A semantic extension-based classification algorithm for short texts, ie, Set-CNN, is proposed
in this paper. The proposed Set-CNN features three aspects. First, a semantic extension …

The distribution network has typically been the least observable and most dynamic and
locally controlled element in the power grid. Complete information about the network …

High-dimensional data is interpreted with a considerable number of features, and new
problems are presented in groups. The so-called" high dimension" is initially created to …

Existing deep learning methods for clustering high-dimensional data perform feature
selection and clustering separately, which can result in the exclusion of some important …

One of the biggest threats of internet communication system is data theft. To handle this
number of technologies like encryption algorithms, firewall, and intrusion detection system …

The objective of clustering ensemble is to fuse multiple base partitions (BPs) to find the
underlying data structure. It has been observed that sample can change its neighbors in …

Grouping similar flight trajectories into a cluster, or a pattern, is an important data
preprocessing step for data-driven methods in air traffic control as it affects the performance …

At present, there is no method to predict or monitor patients with AMI, and there is no specific
treatment method. In order to improve the analysis of clinical influencing factors of acute …

Abstract Software Defect Prediction (SDP) is an important method to analyze software
quality and reduce development cost. Data from software life cycle has been widely used to …

Deploying a solution for handling critical decision-based problem efficiently requires the
processing of high-dimensional data. Over the years, due to modern technological …