Titlebook: Database Systems for Advanced Applications; 23rd International C Jian Pei,Yannis Manolopoulos,Jianxin Li Conference proceedings 2018 Spring

范例

Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspectiveix factorization framework. As a consequence, network embedding can be learned in a unified framework integrating network structure and node content as well as label information simultaneously. We demonstrate the efficacy of the proposed model with the tasks of semi-supervised node classification an

Glucose

Attributed Network Embedding with Micro-meso Structureal information including the microscopic proximity structure and mesoscopic community structure. In particular, both the microscopic proximity structure and node attributes are factorized by Nonnegative Matrix Factorization (NMF), from which the low-dimensional node representations can be obtained.

FEAS

鉆孔

Exploiting Context Graph Attention for POI Recommendation in Location-Based Social Networkseference modeling in the collaborative filtering framework..To address the limitations of existing methods, we propose a . (CGA) model, which can integrate context information encoded in different context graphs with the attention mechanism for POI recommendation. CGA first uses two context-aware at

insightful

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defibrillator

Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mappingt feature mapping is proposed to transfer the latent features of a cold-start user from the auxiliary domain?to the target domain. Extensive experiments on two real datasets extracted from Amazon transaction data demonstrate the superiority of our proposed model against other state-of-the-art method

恫嚇

Ventilator

Towards Efficient Path Skyline Computation in Bicriteria Networks evaluate our proposed algorithm on real networks and the experimental results demonstrate the efficiency of our proposed algorithm. Besides, the experimental results also demonstrate the algorithm that uses . as a building block for the path skyline query can achieve a significant performance impro

jeopardize

Franklyn G. Knox,William S. Spielmanix factorization framework. As a consequence, network embedding can be learned in a unified framework integrating network structure and node content as well as label information simultaneously. We demonstrate the efficacy of the proposed model with the tasks of semi-supervised node classification an