Results 21 to 30 of about 7,350 (305)
Unsupervised Feature Selection for Outlier Detection on Streaming Data to Enhance Network Security
Applied Sciences, 2021 Over the past couple of years, machine learning methods—especially the outlier detection ones—have anchored in the cybersecurity field to detect network-based anomalies rooted in novel attack patterns.
Michael Heigl +3 more
doaj +1 more source
Improved Multi-Pass Streaming Algorithms for Submodular Maximization with Matroid Constraints [PDF]
, 2020 We give improved multi-pass streaming algorithms for the problem of maximizing a monotone or arbitrary non-negative submodular function subject to a general p-matchoid constraint in the model in which elements of the ground set arrive one at a time in a ...
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020) +6 more
core +1 more source
On Two-Pass Streaming Algorithms for Maximum Bipartite Matching [PDF]
, 2021 We study two-pass streaming algorithms for Maximum Bipartite Matching (MBM). All known two-pass streaming algorithms for MBM operate in a similar fashion: They compute a maximal matching in the first pass and find 3-augmenting paths in the second in ...
Naidu, Kheeran K., Konrad, Christian
core +1 more source
Streaming Algorithms with Large Approximation Factors [PDF]
, 2022 We initiate a broad study of classical problems in the streaming model with insertions and deletions in the setting where we allow the approximation factor α to be much larger than 1.
Zhang, Yuheng +3 more
core +1 more source
Breast Cancer Identification from Patients’ Tweet Streaming Using Machine Learning Solution on Spark
Complexity, 2021 Twitter integrates with streaming data technologies and machine learning to add new value to healthcare. This paper presented a real-time system to predict breast cancer based on streaming patient’s health data from Twitter.
Nahla F. Omran +3 more
doaj +1 more source
An online classification algorithm for large scale data streams: iGNGSVM [PDF]
Neurocomputing, 2017 Stream Processing has recently become one of the current commercial trends to face huge amounts of data. However, normally these techniques need specific infrastructures and high resources in terms of memory and computing nodes. This paper shows how mini-batch techniques and topology extraction methods can help making gigabytes of data to be manageable
Andrés L. Suárez-Cetrulo +1 more
openaire +2 more sources
The sparse awakens : streaming algorithms for matching size estimation in sparse graphs [PDF]
, 2017 Estimating the size of the maximum matching is a canonical problem in graph analysis, and one that has attracted extensive study over a range of different computational models.
Muthukrishnan, S. +3 more
core +1 more source
International Journal of Computational Intelligence Systems, 2020 The goals of feature selection are to remove redundant and irrelevant features from high-dimensional data, extract the “optimal feature subset” of the original feature space to improve the classification accuracy, and reduce the time complexity ...
Hongyi Wang, Dianlong You
doaj +1 more source
Sentiment Analysis on WeTV App Reviews on Google Play Store Using NBC and SVM Algorithms
Sistemasi: Jurnal Sistem Informasi, 2023 Since the Covid-19 outbreak hit Indonesia, all community activities have become very limited. The government's decision regarding PPKM to reduce the level of Covid-19 cases forced the community to reduce the level of activities outside the home including
Petronilia Palinggik Allorerung +1 more
doaj +1 more source
Streaming Algorithms for Planar Convex Hulls [PDF]
, 2018 Many classical algorithms are known for computing the convex hull of a set of n point in R^2 using O(n) space. For large point sets, whose size exceeds the size of the working space, these algorithms cannot be directly used.
Tsai, Meng-Tsung +2 more
core +1 more source