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This paper analyzes the development status of intelligent tourist guide system and studies Apriori-based association rule algorithm with corresponding improvement. Then this paper puts forward a weighted association rule algorithm. The algorithm comprehensively takes in to account nature, behavior and situation of tourists, to put forward three aspects of improvement in defects of efficiency and accuracy...
Indonesia is an earthquake-prone country which surrounded by tectonic plate boundary and ring of fire area. In 2016, there are 14 times of earthquake rates ≥ 5 Richter on average per month occurred in Indonesia. Because the high rates of earthquake in Indonesia connected in earthquake tectonic plate boundary, it is important to analyze a causal-effect relationship between earthquake hit in several...
Recently, multi-label classification has gained prime importance among the classification problems. The applications of classification problems has increased so rapidly that the need for efficient and accurate classifiers has become a vital requirement in the area of data mining. Multi-label classification problem is distinguished from the single label classification because of the capability to handle...
No Evidence of Disease (NED) is breast cancer patient condition status which it indicates that they can life, no find the cancer by tested, and without any symptoms of cancer in period of times, after they received primary treatment. NED is a critical status, because it involves the treatment type and patient cancer condition factors. This paper examines about breast cancer problem in data mining...
It is important to predict consumers' location and motion in a large shopping mall to provide them better service. When a consumer passes regions of a shopping mall, his/her moving trace can be recorded for prediction. Existing approaches cannot be directly used to fulfill such task because handling the ordered region sequences is quite challenging. In this paper, we propose an improved Apriori algorithm...
In this paper, we propose a cost function that corresponds to the mean square errors between estimated values and true values of conditional probability in a discrete distribution. We then obtain the values that minimize the cost function. This minimization approach can be regarded as the direct estimation of likelihood ratios because the estimation of conditional probability can be regarded as the...
Although there have lots of studies on using static code attributes to identify defective software modules, there still have many challenges. For instance, it is difficult to implement the Apriori-type algorithm to predict defects by learning from an imbalanced dataset. For more accurate and understandable defect prediction, a novel approach based on class-association rules algorithm is proposed....
Apriori algorithm is a classic mining algorithm which can mining association rules and sequential patterns. However, when the Apriori algorithm is applied to contiguous sequential pattern mining, it is inefficient. In web log mining, the contiguous sequential pattern can better represent the semantic information of the user's access to the site due to the continuity of the user's visit to the site...
Crimes are a social irritation and cost our society deeply in several ways. Any research that can help in solving crimes quickly will pay for itself. About 10% of the criminals commit about 50% of the crimes [9]. The system is trained by feeding previous years record of crimes taken from legitimate online portal of India listing various crimes such as murder, kidnapping and abduction, dacoits, robbery,...
Frequent Itemset Mining is one of the most investigated fields of data mining. It is expensive to mine frequent itemsets for a large scale data set. Especially when some data is added into the data set, it is still time-consuming from the scratch to re-compute the complete data set to update the frequent itemsets of the data set. Aiming to improve the performance of frequent itemset mining for large...
Association Rule Mining is a well-liked in data mining. Mostly Apriori algorithm is used for market basket analysis but this Apriori algorithm have few limitations like scan database again and again for finding frequent itemset, more access time. etc. This limitation is reduced by using vertical datasets in Eclat algorithm with ACO Technique is called E-ACO algorithm. We propose in this paper, memory...
Data mining is also known as knowledge discovery from huge data sets. Potential useful information also comes out from data set through data mining. This outcome is important for existing data sets and for further analysis, development and planning. This paper put a light on performance evaluation, based on the correct and incorrect instances of data classification using different classification algorithm...
Kernel tracing facilitates to demonstrate various activities running inside the Operating System. Kernel tracing tools like LTT, LTTng, DTrace, FTrace provide details about processes and their resources but these tools lack to extract knowledge from it. Pattern recognition is a major field of data mining and knowledge discovery. This paper presents a survey of widely used algorithms like Apriori,...
Recommender Systems are information filtering systems that guide the users in selecting the desired items based on the past user-item transactions. Recommender Systems have become the vital role in recent years and are utilized widely in various areas of social importance. The proposed work aims in recommending the most suitable touring facilities that include customized places recommender and formation...
There have been a lot of researches about aging. Our study suggests a new research method using RTEL (Regulator of Telomere Elongation Helicase). Telomere is the region of repetitive DNA sequence at the end of chromosomes used as a buffer during the DNA replication. We made four sets (each set includes 3 mammals whose lifespan is almost similar) which have different lifespan range, and compared the...
The aim of this article is to describe the design, implementation and evaluation of the educational application to support learning of data mining algorithms. The role of the application is to help students to better understand the algorithms such as Naive Bayes classifier, decision trees and association rules. The application also includes a test area that allows students to generate and solve different...
Nowadays, zika virus infection-occurred in Brazil-is becoming serious global problem. Temporary treatments-using drug-can alleviate symptoms for a while but cannot be a basic solution for infections. We researched amino acids of Zika virus and other four kinds of flaviviruses-Dengue fever, Yellow fever, Saint Louis, Japanese Encephalitis-with bioinformatic experiment; Apriori, K-means and Decision...
This research aims to discover validate the endosymbiotic theory of chloroplast by comparing chloroplast DNA and cyanobacterial DNA using computational methods such as apriori and decision tree. We compared the nucleotide sequences of four plants that each represent four evolutionary classes, bryophytes, pterophyts, gymnosperms, and angiosperms, and Synechococcus DNA. The rules extracted from five...
Recommendation systems are widely used in ecommerce applications. A recommendation system intends to recommend the items or products to a particular user, based on user's interests, other user's preferences, and their ratings. To provide a better recommendation system, it is necessary to generate associations among products. Since e-commerce and social networking sites generates massive data, traditional...
The development of Internet makes plagiarism problem more and more serious. Plagiarism can be in different types, ranging from copying texts to adopting ideas, without giving credit to the original author. Most research in plagiarism checking concentrate on string matching. This method cannot deal with intelligent plagiarism in which the same content can be expressed by different ways. To deal with...
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