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Public policy is the critical key of the welfare programs. It is also a powerful instrument to achieve a feasible national competitiveness. Unfortunately, many public policy making processes does not utilize an appropriate data and tool in holistic and systematical approach. This research will focus on creating a comprehensive conceptual framework for public policymaking based on data and system approach...
Big data technology refers to the rapid acquisition of valuable information from various types of large amounts of data. It can be divided into 8 technologies: data acquisition, data access, infrastructure, data processing, statistical analysis, data mining, model prediction and results presentation. The paper presents improved statistical analysis method based on big data technology. A statistical...
This paper discusses a new decision-support system that integrates data warehouse, knowledge warehouse and model warehouse. Contrast to the fixed model of the old decision-support system and its limited application, the new system can overcome the shortcoming of the old system efficiently, and also it can simplify model-obtaining and coding. So the new system strengthens the effectiveness, intelligence...
Many filtering algorithms have been developed to extract the digital terrain model (DTM) from dense urban light detection and ranging data or the high-resolution digital surface model (DSM), assuming a smooth variation of topographic relief. However, this assumption breaks for a middle-resolution DSM because of the diminished distinction between steep terrains and nonground points. This letter introduces...
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...
Botnet is a malicious software that can perform malicious activities, such as (Distributed Denial of Services) DDoS, spamming, phishing, key logging, click fraud, steal personal information and important data, etc. Botnets can replicate themselves without user consent. Several systems of botnet detection have been done by using a machine learning method with feature selection approach. Currently,...
Software refactoring aims at optimizing software modularization by improving internal software structure without altering its external behavior. There exists various approaches for suggesting refactoring opportunities, based on different sources of information, e.g., structural, semantic, and historical. In this paper, we propose a data fusion model to combine different sources of information in order...
Recently convolutional neural networks (CNNs) have essentially reached the state-of-the-art accuracies in image classification and recognition. CNNs are usually deployed in server side or cloud to handle tasks collected from mobile devices, such as smartphones, wearable devices, unmanned systems and so on. However, significant data transmission overhead and privacy issues have made it necessary to...
With advances in technology, high volumes of a wide variety of valuable data of different veracity can be easily collected or generated at a high velocity in the current era of big data. Embedded in these big data are implicit, previously unknown and potentially useful information. Hence, fast and scalable big data science and engineering solutions that mine and discover knowledge from these big data...
The widespread adoption of Electronic Health Records (EHRs) has enabled data-driven approaches to clinical care and research. However, the performance and generalizability of those approaches are severely hampered by the lack of syntactic and semantic interoperability of EHR data across institutions. Towards resolving this problem, Common Data Models (CDMs) can be used to standardize the clinical...
Discriminating Distributed Denial of Service (DDoS) from Flash Crowds (FC) is a tough and challenging problem, because there are many similarities between each other existed in network layer. In this paper, according to an extensive analysis of user traffic behavior of DDoS and FC, it can be found that some traffic abnormalities are existed between Bots and legitimate users. So a behavior-based method...
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...
This paper proposes a combination of data mining and natural language processing technology, try to analyze students' learning behavior and content in MOOCs interactive part, to dig their learning interest, difficulty, tendencies, to evaluate their homework effect, through the interaction between teachers and students, students posting, homework or answer content, preventing of cheating behavior,...
With the continued growth of the mobile game market, many game companies aim to make money through mobile games. In this situation, knowing the tendency of gamers and predicting the churn in advance can maximize profit through effective game services. For this reason, much study has been conducted for the purpose of gamer analysis and churn prediction. However, the study was mainly conducted using...
Data mining technology is the key technology and core content of big data age. The undergraduate data mining course introduces the basic concepts, basic principles and application techniques of data mining, as well as the characteristics and new technologies of data mining under the background of big data. According to the characteristics of undergraduate students, the curriculum should weaken the...
In the era of the Internet, people are active in multiple online services, and they usually have accounts on more than one online service. Each account is a virtual identity of the user. In order to trace individual's online behavior at any time and any places, linking virtual identities belonging to the same natural person across different online service domains is very important. Existing methods...
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...
For the quality of the wine big data identification technology, the introduction of data mining classification algorithm, effectively according to the content of several impact compounds in wine level identification;Are introduced including the Logistic regression and BP neural network and SVM classification algorithm, in view of the three algorithms identify the modeling analysis of wine quality...
Learning analytics a variant of educational data mining is a process of collection, analysis and reporting of data about learners and their contexts. Analyzing performance of students is a challenging and important task. Use of temporal association mining methods of data mining technique can be a better solution for real time student performance analysis. By using association rule mining approach,...
The amount of data being created and processed daily has grown exponentially with the introduction of the internet and social media. While the data are available, there is a struggle to determine how to effectively use and interpret the data. One of the most popular uses for the large quantities of data is to create models to predict the behavior or tendencies. One important application of prediction...
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