In this paper,we address the problem of unsuperised social network embedding,which aims to embed network nodes,including node attributes,into a latent low dimensional *** recent methods,the fusion mechanism of node at...
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In this paper,we address the problem of unsuperised social network embedding,which aims to embed network nodes,including node attributes,into a latent low dimensional *** recent methods,the fusion mechanism of node attributes and network structure has been proposed for the problem and achieved impressive prediction ***,the non-linear property of node attributes and network structure is not efficiently fused in existing methods,which is potentially helpful in learning a better network *** this end,in this paper,we propose a novel model called ASM(Adaptive Specific Mapping)based on encoder-decoder *** encoder,we use the kernel mapping to capture the non-linear property of both node attributes and network *** particular,we adopt two feature mapping functions,namely an untrainable function for node attributes and a trainable function for network *** the mapping functions,we obtain the low dimensional feature vectors for node attributes and network structure,***,we design an attention layer to combine the learning of both feature vectors and adaptively learn the node *** encoder,we adopt the component of reconstruction for the training process of learning node attributes and network *** conducted a set of experiments on seven real-world social network *** experimental results verify the effectiveness and efficiency of our method in comparison with state-of-the-art baselines.
Payment Channel Network(PCN)provides the off-chain settlement of *** is one of the most promising solutions to solve the scalability issue of the *** routing techniques in PCN have been ***,both incentive attack and p...
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Payment Channel Network(PCN)provides the off-chain settlement of *** is one of the most promising solutions to solve the scalability issue of the *** routing techniques in PCN have been ***,both incentive attack and privacy protection have not been considered in existing *** this paper,we present an auction-based system model for PCN routing using the Laplace differential privacy *** formulate the cost optimization problem to minimize the path cost under the constraints of the Hashed Time-Lock Contract(HTLC)tolerance and the channel *** propose an approximation algorithm to find the top K shortest paths constrained by the HTLC tolerance and the channel capacity,i.e.,top K-restricted shortest ***,we design the probability comparison function to find the path with the largest probability of having the lowest path cost among the top K-restricted shortest paths as the final ***,we apply the binary search to calculate the transaction fee of each *** both theoretical analysis and extensive simulations,we demonstrate that the proposed routing mechanism can guarantee the truthfulness and individual rationality with the probabilities of 1/2 and 1/4,*** can also ensure the differential privacy of the *** experiments on the real-world datasets demonstrate that the privacy leakage of the proposed mechanism is 73.21%lower than that of the unified privacy protection mechanism with only 13.2%more path cost compared with the algorithm without privacy protection on average.
Question Generation(QG)is the task of generating questions according to the given *** of the existing methods are based on Recurrent Neural Networks(RNNs)for generating questions with passage-level input for providing...
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Question Generation(QG)is the task of generating questions according to the given *** of the existing methods are based on Recurrent Neural Networks(RNNs)for generating questions with passage-level input for providing more details,which seriously suffer from such problems as gradient vanishing and ineffective information *** fact,reasonably extracting useful information from a given context is more in line with our actual needs during questioning especially in the education *** that end,in this paper,we propose a novel Hierarchical Answer-Aware and Context-Aware Network(HACAN)to construct a high-quality passage representation and judge the balance between the sentences and the whole ***,a Hierarchical Passage Encoder(HPE)is proposed to construct an answer-aware and context-aware passage representation,with a strategy of utilizing multi-hop ***,we draw inspiration from the actual human questioning process and design a Hierarchical Passage-aware Decoder(HPD)which determines when to utilize the passage *** conduct extensive experiments on the SQuAD dataset,where the results verify the effectivenesss of our model in comparison with several baselines.
Due to the complexity of the underwater environment, underwater acoustic target recognition is more challenging than ordinary target recognition, and has become a hot topic in the field of underwater acoustics researc...
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We investigated the efficiency of charge-to-spin conversion in two-dimensional Rashba altermagnets,a class of materials that combines the characteristics of both ferromagnets and *** quantum linear response theory,we ...
