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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...
At present, all developed countries employing public eProcurement systems create a corpus of generic public procurement fraud schemes. A selection of attributes with fraud suspicion signs is performed. It is necessary to accomplish, first of all, because fraud in the public procurement sphere is one of the most common kinds of frauds. With a view to improve the existing anti-corruption enforcement...
Researchers have designed a decision support system for granting discounts by using the Naïve Bayes method. Naïve Bayes can be used for decisions to grant discounts within a multi-criteria system. The criteria are determined by the company, the purchase of some items, the status of the product, the big day, price ranges. The management system helps the company in providing discounts accordingly. The...
Currently, enterprise systems have been focusing on expenditure services through credit card broadly because it is convenient and quick to pay for products and services. Thus, this research emphasizes on the fraud detection of credit card payment by using the machine learning technique called RUSMRN. The proposed method adopts three base classifiers which are MLP, NB and Naive Bayes algorithms. In...
Today the strategic significance of information is fundamental to any organization. With the intensification of competition between companies in open markets and often saturated, companies must learn to know themselves and to the market through the collection and analysis of quality information. The strategic information is seen as a key resource for success in the business, which is provided by Business...
On the basis of depth study of commercial bank credit risk control model literature, this paper introduced the concepts of credit risk and credit risk control. We research the main influencing factors of commercial bank credit risk control scientifically by artificial neural network theory, and then set a commercial bank credit risk control index system which contains 3 levels of 27 indexes. Improved...
In this work we present a Conversation Classifierbased on Multiple Classifiers, to detect Life Events on SocialMedia. In one hand, conversations can provide more contextand help disambiguate life event detection, compared with single posts. On the other hand, the increase in number of messages and the way they interact with each other within the conversation cannot be trivially modeled by a classifier...
This paper shows the methodology used for analyzing the technical and non-technical skills necessary for defining a university program providing a Data Science certification. The original aspects of the approach consists of the close collaboration between the organizing universities and the collaborating companies. For what concerns the technical skills, the statistics collected by the already existing...
Social media mining from Internet has been an emerging research topic. The problem is challenging because of massive data contents from various sources, especially image data from user upload. In recent years, dictionary learning based image classification has been widely studied and gained significant success. In this paper, we propose a framework for automatic detection of interested uniforms in...
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...
Electric charge is the primary income for the power company. However, collecting electric charge is much difficult due to the existence of the risky consumer which makes the huge impact on the normal operation and development of the company. So the arrear problem of the risky customers has become one of the focus problems. Based on the gettable electric data from some areas, this paper proposed an...
Computer-Assisted Audit Tools and Techniques' use among auditors has been a research topic on information systems' acceptance or adoption. Since the late 70, guidelines and suggestions on Computer-Assisted Audit Tools' use, relating it to auditors' efficacy and efficiency, have been published by professionals, academics and authoritative bodies. In this paper, the main objective is to define statutory...
In recent years software has become integral part of our lives. From product software has become a service now. Software industry has undergone a shift in paradigm. Companies look into every aspect for effective project management. Practitioners have started considering human aspect equally important in the product, process, people triad. Human aspect has become top concern for companies' management...
Fraud is widespread and very costly to the healthcare insurance system. Fraud involves intentional deception or misrepresentation intended to result in an unauthorized benefit. It is shocking because the incidence of health insurance fraud keeps increasing every year. In order to detect and avoid the fraud, data mining techniques are applied. This includes some preliminary knowledge of health care...
Data mining has been recently used in the field of car insurance to help the insurance companies in predicting the customers' choices in order to provide more competitive services. In this composition, the random forest was used to develop a classification model that could be applied in predicting which of the insurance policies would likely to be chosen by the customers. The performance of the developed...
Banks collect large amount of historical records corresponding to millions of credit cards operations, but, unfortunately, only a small portion, if any, is open access. This is because, e.g., the records include confidential customer data and banks are afraid of public quantitative evidence of existing fraud operations. This paper tackles this problem with the application of surrogate techniques to...
In view of the significance of personal performance assessment in the working metrics of human resource management, this study proposes to set up a multi-class Support Vector Machine based model to elaborate how to evaluate the staffs' performance effectively and efficiently. Data samples are collected from a construction company in China, and used to justify the proposed model against the selected...
Class imbalance is a common problem in real world applications and it affects significantly the prediction accuracy. In this study, investigation on better handling class imbalance problem in customer behavior prediction is performed. Using a more appropriate evaluation metric (AUC), we investigated the increase of performance for under-sampling and two machine learning algorithms (weight Random Forests...
Violations of listed companies to disclose accounting information will mislead the ordinary investors seriously and bring huge losses to investors. Therefore, it is particularly necessary to analyze and identify the violations of listed companies based on scientific and effective methods to avoid investment risks in advance. In this paper, we firstly use t-statistic to select eight useful and characteristic...
Telemarketers of online job advertising firms face significant challenges understanding the advertising demands of small-sized enterprises. The effective use of data mining approach can offer e-recruitment companies an improved understanding of customers' patterns and greater insights of purchasing trends. However, prior studies on classifier built by data mining approach provided limited insights...
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