Titlebook: Collaborate Computing: Networking, Applications and Worksharing; 12th International C Shangguang Wang,Ao Zhou Conference proceedings 2017 I

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Gaussian LDA and Word Embedding for Semantic Sparse Web Service DiscoveryWe also leverage the Gaussian LDA in service discovery, which takes continuous word distribution as the input and interprets the Web service description as a hierarchical model by its two distributions. Based on the Gaussian LDA and word embedding, we propose a Web service query and ranking approach

欺骗世家

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discord

钱财

受伤

Morad Benyoucef,Ronald PringadiWe also leverage the Gaussian LDA in service discovery, which takes continuous word distribution as the input and interprets the Web service description as a hierarchical model by its two distributions. Based on the Gaussian LDA and word embedding, we propose a Web service query and ranking approach

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Ahmed Tealeb,Ahmed Awad,Galal Galal-Edeenensive task and memory-unintensive task for execution in parallel. The experimental results demonstrate that our algorithm can find the optimal solution among all the possible combinations. The Maximum improvement of our algorithm is 15.6%).

EVICT

Gerald Schermann,Jürgen Cito,Philipp Leitnerently. LBDAG-DNE can find a good projection matrix, which allows neighbors belonging to the same class to be compact while neighbors belonging to different classes become separable in the subspace. Experiments on two image databases illustrate the effectiveness of the proposed approach.

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Collaborate Computing: Networking, Applications and Worksharing12th International C

传授知识

https://doi.org/10.1007/978-3-319-59288-6algorithms; artificial intelligence; cloud computing; computer networks; data security; Internet; machine