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Different people may have a different learning styles and it is important to provide the most suitable content and course materials for learning. However, determining the learning style may be difficult due to limited information about the learner and lack of a learner profile. The learner has to complete a questionnaire form based on educational theory in order to determine the learning style. Moreover,...
The Document Object Model (DOM) provides a tree structure called DOM tree for representing with objects in HTML. Many researchers have considered using leaf nodes of DOM tree as basic objects in extracting information from web pages. However, web pages are more of information blocks which each have a consistent visual format rather than individual DOM tree nodes. And those information blocks do not...
Insurance telematics is a disruptive technology that is expected to reform the vehicle insurance industry. Based on sensor data, the traditional measures for calculating the insurance premium are complemented to determine a fee that more accurately predicts the risk profile of the policyholder. From an instrumentation and measurement point of view, there are several insurance telematics challenges...
Open source bug tracking systems provide a rich information suite that is actively used by software engineering researchers to design solutions to triaging, duplicate classification and developer assignment problems. Today, open repositories often contain in excess of 100,000 reports, and in cases of RedHat and Mozilla, over a million. Obtaining and analyzing the contents of such datasets are both...
Astrology has started around 4000 years back and has significantly developed over a period of time. Till date no unified rules or standards for astrological prediction exist in the world. Astrologers concentrate on providing quality services to persons rather than defining universal rules and standards for astrological prediction. Advances in artificial intelligence resulted in large number of applications...
With the rapid development of E-commerce, more online reviews for products and services are created, which form an important source of information for both sellers and customers. Research on sentiment and opinion mining for online review analysis has attracted increasingly more attention because such study helps leverage information from online reviews for potential economic impact. The paper discusses...
Malware proliferation has become a serious threat to the Internet in recent years. Most of the current malware are subspecies of existing malware that have been automatically generated by illegal tools. To conduct an efficient analysis of malware, estimating their functions in advance is effective when we give priority to analyze. However, estimating malware functions has been difficult due to the...
The data mining applications such as bioinformatics, risk management, forensics etc., involves very high dimensional dataset. Due to large number of dimensions, a well known problem of “Curse of Dimensionality” occurs. This problem leads to lower accuracy of machine learning classifiers due to involvement of many insignificant and irrelevant dimensions or features in the dataset. There are many methodologies...
Data mining has been an active area of research for the past couple of decades. Classification is an important data mining technique that consists of assigning a data instance to one of the several predefined categories. Various successful methods have already been suggested and tested to solve the problems of the classification. In this paper, author proposed a new hybrid classifier by combining...
The real-world big data can be clustered along desired dimensions but it is limited in its applicability to large-scale problems due to its high computational complexity, user's desire, number of dimensions etc. Recently, many approaches have been proposed to accelerate the large scale data clustering. Unfortunately, these methods usually sacrifice quite a lot of information of the original data;...
User interaction with web sites generates a large amount of web access data stored in the web access logs. Those data can be used for e-commerce to conduct an evaluation of possessed website pages as one of the efforts to understand the desires of the user. Through classification techniques in web usage mining, we conducted an experiment to categorize a number of data obtained from the client log...
Automatic software categorization is the task of assigning software systems or libraries to categories based on their functionality. Correctly assigning these categories is essential to ensure that relevant software can be easily retrieved by developers from large repositories. State of the art approaches either rely on the availability of the source code, or use supervised machine learning approaches,...
Internet Relay Chat (IRC) is a commonly used tool by Open Source developers. Developers use IRC channels to discuss programming related problems, but much of the discussion is irrelevant and off-topic. Essentially if we treat IRC discussions like email messages, and apply spam filtering, we can try to filter out the spam (the off-topic discussions) from the ham (the programming discussions). Yet we...
When enterprises outsource maintenance of IT systems to service providers, thorough knowledge acquisition is critical to the success of the engagement. Program comprehension contributes significantly to acquiring knowledge of the IT systems. It is a common practice to execute test scripts to identify critical scenarios in the system and then trace these as flows in the programs. Instead of executing...
Understanding the severity of reported bugs is important in both research and practice. In particular, a number of recently proposed mining-based software engineering techniques predict bug severity, bug report quality, and bug-fix time, according to this information. Many bug tracking systems provide a field "severity" offering options such as "severe", "normal", and...
Traditional wavelet extraction methods are generally based on the hypothesis of time-invariant seismic wavelet with zero or minimum phase. Additionally, the evaluation of wavelet precision is hard to be performed directly. This paper presents a time-varying mixed-phase wavelet estimation method based on adaptive segmentation, in which quadratic spectrum modeling and higher-order cumulants double spectroscopy...
Classification is a central problem in the fields of data mining and machine learning. Using a training set of labelled 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...
To achieve good performance on Protein sub-nuclear location, one needs to extract a powerful representation containing rich information for identification. Various favorable techniques have been proposed, but it is believed that the single representations, containing one-sided information of protein sequence, are insufficient for discrimination. To this end, we in this paper propose the fused representations...
This paper proposes XCS using Attribute Tracking and Feedback (XCS-ATF) that simultaneously extracts both of the generalized and specialized knowledge, and evaluates its effectiveness by investigating how the extracted knowledge contribute to deriving deep/light sleep of aged persons. The data mining of the daily activities of aged person by XCS-ATF has revealed the following implications: (1) XCS-ATF...
Security is an important aspect in the practical deployment of biometric authentication systems. Biometric data in its original form is irreplaceable and thus, must be protected. This often comes at the cost of reduced matching accuracy or loss of the true key-less convenience biometric authentication can offer. In this paper, we address the shortcomings of current face template protection schemes...
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