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

neutralize

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

欺騙世家

inferno

discord

錢(qián)財(cái)

受傷

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

形容詞詞尾

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.

Gentry

Collaborate Computing: Networking, Applications and Worksharing12th International C

傳授知識(shí)

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