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Now-a-days the storage of a huge amount of data is very easy due to use of modern technologies, but the useful information that remains inside that storage media is unknown to us. The data mining provides us different techniques and rules that can be used to analyze and extract unknown rules, hidden patterns and associations from the previously stored data. Data mining technology is well implemented...
Hashing & Pruning is very popular association rule mining technique to improve the performance of traditional Apriori algorithm. Hashing technique uses hash function to reduce the size of candidate item set. Direct Hashing & Pruning (DHP), Perfect Hashing &Pruning (PHP) are the basic hashing algorithms. Many algorithms have been also proposed by researchers. All algorithms have their own...
Electric commerce is a fire-new business mode, and data mining is a promising new technology to transact information. With business information and data being increased exponentially, it is becoming a hot issue for corporations to analyze and utilize the information. This paper firstly describes international trade e-commerce, and discusses the function and the process of data mining. At last, it...
In recent years, vessel traffic and maritime situation awareness become more and more important for countries across the world. AIS data contains much information about vessel motion and reflects traffic characteristics. In this paper, data mining is introduced to discover motion patterns of vessel movements. Firstly, we do statistical analysis for large scale of AIS data. Secondly, we use association...
Database sharing is a necessary task for most of the real world organizations in order to take advantages from organizational cooperation or to find out hidden knowledge buried in their databases, so they can make decisions more precisely. This incurs the risk of sensitive knowledge disclosure which may occur due to malicious use of database. In this paper, we propose two heuristic algorithms called...
One of the Association rule mining (ARM) algorithm, Apriori, is most popular algorithm. Pruning approach used in this algorithm differentiates between potential frequent and infrequent itemset well before verifying them in the given database. An alternate approach known as filtration does the same. In this paper, five experiments are carried out to prove that filtration approach works as efficient...
Privacy preserving data mining (PPDM) has been a new research area in the past two decades. The aim of PPDM algorithms is to modify data in the dataset so that sensitive data and confidential knowledge, even after mining data be kept confidential. Association rule hiding is one of the techniques of PPDM to avoid extracting some rules that are recognized as sensitive rules and should be extracted and...
Due to wide application of management system, information data grows rapidly. On one hand, people have a large number of information resources. On the other hand, the time cost and difficulty of people finding the proper information increases. To tackle the problems, book recommendation is one of the solutions for university libraries which possess huge volumes of books and reading-intensive users...
In the area of Data Mining, We generally use many techniques for data analysis, among them, association rule learning is a well-liked and well researched technique for discover the interesting relations among the variables in large databases. Association rules are a part of intelligent systems because all the intelligent systems are using the associations. Association rules are usually needed to satisfy...
Network traffic prediction for academic organizations is essential to managing and selecting the best routing path. Since overload traffic is a major problem that delays data transmission in network system and causes some data loss, this research demonstrates an approach to predict network traffic on data transmission in the network system by using association rule discovery which is one of the data...
Concept maps can help students learn more meaningfully. According to test scores only, students were divided into three groups of high-score, middle-score and low-score, in the previous works, researchers then applied data mining association rule technique to analysis different student groups' assessment data to construct corresponding concept maps. However, for considering more accurate to evaluate...
Tourism is one of the most significant industries all across the globe. Information technology plays an indispensable role in promoting the industry. We utilized a web crawler to obtain online tourists' demographics and comments. This study adopts a new perspective in analyzing tourists' profiles where both quantitative (data mining) and qualitative analysis methods were performed on the data collected...
Association rules mining is one of the most popular and significant issue in data mining and intends to discovery interest relations between variables in database. In our paper, we implemented an improved parallel Apriori algorithm which realized both count and candidate generation steps under MapReduce framework, while existing parallel Apriori algorithm only considered count step. We analyzed the...
Data mining is an efficient technology to discover patterns in large databases. Association rule mining techniques are used to find the correlation between the various item sets in the database, and this correlation between various item sets are used in decision making and pattern analysis. In recent years the problem of finding frequent items and association rules from large datasets has been proposed...
Due to the existing Apriori association rules data mining algorithms require to scan the database many times and generate a large numbers of candidate sets, which produce giant I/O expense issues, result in low data mining computational efficiency. Matrix algorithms can improve the efficiency in computing frequency 2-itemset, but not delete non-frequency item set before calculation, not effectively...
Considering the cost, safety and competitive of data migration, a distributed association rule mining algorithm based on matrix named DARMO is put forward for some special distributed applications. This algorithm has some characteristics such as high degree of parallelism, fewer database scanning, less communication overhead and low complexity. The correctness of the algorithm is proved theoretically...
In this paper, the authors present a user-centered concept for the operation experience of human-robot interface. For showing a concrete concept of our research, we design an assistant robot system. There are several stages for developing this system. Firstly, it is to obtain user's data. The authors obtained static data from Internet, and activity data from capturing humans' a motion data. The authors...
This paper focuses the concept of data mining and association rules mining algorithm. Apriori algorithm and FP-growth algorithm, which are well-known and important data mining algorithms, are studied. According to the Apriori algorithm for weighted multidimensional data mining, this paper provides an optimized method which searches the candidate itemsets avoiding to scan the database repeatedly in...
Traditional Association Rules algorithm has computing power shortage in dealing with massive datasets. In order to overcome these problems, a distributed association rules algorithm based on MapReduce programming model named MR-Apriori is proposed. In this paper, we introduce the MapReduce programming model of Hadoop platform and Apriori algorithm of data mining, propose the detailed procedure of...
Association rules have been used in data mining applications to capture relationships present among attributes in large data sets. It can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. In order to mine the frequency patterns of texture, each image can be considered as one transaction. If image...
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