Titlebook: Computer Supported Cooperative Work and Social Computing; 15th CCF Conference, Yuqing Sun,Dongning Liu,Liping Gao Conference proceedings 20

Arthritis

Intact

罵人有污點(diǎn)

Selective Self-attention with BIO Embeddings for Distant Supervision Relation Extractionhe training data generated in this way intrinsically include massive noise. To alleviate this problem, attention mechanism is employed by most prior works that achieves significant improvements but could be still imcompetent for one-sentence bags which means only one sentence within a bag. To this e

隱語

Service Clustering Method Based on Knowledge Graph Representation Learning service accurately and quickly in service computing research. At present, most of the Web services published on the Internet are described in natural language. This trend is becoming more and more obvious. Existing service clustering methods are not only limited to a specifically structured documen

champaign

An Efficient Framework of Convention Emergence Based on Multiple-Local Informationt is important to investigate how rapidly synthesize an ideal convention through repeated local interactions and learning among agents. Many methods have been proposed to generate convention, but it is difficulty to deal with the effectiveness of small-world networks and the efficiency of convergenc

Irrigate

WikiChain: A Blockchain-Based Decentralized Wiki Framework adopt centralized system architectures. Although some work has studied the problem that centralized architectures are unreliable, existing implementations still face some challenges, such as non-disclosure, non-transparency and insecurity. Recently, blockchain has gained extensive attention due to

LUCY

Dynamic Vehicle Distribution Path Optimization Based on Collaboration of Cloud, Edge and End Devicesad conditions, and the inability to reduce the impact on the timeliness of distribution, this paper proposes a dynamic vehicle distribution path optimization method based on the collaboration of cloud, edge and end devices. This method considers the requirements of demand points for the delivery tim

syncope

CLENet: A Context and Location Enhanced Transformer Network for Target-Oriented Sentiment Classifica-attention structure, but practice shows that LSTM and attention mechanism can not correctly identify and classify partial negation relations and multi-target scenarios on limited datasets. This paper proposes a context and location enhanced transformer network that improves both the modeling of neg

TOXIN

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