A survey on the integration models of multi
... It was defined for datasets with two views but it was later generalized to data with more than two representations in several ways (Kettenring, 1971 - Batch, ...
... It was defined for datasets with two views but it was later generalized to data with more than two representations in several ways (Kettenring, 1971 - Batch, ...
Spatio-Temporal Outlier Detection in Precipitation Data
... The Exact-Grid Top-k algorithm finds the top-k outliers for each time period by keeping track of the highest discrepancy regions as they are found. As it iterates through all the region shapes, it may find a new region that has a discrepancy value higher than the lowest discrepancy value (kth value) ...
... The Exact-Grid Top-k algorithm finds the top-k outliers for each time period by keeping track of the highest discrepancy regions as they are found. As it iterates through all the region shapes, it may find a new region that has a discrepancy value higher than the lowest discrepancy value (kth value) ...
Spammer Detection by Extracting Message Parameters from Spam
... was short (i.e. where the total count of words was less) Emails that include differentiating punctuations like a sentence that always end with an exclamation mark (!) or question mark (?) or style are easy to identify using this stylistic clustering. Semantic clusters yield good results when the sem ...
... was short (i.e. where the total count of words was less) Emails that include differentiating punctuations like a sentence that always end with an exclamation mark (!) or question mark (?) or style are easy to identify using this stylistic clustering. Semantic clusters yield good results when the sem ...
Clustering Game Behavior Data - Game Analytics Resources v
... of thousands of simultaneously active users spread across hundreds of instances of the same virtual environment [7]. Each player controls one or more characters with up to hundreds of abilities that evolve over time. While playing, users can perform dozens of actions per minute which lead to hundred ...
... of thousands of simultaneously active users spread across hundreds of instances of the same virtual environment [7]. Each player controls one or more characters with up to hundreds of abilities that evolve over time. While playing, users can perform dozens of actions per minute which lead to hundred ...
Nearest-neighbor chain algorithm
In the theory of cluster analysis, the nearest-neighbor chain algorithm is a method that can be used to perform several types of agglomerative hierarchical clustering, using an amount of memory that is linear in the number of points to be clustered and an amount of time linear in the number of distinct distances between pairs of points. The main idea of the algorithm is to find pairs of clusters to merge by following paths in the nearest neighbor graph of the clusters until the paths terminate in pairs of mutual nearest neighbors. The algorithm was developed and implemented in 1982 by J. P. Benzécri and J. Juan, based on earlier methods that constructed hierarchical clusterings using mutual nearest neighbor pairs without taking advantage of nearest neighbor chains.