Results 11 to 20 of about 5,816 (262)
Towards secure and network state aware bitrate adaptation at IoT edge
Journal of Cloud Computing: Advances, Systems and Applications, 2020 Video streaming is critical in IoT systems, enabling a variety of applications such as traffic monitoring and health caring. Traditional adaptive bitrate streaming (ABR) algorithms mainly focus on improving Internet video streaming quality where network ...
Zeng Zeng +6 more
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Online algorithms for mining semi-structured data stream [PDF]
2002 IEEE International Conference on Data Mining, 2002. Proceedings., 2003 In this paper, we study an online data mining problem from streams of semi-structured data such as XML data. Modeling semi-structured data and patterns as labeled ordered trees, we present an online algorithm StreamT that receives fragments of an unseen possibly infinite semi-structured data in the document order through a data stream, and can return ...
Tatsuya Asai +4 more
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Markov Boundary Learning With Streaming Data for Supervised Classification
IEEE Access, 2020 In this paper, we study the problem of Markov boundary (MB) learning with streaming data. A MB is a crucial concept in a Bayesian network (BN) and plays an important role in BN structure learning.
Chaofan Liu, Shuai Yang, Kui Yu
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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
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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
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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
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Low-Memory Algorithms for Online and W-Streaming Edge Coloring
CoRR, 2023 For edge coloring, the online and the W-streaming models seem somewhat orthogonal: the former needs edges to be assigned colors immediately after insertion, typically without any space restrictions, while the latter limits memory to sublinear in the input size but allows an edge's color to be announced any time after its insertion.
Prantar Ghosh, Manuel Stoeckl
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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
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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
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IEEE Access, 2019 Early diagnosis significantly improves the survival rate in lung carcinoma patients. This study attempts to construct a predictive network between the computational features and semantic features of pulmonary nodules using online feature selection and ...
Jing Yang +4 more
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