Indian economy can possibly turn into the world's third biggest economy by the following decade, and one of the biggest economies by mid-century. What's more, the viewpoint for transient development is additionally great as indicated by the IMF, the Indian economy is the “splendid spot” in the worldwide scene, this paper analyses the most important factor that will result in understanding the...
The memory performance of data mining applications became crucial due to increasing dataset sizes and multi-level cache hierarchies. Decision tree learning is one of the most important algorithms in this field, and numerous researchers worked on improving the accuracy of model tree as well as enhancing the overall performance of the learning process. Most modern applications that employ decision tree...
Hypertension is one of the leading causes of human deaths world. Based on data from the WHO in 2013, that there are more than 17 million people worldwide died of cardiovascular disease. While in Indonesia, based on the Basic Health Research in 2013, there were 25.8 percent of Indonesia's population suffering from hypertension [1] [2]. This research is develops a system of prediction of prognosis in...
Education is one of the primary requirements for leading a good life. In India, still a large section of population is not educated, which makes them lag behind everyone. For overall development of our country, the citizens have to be educated and consequently employed. This paper analyses the most important factor that will result in the improved education level of our country, using data mining...
Today, Relational databases are used to store structured and complex data. They consist of multiple relations that are linked together conceptually via entity-relationship links. While the need to analyze these complex and structured data now have been increased, but many traditional learning techniques mine a single table as input and could not meet this requirement. So Multi-relational data mining...
Big data is one of the latest technologies that have the potential for radically changing the way organizations use information to enhance the customer experience and transform their business models. The healthcare industry has been handling large amounts of data and is largely driven by compliance, regulatory requirements, record keeping and similar aspects of patient care. The goal is to introduce...
Data mining rely on large amount of data to make learning model and the quality of data is very important. One of the important problem under data quality is the presence of missing values. Missing values can occur in both at the time of training and at the time of testing. There are many methods proposed to deal with missing values in training data. Many of them resort to imputation techniques. However,...
GPS and WIFI Positioning Technology bases on Intelligent mobile phone terminal, it collects a certain number of big data for a positioned student sample in a specific period, uses clustering algorithm to the massive data, removes some meaningless noise data, renders the result of cluster analysis based on the platform for two-dimensional geographic information system, according to the actual 2D map...
This paper introduces a new methodology for digital design properties extraction from simulation traces. The innovated methodology is based on a new data mining technique guided with static analysis of the intended design. The mining engine of the proposed methodology is based on innovated Breadth-First Decision Tree (BF-DT) search algorithm. The data structure of each node in the decision tree is...
A central challenge in education is to match instruction to the characteristics and learning styles of students in order to optimize learning. In this article, we intend to outline our approach to supporting personalized learning strategies by constructing dynamical student profiling using ubiquitous computing capability. This profiling includes recorded data on students' affective responses to learning...
In today's economic transformation setting round the globe, there has been a growing interest in Human Resources Management (HRM) of corporations and their consequence on revenues of these corporations. Yet, there are some challenges and issues in deciding about the best people with talents and recommending them for rising in financial gain or promotion based on some features which are vital for the...
Data Mining is an analytical process designed to explore data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data. The overall goal of data mining is to extract information from a dataset and transform it into useful structure for further use. This can help in building new systems...
The challenge to choose the best algorithm and its best parameters for a given problem is known as Combined Algorithm Selection and Hyperparameter Optimization Problem. Among all the classification algorithms available are those based on human comprehensible representations, such as decision trees and classification rule induction. These algorithms are usually chosen by the clarity of the results...
This paper discusses the features of equipment comprehensive maintenance and the defect of their operations, and generalizes the requirement and development oriented by intelligent decision making of urban rail transit. Then it figures out relations between faulty equipment groups, through massive monitoring data clustering. It also applies the anti-direction decision tree to build model to identify...
Indicators of medical quality is the main basis of medical quality evaluation, predictive analyzing the indicators by using data mining technology, we can find and solve the problems of hospital quality management more timely. The study, basing on the medical homepage records, analyzes the key indicators of the hospital medical quality by decision tree C4.5 algorithm. Decision tree is a prediction...
With the advent of the computer science, the data volume that needed to be processed under many practical situations increases dramatically, challenging many traditional machine learning techniques. Bearing this in mind, we made an intensive study on the optimization of decision tree algorithm and its corresponding porting to the big data analysis in this paper. An optimized genetic algorithm is merged...
As the number of cyber attacks have increased, detecting the intrusion in networks become a very tough job. For network intrusion detection system (NIDS), many data mining and machine learning techniques are used. However, for evaluation, most of the researchers used KDD Cup 99 data set, which has widely criticized for not showing current network situation. In this paper we used a new labelled network...
Aspect extraction is an important step in opinion mining to identify aspect in customer review products. Most existing works defines the pattern set manually or using heuristic approach. In this paper, we propose learning-based approach using decision tree and rule learning to generate pattern set based on sequence labelling. The patterns will be used to identify and extract aspect in customer product...
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