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Generating bunkering statistics from AIS data : a machine learning approach

Fuentes, Gabriel - In: Transportation research / E : an international journal 155 (2021), pp. 1-23

Persistent link: https://www.econbiz.de/10012695486

Inventor name disambiguation with gradient boosting decision tree and inventor mobility in China (1985-2016)

Yin, Deyun; Motohashi, Kazuyuki - 2018

Persistent link: https://www.econbiz.de/10012133429

Analysis of enterprise social media intelligence acquisition based on data crawler technology

Yu, Lehe; Gui, Zhengxiu - In: Entrepreneurship research journal : ERJ 11 (2021) 2, pp. 3-23

Persistent link: https://www.econbiz.de/10012523500

Effectiveness of Heuristic Based Approach on the Performance of Indexing and Clustering of High Dimensional Data

Chen, Alan; Gao, Shang; Jarada, Tamer N.; Zhang, Ming; … - In: Journal of Information & Knowledge Management (JIKM) 10 (2011) 03, pp. 261-271

utilised a number of clustering techniques, including the agglomerative hierarchical clustering, k-means clustering, and DBSCAN … attention in the research community. Indexing and clustering of high dimensional data are two of the most challenging techniques … technique applicable to indexing and clustering algorithms which need to calculate distances and check them against some minimum …

Persistent link: https://www.econbiz.de/10009274282

Application of improved clustering algorithm in precision poverty auditing : an example from region D

Zhang, Yantai - In: International journal of networking and virtual … 28 (2023) 2/4, pp. 247-264

Persistent link: https://www.econbiz.de/10014436403

Towards Identifying Multicriteria Outliers: An Outranking Relation-Based Approach

Rouba, Baroudi; Nait-Bahloul, Safia - In: International Journal of Decision Support System … 10 (2018) 3, pp. 27-38

This article tackles the problem of outlier detection in the multicriteria decision aid (MCDA) field. The authors propose an outlier detection method based on binary outranking relations and Local Outlier Factor (LOF) algorithm. The outlier is detected by applying LOF algorithm on the...

Persistent link: https://www.econbiz.de/10012044149

Hilbert Index-based Outlier Detection Algorithm in Metric Space

Xu, Honglong; Rong, Haiwu; Mao, Rui; Chen, Guoliang; … - In: International Journal of Grid and High Performance … 8 (2016) 4, pp. 34-54

Big data is profoundly changing the lifestyles of people around the world in an unprecedented way. Driven by the requirements of applications across many industries, research on big data has been growing. Methods to manage and analyze big data to extract valuable information are the key of big...

Persistent link: https://www.econbiz.de/10012045036

K-NN Based Outlier Detection Technique on Intrusion Dataset

Sahu, Santosh Kumar; Jena, Sanjay Kumar; Verma, Manish - In: International Journal of Knowledge Discovery in … 7 (2017) 1, pp. 58-70

Outliers in the database are the objects that deviate from the rest of the dataset by some measure. The Nearest Neighbor Outlier Factor is considering to measure the degree of outlier-ness of the object in the dataset. Unlike the other methods like Local Outlier Factor, this approach shows the...

Persistent link: https://www.econbiz.de/10012046205

Statistical Modeling for Studying the Impact of ICD-10 on Health Fraud Detection

Zhang, Yu; Olson, Tyler - In: International Journal of Privacy and Health Information … 5 (2017) 1, pp. 111-131

When an individual is seen or treated by a healthcare professional, a series of alphanumeric codes are used to describe the medical diagnoses and services provided. This designated classification structure, the ninth iteration of ICD (International Classification of Diseases), implements the use...

Persistent link: https://www.econbiz.de/10012047088

Parallel Outlier Detection for Streamed Data Using Non-Parameterized Approach

Markad, Harshad Dattatray; Sangve, S. M. - In: International Journal of Synthetic Emotions (IJSE) 8 (2017) 2, pp. 25-37

Outlier detection is used in various applications like detection of fraud, network analysis, monitoring traffic over networks, manufacturing and environmental software. The data streams which are generated are continuous and changing over time. This is the reason why it becomes nearly difficult...

Persistent link: https://www.econbiz.de/10012047571