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A number of algorithms are available in the areas of data mining, machine learning and pattern recognition for solving the same kind of problem. But there is a little guidance for suggesting algorithm to use which gives best results for the problem at hand. This paper shows an approach for solving this problem using meta-learning. The paper uses three types of data characteristics. Simple, information...
During the last two decades, the credit card system has been widely used as a mechanism to drive the global economy to grow dramatically. A credit card provider has issued millions of credit cards to its customers. However, issuing credit cards to wrong customers can be a crucial factor of a financial crisis, e.g., the ones happened in 1997 and 2008. This paper presents a systematic analysis and a...
It is a generally accepted fact that the Airport is the focal point of the country which creates a lasting impression of its people. The challenge faced by airports today is the complexity of players and processes, and the inability of multiple systems to share and analyze data. In order to face this challenge, many airports have implemented isolated solutions. While these solutions may improve specific...
Tweet data on Twitter as microblogging can be processed to be an important and useful information. We propose opinion mining with Support Vector Machine (SVM) algorithm to classify tweet opinion data which is a huge data. This opinion mining will be used to get insight of public opinion about State Islamic University of Sunan Gunung Djati Bandung which is one of large university in Indonesia. We have...
In recent years, data mining techniques has been used widely to address the problem of huge data sets stored on huge, heterogeneous data warehouses and may be located in different sites. Rapid growth of data arise in many areas like healthcare, social media, science, Internet…etc. Multi-agent technology has improved the processing of such huge data by the use of the agent technology along with data...
Customer feedbacks are the mile stones for the success functionality for the companies. A producer will get the correct result of his product from the customer feedback. He can make necessary changes to his product according to the feedback. But most users always fail to give their feedbacks. To avoid the difficulty of providing feedback, this paper focus on the technique of providing automatic feedback...
Opinion mining has become the center of attention for many researchers and scientists. That's because people share their thoughts and opinions as texts precisely in microblogs such as on Facebook and Twitter. This research presents a process for opinion mining of Tweeps, the people who tweet on Twitter. The immigration topic was chosen specifically in comparison with other important topics of politics...
Intensive Care Unit (ICU) admission is a major factor that affects the healthcare budget. ICU cost is extremely high because its resources are consumed through highly advanced equipment providing quality healthcare service for patients. Thus, the need for a predictive model for the decision to transfer stroke in-patients to the ICU is very important. Also, this predictive model will help to lower...
This paper explores opinion mining using supervised learning algorithms to find the polarity of the student feedback based on pre-defined features of teaching and learning. The study conducted involves the application of a combination of machine learning and natural language processing techniques on student feedback data gathered from module evaluation survey results of Middle East College, Oman....
Intrusion detection systems monitor network or host packets in an attempt to detect malicious activities on a system. Anomaly detection systems have success in exposing new attacks, commonly referred to as ‘zero’ day attacks, yet have high false positive rates. False positive events occur when an activity is flagged for investigation yet it was determined to be benign upon analysis. Computational...
The advancement of information technology has made public health management system more efficient on keeping an eye on major outbreaks like dengue fever than before. Vigorous prediction of dengue fever not only helps the management to act faster but also helps medical professionals to treat and suggest a good solution to the patients. In this context, this paper aims to develop an intelligent computing...
The development of the concept of business intelligence and analysis has emphasized the importance of the collection, integration, processing of data and reporting of underlying knowledge and how this knowledge can help to make more appropriate business decisions, acquire a better understanding of market behaviors and trends. Tremendous growth of the data has enabled us to uncover the hidden knowledge...
Inspired by the coming of data-driven innovation and economy, an increasing number of companies over the world are eager to analyze their data for creating useful knowledge, while graph data have become more and more crucial in many areas, such as social networks and medical/chemical applications. Different from conventional transaction data, finding the frequent patterns in a graph is more challenging...
A new diagnostic scheme is presented for ball bearing localized faults based on pattern recognition (PR) methods, which utilize preprocessed time domain features. The features are statistically processed (FP) using their central tendency (CT) estimations, prior to the classification process. Vibration data is acquired from faulty bearings, and the features are extracted to form data set. The FP algorithm...
Classification of web content is an interesting and widely pursued field of research in machine learning. Web classification could be done in various ways based upon the criteria chosen. Subjective classification involves classification of web pages based upon the subject to which these pages belong (say history, economics, politics, etc.). Another way of classifying web pages could be based upon...
It is difficult to choose a best feature subset for the power system transient stability assessment(TSA) problem, and the existing data mining methods for TSA lack sufficient considerations for these situations that wrongly classify unstable samples as stable ones. In response to these deficiencies, this paper proposes a multi-support vector machine (SVM) power system TSA method based on relief algorithm...
In airline service industry, it is difficult to collect data about customers' feedback by questionnaires, but Twitter provides a sound data source for them to do customer sentiment analysis. However, little research has been done in the domain of Twitter sentiment classification about airline services. In this paper, an ensemble sentiment classification strategy was applied based on Majority Vote...
Student performance classification is a challenging task for teacher and stakeholder for better academic planning and management. Data mining can be used to find knowledge from student data to improve the performance of classifying model. Before applying a classification model, feature selection method is proposed in data preprocessing process to find out the most significant and intrinsic features...
Most of the service providers and product based companies while launching brand new products, services or releasing new versions of existent products need to campaign to reach at the potential customers. While doing so they target their already existing customers who are the ambassadors of their company. To address the existing customers, they maintain the detailed customer data at all levels as customer...
This paper presents the improved algorithm for the Hybrid Approach of Neural network and Level-2 Fuzzy set (HANN-L2F). The main structure is including 2 parts. The first part is Neuro-Fuzzy system, including the MLP Neural network with the combination of the level-2 Fuzzy system. The second part is using k-nearest neighbor to classify the output from Neuro-fuzzy. The HANN-L2F is an algorithm with...
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