Enhancing attributed network embedding via enriched attribute representations
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02498-w
Abstract: Attributed network embedding enables to generate low-dimensional representations of network objects by leveraging both network structure and attribute data. However, how to properly combine two different information to achieve better vector representations remains still unclear.… read more here.
Keywords: attribute representations; network; attribute; network embedding ... See more keywords
Security Protection Technology in Multi-Attribute Data Transmission Based on Fuzzy Genetic Algorithm
Sign Up to like & getrecommendations! Published in 2021 at "Wireless Personal Communications"
DOI: 10.1007/s11277-021-08447-7
Abstract: Because the traditional data transmission security protection methods ignore the process of multi-attribute data detection, resulting in the abnormal data false alarm rate, high missing alarm rate, eliminating accuracy and other problems, a multi-attribute data… read more here.
Keywords: multi attribute; security protection; attribute data; data transmission ... See more keywords
Measuring shallow-water bathymetric signal strength in lidar point attribute data using machine learning
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Geographical Information Science"
DOI: 10.1080/13658816.2020.1867147
Abstract: ABSTRACT The goal of this work was to evaluate if routinely collected but seldom used airborne lidar metadata – ‘point attribute data’ (PAD) – analyzed using machine learning/artificial intelligence can improve extraction of shallow-water (less… read more here.
Keywords: point attribute; attribute data; lidar point; bathymetry ... See more keywords
Multi-Attribute Data Recovery in Wireless Sensor Networks With Joint Sparsity and Low-Rank Constraints Based on Tensor Completion
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DOI: 10.1109/access.2019.2942195
Abstract: In wireless sensor networks (WSNs), data recovery is an indispensable operation for data loss or energy constrained WSNs using sparse sampling. However, the recovery accuracy is not satisfying for WSNs with various sensor types due… read more here.
Keywords: low rank; multi attribute; data recovery; attribute data ... See more keywords
A Subspace Approach to Sparse-Sampling-Based Multi-Attribute Data Aggregation in IoT
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3161720
Abstract: The emergence of the heterogeneous Internet of Things (IoT) has realized the demand for multi-attribute data collection in response to the increasing demand for information in diverse applications. Sparse sampling has been used to reduce… read more here.
Keywords: sparse sampling; real time; attribute data; multi attribute ... See more keywords
Compressive Multi-Attribute Data Gathering Using Hankel Matrix in Wireless Sensor Networks
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2019.2941194
Abstract: For heterogeneous WSNs with various types of sensors, compressive data gathering method requires more measurements due to the increased multiple attributes. In this letter, a compressive multi-attribute data gathering method using low-rank Hankel matrix is… read more here.
Keywords: attribute data; data gathering; multi attribute; hankel matrix ... See more keywords
Sparse-Group Lasso for Graph Learning From Multi-Attribute Data
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2021.3057699
Abstract: We consider the problem of inferring the conditional independence graph (CIG) of high-dimensional Gaussian vectors from multi-attribute data. Most existing methods for graph estimation are based on single-attribute models where one associates a scalar random… read more here.
Keywords: multi attribute; sparse group; attribute data; graph ... See more keywords
RankAxis: Towards a Systematic Combination of Projection and Ranking in Multi-Attribute Data Exploration
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Visualization and Computer Graphics"
DOI: 10.1109/tvcg.2022.3209463
Abstract: Projection and ranking are frequently used analysis techniques in multi-attribute data exploration. Both families of techniques help analysts with tasks such as identifying similarities between observations and determining ordered subgroups, and have shown good performances… read more here.
Keywords: projection ranking; projection; multi attribute; exploration ... See more keywords