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pro vyhledávání: '"Viger, A."'
In recent years, data mining technologies have been well applied to many domains, including e-commerce. In customer relationship management (CRM), the RFM analysis model is one of the most effective approaches to increase the profits of major enterpr
Externí odkaz:
http://arxiv.org/abs/2411.05317
Autor:
Dinh, Tai, Hauchi, Wong, Fournier-Viger, Philippe, Lisik, Daniil, Ha, Minh-Quyet, Dam, Hieu-Chi, Huynh, Van-Nam
The clustering of categorical data is a common and important task in computer science, offering profound implications across a spectrum of applications. Unlike purely numerical data, categorical data often lack inherent ordering as in nominal data, o
Externí odkaz:
http://arxiv.org/abs/2408.17244
In critical software engineering, structured assurance cases (ACs) are used to demonstrate how key properties (e.g., safety, security) are supported by evidence artifacts (e.g., test results, proofs). ACs can also be studied as formal objects in them
Externí odkaz:
http://arxiv.org/abs/2407.10345
Autor:
Geng, Meng, Wu, Youxi, Li, Yan, Liu, Jing, Fournier-Viger, Philippe, Zhu, Xingquan, Wu, Xindong
Sequential pattern mining (SPM) is an important branch of knowledge discovery that aims to mine frequent sub-sequences (patterns) in a sequential database. Various SPM methods have been investigated, and most of them are classical SPM methods, since
Externí odkaz:
http://arxiv.org/abs/2311.09667
Autor:
Wu, Youxi, Meng, Yufei, Li, Yan, Guo, Lei, Zhu, Xingquan, Fournier-Viger, Philippe, Wu, Xindong
Recently, order-preserving pattern (OPP) mining, a new sequential pattern mining method, has been proposed to mine frequent relative orders in a time series. Although frequent relative orders can be used as features to classify a time series, the min
Externí odkaz:
http://arxiv.org/abs/2310.02612
Node classification is the task of predicting the labels of unlabeled nodes in a graph. State-of-the-art methods based on graph neural networks achieve excellent performance when all labels are available during training. But in real-life, models are
Externí odkaz:
http://arxiv.org/abs/2308.05463
Image-text retrieval is one of the major tasks of cross-modal retrieval. Several approaches for this task map images and texts into a common space to create correspondences between the two modalities. However, due to the content (semantics) richness
Externí odkaz:
http://arxiv.org/abs/2304.10254
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 3, Pp 942-963 (2024)
Disinformation, often known as fake news, is a major issue that has received a lot of attention lately. Many researchers have proposed effective means of detecting and addressing it. Current machine and deep learning based methodologies for classific
Externí odkaz:
https://doaj.org/article/533e3f62e8a04698a0254c095ae51e7e
Autor:
A. Viger, S. Dominguez, S. Mazzotti, M. Peyret, M. Henriquet, G. Barreca, C. Monaco, A. Damon
Publikováno v:
Solid Earth, Vol 15, Pp 965-988 (2024)
New satellite geodetic data challenge our knowledge of the deformation mechanisms driving the active deformations affecting southeastern Sicily. The PS-InSAR (Permanent Scatterer Interferometry Synthetic Aperture Radar) measurements evidence a genera
Externí odkaz:
https://doaj.org/article/ea28cc63d29f436a86b851a0adb184ce
Finding high-importance patterns in data is an emerging data mining task known as High-utility itemset mining (HUIM). Given a minimum utility threshold, a HUIM algorithm extracts all the high-utility itemsets (HUIs) whose utility values are not less
Externí odkaz:
http://arxiv.org/abs/2303.14510