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Numerous spatiotemporal datasets are available in databases across several science and technology fields. One common example of spatiotemporal data is a satellite-derived time-series image. In this study, a method for extracting the recurrence of temporal changes highly correlated with a specific time-series subsequence in its spatiotemporal neighborhood is developed using a criterion based on support...
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.
Many applications such as intelligent tutoring system (ITS) use data that are better represented as binary data. This paper presents a novel algorithm called MBER (Mining Binary Data Efficiently by Reduced AND operations) for finding frequent itemsets in a binary dataset using matrix algebra operations. Frequent itemsets are sets of items in a transactional database that occur together frequently...
Frequent itemset mining is the technique used mostly in field of data mining like finance, health care system. We are focusing on methodologies for extracting the useful knowledge from given data by using frequent itemset mining. Most important use of FIM is customer segmentation in marketing, shopping cart analyzes, management relationship, web usage mining, and player tracking and so on. Association...
Association rule mining is one of the significant tasks in data mining. In literature, several approaches for finding interesting association rules have been proposed. Finding association rules is a two phase process. The first phase finds frequent itemsets or patterns and the second phase generates association rules. The phase that detects the frequent itemsets consumes more time and efforts. Thus...
Bacterial colonies perform a cooperative distributed exploration of the environment. This paper describes bacterial colony networks and their skills to explore resources as a tool for mining association rules in databases. The proposed algorithm is designed to maintain diverse solutions to the problem at hand, and its performance is compared to other well-known bio-inspired algorithms, including a...
Power ramp estimation is utmost importance for wind power plants which will be the focus of this paper. Power ramps are caused by intermittent supply of wind power generation. This is an important problem in the power system that needs to keep the load and generation at balance at all times while any unbalance leads to price volatility, grid security issues that can create power stability problems...
The traditional association rule mining Apriori algorithm in time overhead, in view of the shortcomings of the Apriori algorithm, based on the theory of relational algebra using relationship matrix and related operations are the search for frequent item sets of association rules based on relational algebra theory of mining algorithm, by simulation experiment to compare the execution time of the two...
With the advent of smart grids, the volume of data from metering and information about consumers to be storaged and analysed by the distribution companies will be very large, mainly due to the use of advanced metering infrastructure and digital meters with automatic readers. This new scenario has stimulated these companies to develop intelligent computing systems which can handle data and information...
To assess the performance of a cellular wireless network such as GSM, UMTS and LTE etc., performance counters are logged and maintained by the network management system (NMS). Due to the complexity of a network, the number of these performance counters is typically very large, and the analysis of these data is very difficult. In a typical situation, only a few number of key performance indicators...
This paper presents the formalized apparatus of mining inter-dimensional association rules in multidimensional data, their representation by means of templates, and also the method of all frequent item sets generation in multidimensional data with help of which association rules can be generated by preset templates.
Because of large amounts of unstructured text data generated on the Internet, text mining is believed to have high commercial value. Text mining is the process of extracting previously unknown, understandable, potential and practical patterns or knowledge from the collection of text data. This paper introduces the research status of text mining. Then several general models are described to know text...
Techniques for efficient mining of frequent patterns have been studied extensively by many researchers. However, the previously proposed techniques still encounter some performance bottlenecks when mining databases with different data characteristics such as, dense vs. sparse, long vs. short patterns, memory-based vs. disk-based, etc. In this study, explored the unifying feature among the internal...
Data mining techniques is a popular research area. Association rule mining is the technique used to detect rules and patterns. One of the most well-known techniques is the Direct Hashing and Pruning (DHP) algorithm. This algorithm tries to find associations among the various data items in the date warehouse. In this paper, the attempt was made to optimize this algorithm further by changing its data...
Currently, insurance fraud spreads quickly in the domestic and foreign field, especially in the field of automobile insurance, so that we need more efficient and accurate technology to anti automobile insurance fraud. Therefore, this paper studied the data mining technology to anti automobile insurance fraud. The improved outlier detection method based on the nearest neighbor with pruning rules was...
Sequential pattern mining is valuable approach to uncover consumer buying behaviour from huge sequence database. Weather prediction, web log analysis, stock market analysis, scientific research, sales analysis, and so on are the application of sequential pattern mining. The pattern that is recent and profitable can't discover by conventional sequential pattern mining. So, RFM-based sequential pattern...
Radio Frequency Identification (RFID) is a useful ICT technology for E-logistics Enterprises. One of the standards used for RFID is Electronic Product Code Information Services (EPCIS). However, it is nontrivial to get effective knowledge from massive data to improve the existed production or logistic system comparing with convenient data collection. In this paper, we develop an intelligent platform...
Association rules is one of the important studies on data mining, while, the study of quantitative association rules mining is lacking. This paper proposes a fuzzy association rules mining algorithm FMFFI (Fast Mining Fuzzy Frequent Item sets) based on bidirectional search. This algorithm uses FCM clustering technique to map quantitative data sets into fuzzy data sets, and uses the bidirectional search...
Earlier association rule data mining was mainly used for analysis of market basket data but now the scope has widened. It is experimented in various areas where extraction of interesting correlations can help like healthcare, education systems, manufacturing engineering, network management, intelligence etc. As android is a new technology which came into use from 2008 only, very few researchers have...
Data mining, a need in the modern era of technology where data matters the most, is a prodigious role player. Among the existing techniques of data mining, Association rule is one of the most important tasks which is devoted to discover frequent itemsets and draw the correlations among the items in them. In the recent researches for association rule mining, different supporting threshold and pruning...
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