2,768 Result(s)
within
Jian** **
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
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Article
HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer texts present challenges, including noise, long-range depend...
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Graph neural architecture search with heterogeneous message-passing mechanisms
In recent years, neural network search has been utilized in designing effective heterogeneous graph neural networks (HGNN) and has achieved remarkable performance beyond manually designed networks. Generally, ...
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GTHP: a novel graph transformer Hawkes process for spatiotemporal event prediction
The event sequences with spatiotemporal characteristics have been rapidly produced in various domains, such as earthquakes in seismology, electronic medical records in healthcare, and transactions in the finan...
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Integrating online partial pair programming and socially shared metacognitive regulation for the improvement of students’ learning
Many universities around the world were forced to lock down and students had to continue their learning in online environments in response to the COVID-19 pandemic. Teachers thus had to adopt effective and app...
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Probabilistic graph model and neural network perspective of click models for web search
Click behavior is a typical user behavior in the web search. How to capture and model users’ click behavior has always been a common research topic. However, there are few review studies on this topic. In this...
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A new neighbourhood-based diffusion algorithm for personalized recommendation
Object ratings in recommendation algorithms are used to represent the extent to which a user likes an object. Most existing recommender systems use these ratings to recommend the top-K objects to a target user...
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Progressive spatial–temporal transfer model for unsupervised person re-identification
Over the past decade, a more widespread area of computer vision research has been person re-identification (P-Reid). This technology is applied in fields such as pedestrian tracking, security, and video survei...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
The construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole. The exist...
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Improving stock trend prediction with pretrain multi-granularity denoising contrastive learning
Stock trend prediction (STP) aims to predict price fluctuation, which is critical in financial trading. The existing STP approaches only use market data with the same granularity (e.g., as daily market data). ...
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Adaptive graph contrastive learning with joint optimization of data augmentation and graph encoder
Graph contrastive learning (GCL) has been successfully used to solve the problem of the huge cost of graph data annotation, such as labor cost, time cost, and professional knowledge cost. Recent works have foc...
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Integrating online meta-cognitive learning strategy and team regulation to develop students’ programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom
With the development of technology and demand for online courses, there have been considerable quantities of online, blended, or flipped courses designed and provided. However, in the technology-enhanced learn...
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DAABNet: depth-wise asymmetric attention bottleneck for real-time semantic segmentation
With the increasing demand for the real-world applications such as autonomous driving and video surveillance, lightweight semantic segmentation methods achieving good trade-offs in terms of parameter size, spe...
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Text-assisted attention-based cross-modal hashing
As one of the hottest research topics in multimedia information retrieval, cross-modal hashing has drawn widespread attention in the past decades. How to minimize the semantic gap of heterogeneous data and acc...
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Graph neural architecture prediction
Graph neural networks (GNNs) have shown their superiority in the modeling of graph data. Recently, increasing attention has been paid to automatic graph neural architecture search, aiming to overcome the short...
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A novel image denoising algorithm combining attention mechanism and residual UNet network
Images are easily polluted by noise in the process of acquisition and transmission, which will affect people's understanding and utilization of knowledge and information in images. Therefore, image denoising, ...
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Community-aware graph embedding via multi-level attribute integration
Graph embedding has been extensively studied in the literature and is widely used in various applications such as drug discovery, social network analysis, and natural language processing. However, existing app...
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Node classification across networks via category-level domain adaptive network embedding
To improve the performance of classifying nodes on unlabeled or scarcely-labeled networks, the task of node classification across networks is proposed for transferring knowledge from similar networks with rich...
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Distributional constraint discovery for intelligent auditing
Constraint discovery in relational databases aims to find constraints that express dependency relationships among a set of attributes and has witnessed remarkable success in the applications of data cleaning, ...
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A representation learning model based on stochastic perturbation and homophily constraint
The network representation learning task of fusing node multi-dimensional classification information aims to effectively combine node multi-dimensional classification information and network structure informat...
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Interactive communication in the process of physical education: are social media contributing to the improvement of physical training performance
The development of modern technologies and the use of social networks create an environment for the exchange of information, interactive communication, learning, and optimization of various processes. The stud...
