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Stroke is a serious condition that can make it impossible for some body parts to move. When blood flow to a portion of the brain is suddenly cut off, a stroke results. A stroke patient needs to receive treatment right away because delaying care could ...

Aiming at the problems of low recommendation accuracy and low user interest in the existing methods, a news recommendation of social media platform based on improved collaborative filtering is designed. The initial key features of news data are ...

Sarcasm is regarded as the enveloping linguistic factor in online documents that describes the deeply-felt subjective and opinions. This paper intends to introduce a sarcasm detection model that classifies words under sarcastic or non-sarcastic forms. ...

The autonomous exploration task we consider requires Unmanned Aerial Vehicles (UAVs) to actively navigate through unknown environments with the goal of fully perceiving and mapping the environments. Some existing exploration strategies suffer from rough ...

Due to the large number of customers and diverse interest characteristics in e-commerce trading platforms, there are many problems such as large classification errors, low accuracy in customer interest feature extraction, and high classification time ...

IoT devices have become a major target for numerous cyber-attacks, among which botnet-based attacks are the most serious and commonly occurring type. Thus, accurate detection schemes have become essential in identifying malicious attacks to safeguard IoT ...

Feature selection is one of the most significant procedures in machine learning algorithms. It is particularly to improve the performance and prediction accuracy for complex data classification. This paper discusses a hybrid feature selection technique ...

With regard to large dimensions of contemporary data sets and restricted computational time of intelligent systems, reducing the dimensions of data sets is necessary. Feature selection is a practical way to remove a set of redundant, irrelevant, ...

The performance of the neighborhood rough set model in feature selection is limited by nonobjective parameter selection method, the uncertainty measures considered only from a single view, and high time cost caused by processing high‐dimensional ...

In recent years, a large amount of data is collected from multiple sources and the demands for analyzing these data have increased enormously. Data sharing is a valuable part of this data-intensive and collaborative environment due to the synergies and ...

Nowadays, credit card fraud actions happen commonly, which results in vast financial losses. Fraudulent transactions can take place in a variety of ways and can be put into various categories. Hence, financial institutions and banks put forward credit ...

Filter-based feature selection used the intrinsic statistical characteristic to select high-rank features from a dataset. However, it affects the classification performance due to lack of feature interaction among the selected features. Gain ration (GR)-...

We introduce the first path-oriented drone trajectory planning algorithm, which performs continuous (i.e., dense) image acquisition along an aerial path and explicitly factors path quality into an optimization along with scene reconstruction quality. ...

A trajectory, defined as a sequence of location measurements, contains valuable information about movements of an individual. Its value of information (VOI) may change depending on the specific application. However, in a variety of applications, knowing ...

There are a wide range of genes in single-cell data, but some are not beneficial to classification. In order to eliminate these redundant genes and select beneficial genes, this study first utilises the information gain (IG) to select some genes coarsely, ...

The accuracy and performance of any machine learning model are highly dependent on the number of qualitative features taken into consideration while training the model. The selection of qualitative features depends on the considerate choice of feature ...

Data sharing among organizations has become an increasingly common process, but any part will most likely try to hide some sensitive patterns before it shares its data with others. In this article, we present a java application based on Local Distortion ...

Information gathering in a partially observable environment can be formulated as a reinforcement learning (RL), problem where the reward depends on the agent's uncertainty. For example, the reward can be the negative entropy of the agent's belief over ...

C4.5 is one of the top ten data mining algorithms; it is the most widely used decision trees construction techniques. Although effective, it suffers from the problem of complexity when it deals with continuous attributes. It also leads to a certain level ...

Cloud computing provides huge storage ability to clients, in order to convey their applications without any infrastructure investment. Alongside those applications, an extensive set of intermediate datasets will be created, and it is a challenging issue ...