Methods and challenges in shot boundary detection: a review
The recent increase in the number of videos available in cyberspace is due to the availability
of multimedia devices, highly developed communication technologies, and low-cost storage …
of multimedia devices, highly developed communication technologies, and low-cost storage …
Isolation‐based anomaly detection using nearest‐neighbor ensembles
The first successful isolation‐based anomaly detector, ie, iForest, uses trees as a means to
perform isolation. Although it has been shown to have advantages over existing anomaly …
perform isolation. Although it has been shown to have advantages over existing anomaly …
Hybridization of feature selection and feature weighting for high dimensional data
The classification of high dimensional data is a challenging problem due to the presence of
redundant and irrelevant features in a higher amount. These unwanted features degrade …
redundant and irrelevant features in a higher amount. These unwanted features degrade …
On perfect clustering of high dimension, low sample size data
Popular clustering algorithms based on usual distance functions (eg, the Euclidean
distance) often suffer in high dimension, low sample size (HDLSS) situations, where …
distance) often suffer in high dimension, low sample size (HDLSS) situations, where …
A comprehensive empirical comparison of hubness reduction in high-dimensional spaces
R Feldbauer, A Flexer - Knowledge and Information Systems, 2019 - Springer
Hubness is an aspect of the curse of dimensionality related to the distance concentration
effect. Hubs occur in high-dimensional data spaces as objects that are particularly often …
effect. Hubs occur in high-dimensional data spaces as objects that are particularly often …
usfAD: a robust anomaly detector based on unsupervised stochastic forest
In real-world applications, data can be represented using different units/scales. For example,
weight in kilograms or pounds and fuel-efficiency in km/l or l/100 km. One unit can be a …
weight in kilograms or pounds and fuel-efficiency in km/l or l/100 km. One unit can be a …
A new simple and effective measure for bag-of-word inter-document similarity measurement
To measure the similarity of two documents in the bag-of-words (BoW) vector representation,
different term weighting schemes are used to improve the performance of cosine similarity …
different term weighting schemes are used to improve the performance of cosine similarity …
A comparative study of data-dependent approaches without learning in measuring similarities of data objects
Conventional general-purpose distance-based similarity measures, such as Minkowski
distance (also known as ℓ _p ℓ p-norm with p> 0 p> 0), are data-independent and sensitive …
distance (also known as ℓ _p ℓ p-norm with p> 0 p> 0), are data-independent and sensitive …
A Fuzzy Twin Support Vector Machine Based on Dissimilarity Measure and Its Biomedical Applications
J Qiu, J Xie, D Zhang, R Zhang, M Lin - International Journal of Fuzzy …, 2024 - Springer
Biomedical data exhibit high-dimensional complexity in its internal structure and are
susceptible to noise interference, making classification tasks in biomedical data highly …
susceptible to noise interference, making classification tasks in biomedical data highly …
[HTML][HTML] Is it possible to find the single nearest neighbor of a query in high dimensions?
We investigate an open question in the study of the curse of dimensionality: Is it possible to
find the single nearest neighbor of a query in high dimensions? Using the notion of (in) …
find the single nearest neighbor of a query in high dimensions? Using the notion of (in) …