[PDF] Top 20 1. Spatial data mining for finding nearest neighbor and outlier detection
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1. Spatial data mining for finding nearest neighbor and outlier detection
... k-nearest neighbor algorithm for top-n query processing in spatial ...the data points nearest to the query ...algorithm, data plane is divided in two half planes using ... See full document
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Outlier Mining Based on Neighbor-Density-Deviation with Minimum Hyper-Sphere
... in data processing. Hawkins describes an outlier intuitively as :“An outlier is an object that deviates so much from other objects as to be suspected that it was generated by a different ... See full document
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A STUDY ON DIFFERENT APPROACHES OF OUTLIER DETECTION IN DATA MINING
... identifies outlier, based on distance between points and nearest neighbor in the ...The outlier is detected as “An object O in a dataset T is a (p, D) considered outlier only, if at ... See full document
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Different Outlier Detection Algorithms in Data Mining: A Review
... stronger outlier than a point with more neighboring within a distance ...for mining outliers which the user does not need to specify the distance parameter ...k nearest neighbor of a ... See full document
6
Survey of Efficient and Fast Nearest Neighbor Search For Spatial Query on Multidimensional Data
... Data mining is concerned with the process of analyzing data available or generated from various sources and it’s bunching into some useful information to be used to attain some predetermined goals ... See full document
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Outlier Detection Technique in Data Mining: A Research Perspective
... stronger outlier than a point with more neighboring within a distance ...for mining outliers which the user dose not need to specify the distance parameter ...k nearest neighbor of a ... See full document
9
Nearest Neighbor Search with Keywords in Spatial Databases
... Nearest neighbor search (NNS) also called as proximity search, similarity search or closest point search, is an optimization problem for finding closest points or similar ...points Nearest ... See full document
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Classification Of Medical Image Data Using K Nearest Neighbor And Finding The Optimal K Value
... of data distortions that exposes higher spatial and temporal ...reconstruction data demands irregularized data ...the data matrix in order to reduce ... See full document
6
Outlier Detection Using Hub, Antihub & Semisupervised approach for Distance based Method
... anomaly detection techniques based on nearest neighbor ...normal data instances occur in dense neighbour hoods, while outliers occur far from their nearest ...of nearest ... See full document
7
SPATIAL OUTLIER DETECTION USING IMPROVED Z-SCORE TEST
... for outlier detection in spatial databases, which depends upon the K-nearest neighbors of each spatial point of the data ...each spatial point to compute the value of a ... See full document
5
Outlier Mining for Removing the Anomalies in High Dimensional Data Using ARVDH Algorithm
... Outlier detection[1] refers detection of data or any thing that deviate from the expected ...of data Application of outlier detection are Fraud detection, ... See full document
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Schubert, Erich (2013): Generalized and efficient outlier detection for spatial, temporal, and high-dimensional data mining. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... + 1 discrete values only), and the average precision is dominated by the precision in the first ...actual outlier detection method nor the evaluation method, but by the automatic score distribution ... See full document
290
Credit Card Nearest Neighbor Based Outlier Detection Techniques
... fraud detection systems has thus become imperative for all credit card issuing banks to minimize their ...Intelligence, Data mining, Fuzzy logic, Machine learning, Sequence Alignment, Genetic ... See full document
7
A NOVEL AND EFFICIENT KNN USING MODIFIED APRIORI ALGORITHM
... between the test and trained samples, rather than all of the attributes. But, the attributes selected have to be the most appropriate ones. By appropriate we mean that they have to be sufficient for determining the class ... See full document
6
An Implementation of Web Recommendation System using Web Usage Mining Technique
... usage mining and web content mining for recommending the most relevant user next web page for ...usage mining evaluates the user behavior and the content mining extract the user ... See full document
7
Prediction of heart disease using data mining techniques: A Case study
... large data is generated from different patient’s symptoms and clinic ...the data in medical sector is computerized but not utilized ...This data can be harnessed to predict diseases such as Cancer, ... See full document
13
A comparative study for outlier detection techniques in data mining
... for outlier detection [7]. On the other hand, Deviation-based outlier detection does not use statistical tests or distance-based measures to identify exceptional ... See full document
6
Outlier Detection and Removal Using Data Mining Techniques
... There are two main ways for noticing intrusions, signature-based and anomaly- based intrusion detection. In the early way, attack outlines or the deeds of the intruder is modeled (attack signature is modeled). ... See full document
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Title: AN ADVANCE APPROACH IN CLUSTERING HIGH DIMENSIONAL DATA
... dimensional data to contain points that frequently occur in k-nearest neighbor lists of other ...dimensional data points and let Nk(y) denote the number of k-occurrences of point y ∈ S, ... See full document
5
Retrieving Datasets with Nearest Neighbor Search using Spatial Queries
... This would become the reality if we could browse the lists synchronously by distances has opposed to by ids. in the particular, has long as we could access the points of all lists in the ascending order of the IR ... See full document
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