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Data mining applied on educational data aims to find useful patterns in large volumes of data in order to transform and optimize educational paths. It involves many steps. This paper presents a case study for a data preprocessing framework for students' outcome prediction using data collected by Moodle system.
This article is about next generation knowledge management technologies. The original approach was to externalize the tacit knowledge of human beings. Store the externalized content, mainly text or data based documents, later multimedia contents. Handle these documents in different data bases, together with their metadata. The new associative data models will be able to handle the stored content units...
Nowadays, high volumes of valuable uncertain data can be easily collected or generated at high velocity in many real-life applications. Mining these uncertain Big data is computationally intensive due to the presence of existential probability values associated with items in every transaction in the uncertain data. Each existential probability value expresses the likelihood of that item to be present...
Web data mining is a key tool for e-commerce in such an age of Internet. Due to previous studies, there is no such a mining technology superior to others. Therefore, this paper can give a simplified comprehension of web data mining and indicate the improvement direction of each kind of mining algorithm based on their existing defects. This paper first introduces the main process of data mining, including...
AHP Construct Mining Component (ACMC), which is a new term, is an enhancement of applicable structure for multidimensional and multi-level complex dataflow. ACMC is applied into data mining framework and different processing components with the purpose are improvement on numerous aspects in multiply level. ACMC provides not only an integrated platform to support different processing components with...
Based on operator SPJ (Select-Project-Join) and the technology of self-maintainable view, this paper proposes a new maintainable model of materialized view; the proposed model contains two processes: the monitoring process and maintenance process, the first process is used to monitor the changes of basic tables; while the second process will automatically update the materialized view by auxiliary...
In the paper we first propose a user preference model with the minimum support intelligent set method. Secondly, we propose a new data mining problem, the structure of the database to find frequent patterns associated pair. To effectively address these problems, we developed a series of cutting ability with a strong algorithm. The new algorithm is also discussed in the one-dimensional and multi-dimensional...
Data mining can efficiently deal with the large number of historical and current data, from the database can find some potential, useful and valuable information for the retail stores. The paper takes a large retail supermarket as its study object, use data mining methods to retail enterprise customer segments, and then use association rules to different groups of customer and get rules about customer...
The paper mainly discussed the Application of the Model_Multi based on Apriori algorithm in Supporting System of Medical Decision. Model_multi is the exploring model of the multi-dimension relational rule. It is used to explore the knowledge from the present database so that the manager of the hospital can manage the hospital through the explored knowledge. The Aprior algorithm calculation of the...
The use of information technology for assist the speech disorder therapy allows collecting a huge volume of data. This data may be the foundation of a data mining process that can offer models, which lead to the optimization of therapy through its personalization. This paper aims to analyze how useful is data mining in logopaedic area and to present a proposed data mining system for optimize the decision...
Knowledge discovery has received more and more attention from the business community for the last few years. One of the most important and challenging problems in it is the definition of discovery process model, which are well understood, efficiency, and quality of outcome. A conceptual infrastructure for knowledge discovery process is proposed with business understanding, model selection and domain...
Data mining aims at extraction of previously unidentified information from large databases. It can be viewed as an automated application of algorithms to discover hidden patterns and to extract knowledge from data. Online Analytical Processing (OLAP) systems, on the other hand, allow exploring and querying huge datasets in interactive way. These OLAP systems are the predominant front-end tools used...
According to the management needs for scientific research projects, this paper propose a framework that combines data warehouse as the basis, OLAP, association rule, and apply it into the projects analysis of Science and Technology Bureau in Handan City. As a practical implementation of the framework, the Handan City Science and Technology Plan Project Implementation Survey System was developed. The...
Knowledge Discovery in Databases (KDD) is a complex interactive and iterative process which involves many steps that must be done sequentially. Supporting the whole KDD process has enjoyed a great popularity in recent years, with advances in research. We however still lack of a generally accepted underlying framework and this hinders the further development of the field. We believe that the quest...
Data mining driven fishbone, which is whole a new term, is an enhancement of abstractive conception of multidimensional-data flow of fishbone applied for data mining to optimize the process and structure of data mining. End-to-end DMDF diagram includes complex dataflow and different processing component and improvements for numerous aspects in multiply level. DMDF provides integrated platform and...
XML has become the standard for data representation on the web. This expansion in reputation has prompted the need for a technique to access XML documents. Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.
Recommendation systems are essentially solving a prediction problem where, given that p items have already been selected or rated by a user, the goal is to propose k target items most likely to be appreciated by her/him. Many models have been proposed to identify these target items but the results are not always satisfactory in practice because they often only include the most popular items and ignore...
With the emergence of large-volume and high-speed streaming data, the recent techniques for stream mining of CFIpsilas (closed frequent itemsets) will become inefficient. When concept drift occurs at a slow rate in high speed data streams, the rate of change of information across different sliding windows will be negligible. So, the user wonpsilat be devoid of change in information if we slide window...
As the quick development of Internet, more and more application of XML data description appears in the Internet. How to access the knowledge we need effectively among numerous XML data is becoming a main research direction. This paper studies the data mining of XML document initially, divides the mining of XML document into structure mining and content mining, introduces the knowledge to analyze by...
An advanced alarm system (AAS) of a NPP (nuclear power plant) is primarily a digital system employing advanced alarm process logics and a VDU (visual display unit) based control and display for the alarms. The role of the AAS is to provide the information necessary to safely shutdown the reactor under all plant conditions, to monitor the plant parameters approaching or exceeding the operating limits...
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