Machine learning in information systems-a bibliographic review and open research issues
Abstract Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in
industry and business practice, while management-oriented research disciplines seem …
industry and business practice, while management-oriented research disciplines seem …
The analytics paradigm in business research
The availability of data in massive collections in recent past not only has enabled data-
driven decision-making, but also has created new questions that cannot be addressed …
driven decision-making, but also has created new questions that cannot be addressed …
Outlier detection in wireless sensor networks using machine learning techniques: a survey
Now-a-days, Internet of Things (IoT) based systems are develo** very fast which have
various type of wireless sensor networks (WSN) behind it. These networks have various …
various type of wireless sensor networks (WSN) behind it. These networks have various …
Toward an understanding of consumer attitudes on online review usage
With the rapid e-commerce growth and changes in consumers' behaviors, many businesses
are forced to adapt their business model to match their target customers' needs. To provide …
are forced to adapt their business model to match their target customers' needs. To provide …
Energy-based anomaly detection for mixed data
Anomalies are those deviating significantly from the norm. Thus, anomaly detection amounts
to finding data points located far away from their neighbors, ie, those lying in low-density …
to finding data points located far away from their neighbors, ie, those lying in low-density …
A double-weighted outlier detection algorithm considering the neighborhood orientation distribution of data objects
Q Gao, QQ Gao, ZY **ong, YF Zhang, YQ Wang… - Applied …, 2023 - Springer
Outlier detection is a hot research topic in data mining, and its requirements for algorithms to
engage with various complex-shaped datasets more effectively are also increasing. This …
engage with various complex-shaped datasets more effectively are also increasing. This …
An effective intrusion detection system using flawless feature selection, outlier detection and classification
Intrusion detection system (IDS) is playing crucial role to provide the security in the fastest
world by protecting the internet applications such as healthcare applications, government …
world by protecting the internet applications such as healthcare applications, government …
Data Science
BM Abdel-Karim - Data Science: Best Practices mit Python, 2022 - Springer
In diesem Kapitel wird auf den Begriff Data Science und die dahinterstehenden
Forschungsdisziplinen eingegangen. Hierbei werden zentrale Aspekte beleuchtet und eine …
Forschungsdisziplinen eingegangen. Hierbei werden zentrale Aspekte beleuchtet und eine …
Outlier Detection in Wireless Sensor Networks Based on Machine Learning
Due to their deployment in harsh situations with hundreds to thousands of nodes, wireless
sensor networks, or WSNs, have proven vital in a variety of applications, from military …
sensor networks, or WSNs, have proven vital in a variety of applications, from military …
Study on anomaly detection method of improper foods using import food big data
S Cho, G Choi - The Journal of BigData, 2018 - koreascience.kr
Owing to the increase of FTA, food trade, and versatile preferences of consumers, food
import has increased at tremendous rate every year. While the inspection check of imported …
import has increased at tremendous rate every year. While the inspection check of imported …