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The paper proposes a methodology for the development of a marketing decision support system using Big Data technology and data mining techniques. The approach was inspired by the CRISP-DM methodology, which is not oriented towards Big Data projects. Therefore, we have modified this methodology with respect to the purpose and technological requirements of the project. The proposed methodology was tested...
Cyberspace offers users and information communication systems the opportunity to interact with each other for business. Data, as the carrier of information, represents the processing content of different business work. In order to improve the quality of data, data cleaning plays an important role in various cyberspace scenarios, such as RFID and sensor, ETL process etc. This paper presents a survey...
Nowadays, in the period of the digitalization and knowledge economy development, majority of activities result in the increase of data that should be captured. In each area of business, there is an increasing urge to extract the knowledge from data in a timely manner in order to be able to make shifts that ensure a competitive advantage. Thus, the knowledge of methods and techniques of big data processing...
Information constructions at colleges have transferred from digitalized campus to intelligence campus. Data switching center makes converting, cleansing, monitoring, comparison and other process to data of each business system, which provides an important support to intelligence campus.
Motivation is fundamental for students to achieve successful and complete learning. Motivation can be extrinsic, i.e., driven by external rewards, or intrinsic, i.e., driven by internal factors. Intrinsic motivation is the most effective and must be inspired by the task at hand. Here, a novel strategy is presented to increase intrinsic motivation toward activities requiring the use of sample data...
Datamining is the process of extracting interesting information of patterns from large databases. One of the most important datamining task and well-researched is the association rules mining. It aims to find the interesting correlation and relations among sets of items in the transaction databases. One of the main problems related to the discovery of these associations that a decision maker faces...
The literature about enterprise architecture (EA) measurement discusses a number of challenges. This systematic mapping survey explores the EA measurement research area to figure out how the research area is structured, look at gaps in EA measurement research, and recommend future improvements. Some of the key findings of this paper show that current research only address a limit perspective on the...
Hiding High Utility Sequential Patterns (HUSPs) is the task of finding the ways how to hide high utility sequential patterns appearing in sequence databases so that the adversaries cannot discover them after hiding. It has become an important research topic in recent years and has been applied in various domains such as business, marketing, stock, health and security, etc. However, few methods have...
Merchant acquirer is a business of acquiring debit card, credit card, and prepaid card transactions using EDC (electronic payment terminals) in merchants. It is included in one of the top business priority areas in PT. XYZ. It is in the area of retail payments and deposits. It increases fees based incomes, cheap funds, and high yield loans. In order to improve its business performance, PT. XYZ needs...
In recent years, a number of Chinese remote sensing satellites, including GF-1, GF-2, ZY-1 02C, have been launched and put into use. Compared with traditional application pattern of individual interpretation, continuous remote sensing images can support a more large scaled application in land and resources, known as the operational application. In this paper, an operational application system, which...
Prefixspan algorithm with GRC constraints which generates sequential patterns by using prefix projected pattern growth approach is implemented. Other than frequency this algorithm also uses gap, compactness and recency constraints during sequential pattern mining process. The gap constraint applies limit on the separation of two consecutive transactions of discovered patterns, recency constraint makes...
One of the important approach in data mining is sequential pattern mining that is used for discovering behaviors of sequential databases. There are various challenges in sequential pattern mining such as efficiency and effectiveness. In this paper different sequential pattern mining algorithm are discussed such as GSP, FreeSpan, PrefixSpan, and CAI-PrefixSpan to improve performance to finding sequential...
The location of business is indispensable for all commercial activities. However, current partition of commercial area mostly depends on human experience and other subjective factors rather than intelligent decisions, which is likely to mislead people who want to engage in business. The new combination of algorithms in this paper aims to clarify how the commercial area is formed by visualizing whether...
Big-data middle layer architecture is defined to perform the query analysis and the evaluation of the Big Data. This scheme is implemented on dynamic generated data section. The concept of Big Data concerns with a bulk of data presented in large volume with complicated architecture and with increasing data set. The data for such system can be taken from multiple sources and sometimes from independent...
Mining frequent patterns is a crucial task in data mining. Most of the existing frequent pattern mining methods find the complete set of frequent patterns from a given dataset. However, in real-life scenarios we often need to predict the future frequent patterns for different tasks such as business policy making, web page recommendation, stock-market behavior and road traffic analysis. Predicting...
Primary user emulation (PUE) attacks are an emerging threat to cognitive radio (CR) networks in which malicious users imitate the primary users (PUs) signals to limit the access of secondary users (SUs). Ascertaining the identity of the devices is a key technical challenge that must be overcome to thwart the threat of PUE attacks. Typically, detection of PUE attacks is done by inspecting the signals...
In many applications such as dynamic social network and customer behavioral analysis, the data intrinsically have many dimensions and can be naturally represented as high-order tensors. In this study, a SVM ensemble learning method is proposed for classification using tensor data. The method is used in identifying cross selling opportunities to recommend personalized products and services to customers...
The emerging growth and evolution of web based systems and services make the job of audit professionals a complicated and time-consuming one for many enterprises. In this context, continuous process auditing (CPA) systems in the form of audit-as-a-service (AaaS) emerges as an inexpensive and effective approach. A CPA system helps to satisfy process auditing needs and recommendations in the context...
With the appearance of computer network, could computing, the internet of things, big data more and more get the attention of people. Understanding and Application big data, and make a scientific decision, become the most necessary and urgent problem. Big data, not only let the database have always been known for efficient and secure storage embarrassed, but also allow the data warehouse that provide...
User online shopping preference mining is the key point on user found, e-commerce marketing and user personalized recommendation. A method for Online shopping preference analysis based on MapReduce is proposed in this paper. The campus network traffic is analyzed using MapReduce model, in which the features of user online shopping behavior are extracted by four MapReduce jobs using deep packet inspection...
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