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Social networking portals serve as an ideal platform for a person or an organization, to accomplish self-presentation and self-enhancement goals there by to understand their social relevance and hence, there have been many studies attempting to identify the relationship between different aspects of social media articles. Machine learning methods play a critical role in social media data analytics...
Graduate employability is an increasingly major concern for academic institutions and assessing student employability provides a way of linking student skills and employer business requirements. Enhancing student assessment methods for employability can improve their understanding about companies in order to get suitable company for them. So, enhanced employability prediction of student can help them...
Good nutrition is an essential component of life. Undernutrition is the root cause of death of over 3.5 million children under the age of five in India. To address this issue of malnutrition, though overarching national policy is desirable, it may not be effective if the root cause of malnutrition varies across regions of the country. In this context, the attempt made in this paper is two-fold. First,...
Process Mining is a technique to automatically discover and analyze business processes from event logs. Discovering concurrent activities often uses process mining since there are many of them contained in business processes. Since researchers and practitioners are giving attention to the process discovery (one of process mining techniques), then the best result of the discovered process models is...
In this study, a novel intelligent relaying scheme is proposed for fault classification and faulted phase selection using magnitude of differential power (MODP). The DP is the multiplication of difference between the magnitude of the real and estimated voltage and current phasors. The MODP for each phase is used as an input data to the data mining model known as decision tree (DT). The DT is used...
Autonomic nervous system (ANS) is a control system that acts largely unconsciously and regulates bodily functions. An autonomic malfunction can lead to serious problems related to blood pressure, heart, swallowing, breathing and others. A set of dynamic tests are therefore adopted in ANS units to diagnose and treat patients with cardiovascular dysautonomias. These tests generate big amount of data...
ID3 decision tree data mining is a popular and widely studied data analysis technique for a range of applications. In this paper, we focus on the privacy-preserving ID3 decision tree algorithm on horizontally partitioned datasets. In such a scenario, data owners wish to learn the decision tree result from a collective data set but disclose minimal information about their own sensitive data. In this...
The problem faced by the company is how to determine potential customers and apply CRM (Customer Relationship Management) in order to perform the right marketing strategy, so it can bring benefits to the company. This research aims to perform clustering and profiling customer by using the model of Recency Frequency and Monetary (RFM) to provide customer relationship management (CRM) recommendation...
Determining threshold values of key economic security indices describing an economic situation in any country is an important stage in the assessment of the country's economic stability. Threshold values must be periodically reevaluated due to their continuous deterioration as far as the global economic environment is undergoing changes. The authors offer a rough estimate method for achieving this...
Decision tree model is one of data mining method for builds classification models in the form of a tree structure. These methods are produced various ways of splitting a data set into branch like segments that call nodes. Today, forecasting method is very importance for every side especially agriculture. Because some farmers who want to predict their crops for each semester. This paper describes about...
Supervision is important in the application of Smart City. Closed-Circuit Television (CCTV) is one of the main tools of Smart City surveillance. Some CCTVs connected with Information and Communication Technology (ICT) form Smart Monitoring. In order to support Smart Mobility, CCTV is installed to monitor road conditions. The problem is the installation of CCTV which is not always appropriate with...
We present our preliminary results on building a framework for analyzing online ratings. There are four major components constructed in this framework including data retrieval, data processing, data analytics, and data visualization. The data retrieval module is responsible for scraping or streaming online rating data. Cleaning, filtering, and parsing unstructured data are done in the data processing...
Intelligent Tutoring Systems (ITS) are typically designed to offer one-on-one tutoring on a subject to students in an adaptive way so that students can learn the subject at their own pace. The ability to predict student performance enables an ITS to make informed decisions towards meeting the individual needs of students. It is also useful for ITS designers to validate if students are actually able...
In the big data era, machine learning has become an increasingly popular approach for data processing. Data could be in various forms, such as text, images, audios, videos and signals. The essence of machine learning is to learn any patterns from features of data. In the above types of data, the number of features is massively high, which could result in the presence of a large number of irrelevant...
For supporting interpretation, assessment and application of data mining models, explanation-aware methods are crucial. This paper presents an approach for explanation-aware feature selection and assessment using symbolic abstractions of time series. For that, we utilize the symbolic approximate aggregation (SAX) method for data abstraction to be implemented into data mining models. We investigate...
This paper aims to identify lead users from an online user innovation community. Based on three dimensions of user characteristics — user activeness, community influence, and user relations, a Random Forest classification model for lead user identification is proposed. Using the data from the MIUI forum of Xiaomi community, this model is tested. The result shows that Random Forest classification based...
This study proposed a new method of urban impervious surface extraction from very high resolution (VHR) imagery, by combining spatial and spectral unmixing and decision tree classification. Endmember classes were first defined, where two shadow endmembers were used. Spatial homogeneity and spectral purity were fused to extract endmembers, i.e., spatial and spectral endmember. A modified multiple endmember...
A decision tree is an important classification technique in data mining classification. Decision trees have proved to be valuable tools for the classification, description, and generalization of data. J48 is a decision tree algorithm which is used to create classification model. J48 is an open source Java implementation of the C4.5 algorithm in the Weka data mining tool. In this paper, we present...
Recruitment and selection of new employees rank to the important processes of human potential management and development. Especially the process of employee selection prepares proper conditions for a successful work performance and decides on a future progress-ability of the organizations. In a unique sector of private security, the precise realization of employee selection can solve one of the most...
In this paper we propose a methodology for extracting complex sales expert rules by analyzing the data from the past lost/won deals stored in Customer Relationship Management Systems.
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