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We investigated the efficiency of charge-to-spin conversion in two-dimensional Rashba altermagnets,a class of materials that combines the characteristics of both ferromagnets and *** quantum linear response theory,we quantified the longitudinal and spin Hall conductivities in this system and demonstrated a substantial enhancement in the spin Hall angle below the band crossing point through the dual effects of relativistic spin–orbit interaction and nonrelativistic altermagnetic exchange ***,the results showed that the skew scattering and intrinsic mechanisms arising from Fermi sea states are almost negligible in this system,in contrast to conventional ferromagnetic Rashba *** findings not only elucidate the spin dynamics in Rashba altermagnets but also pave the way for developing novel strategies for manipulating charge-to-spin conversion via sophisticated control of noncollinear and collinear out-of-plane spin textures.
Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed dat...
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Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed data is undoubtedly higher than that of original data, and adopted association measure method does not well balance effectiveness and efficiency. To address above two issues, this paper proposes a novel association-based representation improvement method, named as AssoRep. AssoRep first obtains the association between features via distance correlation method that has some advantages than Pearson’s correlation coefficient. Then an improved matrix is formed via stacking the association value of any two features. Next, an improved feature representation is obtained by aggregating the original feature with the enhancement matrix. Finally, the improved feature representation is mapped to a low-dimensional space via principal component analysis. The effectiveness of AssoRep is validated on 120 datasets and the fruits further prefect our previous work on the association data reconstruction.
Transmission line(TL)Parameter Identification(PI)method plays an essential role in the transmission *** existing PI methods usually have two limitations:(1)These methods only model for single TL,and can not consider t...
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Transmission line(TL)Parameter Identification(PI)method plays an essential role in the transmission *** existing PI methods usually have two limitations:(1)These methods only model for single TL,and can not consider the topology connection of multiple branches for simultaneous identification.(2)Transient bad data is ignored by methods,and the random selection of terminal section data may cause the distortion of PI and have serious ***,a multi-task PI model considering multiple TLs’spatial constraints and massive electrical section data is proposed in this *** Graph Attention Network module is used to draw a single TL into a node and calculate its influence coefficient in the transmission ***-Task strategy of Hard Parameter Sharing is used to identify the conductance ofmultiple branches *** show that themethod has good accuracy and *** to the consideration of spatial constraints,the method can also obtain more accurate conductance values under different training and testing conditions.
Anomaly detection in time series data (e.g., sensor data) is becoming a fundamental research problem that has various applications. Due to the complex inter-sensor relationships, it is challenging to detect anomalous ...
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Recently advancements in deep learning models have significantly facilitated the development of sequential recommender systems(SRS).However,the current deep model structures are limited in their ability to learn high-...
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Recently advancements in deep learning models have significantly facilitated the development of sequential recommender systems(SRS).However,the current deep model structures are limited in their ability to learn high-quality embeddings with insufficient ***,highly skewed long-tail distribution is very common in recommender ***,in this paper,we focus on enhancing the representation of tail items to improve sequential recommendation *** empirical studies on benchmarks,we surprisingly observe that both the ranking performance and training procedure are greatly hindered by the poorly optimized tail item *** address this issue,we propose a sequential recommendation framework named TailRec that enables contextual information of tail item well-leveraged and greatly improves its corresponding *** the characteristics of the sequential recommendation task,the surrounding interaction records of each tail item are regarded as contextual information without leveraging any additional side *** approach allows for the mining of contextual information from cross-sequence behaviors to boost the performance of sequential *** a light contextual filtering component is plug-and-play for a series of SRS *** verify the effectiveness of the proposed TailRec,we conduct extensive experiments over several popular benchmark *** experimental results demonstrate that TailRec can greatly improve the recommendation results and speed up the training *** codes of our methods have been available.
Wireless power transmission has been widely used to replenish energy for wireless sensor networks, where the energy consumption rate of sensor nodes is usually time varying and indefinite. However, few works have inve...
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