Titlebook: Computer Supported Cooperative Work and Social Computing; 17th CCF Conference, Yuqing Sun,Tun Lu,Bowen Du Conference proceedings 2023 The E

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Marko Kananen,Ville-Samuli Haverinene, whether using the power of the crowd can improve source searching algorithms remains unanswered. To this end, we propose a crowd-powered sourcing search approach, using human rationales as external supports to improve existing search algorithms, and meanwhile to minimize the human effort using ma

四牛在彎曲

https://doi.org/10.1007/978-3-531-93056-5low-privacy and non-privacy tasks. ANOVA technique is used to verify the performance of the proposed algorithm. The experimental results show that the proposed algorithm is superior to others in terms of the number of devices, the amount of different task data, and the proportion of privacy tasks at

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MatricEs: Matrices Embeddings for?Link Prediction in?Knowledge Graphs and interpretability. We formally define the relation patterns which are satisfied by MatricEs, including symmetry, antisymmetry, inversion, commutative compositions and non-commutative compositions, absorption and transitivity. Theoretical analysis shows that MatricEs is a valid, simple and univer

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Learning User Embeddings Based on?Long Short-Term User Group Modeling for?Next-Item Recommendationo detect which latent groups a user belongs to, followed by an aggregation of these latent group representations. Finally, user preference representations are shaped comprehensively by considering all these four aspects, based on an attention mechanism. Extensive experiments prove our model outperfo

FAZE

Context-Aware Quaternion Embedding for?Knowledge Graph Completioniginal embedding, and finally use quaternion multiplication to model triples. The experiment and results on two common benchmark datasets show that CAQuatE can significantly outperform the existing state-of-the-art model in the knowledge graph completion task by obtaining lower dimensional represent

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ICKG: An I Ching Knowledge Graph Tool Revealing Ancient Wisdomool (ICKG) is developed to support knowledge graph-based visualization and interactive knowledge mining. It provides users with search and visualization functions for each hexagram and each entity in the I Ching. Moreover, it supports the visualized linking including the connections among entities i