Titlebook: Big Data; 8th CCF Conference, Hong Mei,Weiguo Zhang,Li Wang Conference proceedings 2021 Springer Nature Singapore Pte Ltd. 2021 artificial

短程旅游

https://doi.org/10.1007/b107943rs of the questions and candidate answers were sent to the Convolutional Neural Network for learning, which is used the Leaky Relu activation function, and the learning results were pieced together with four Attention items, and features in relation to the vocabulary and topic, and then input into t

得体

MAOIS

残暴

Terrence Schofield,Rahn Kennedy Baileyructure. Graph convolution networks (GCN) are successfully applied in node embedding task as they can learn sparse and discrete dependency in the data. Most of the existing work in GCN requires costly matrix operation. In this paper, we proposed a graph neighbor Sampling, Aggregation, and ATtention

Arbitrary

A. Dexter Samuels,Rahn Kennedy Baileyy developed and get many different variants of GAN. GAN was proposed to generate similar-looking samples to those in the training data sets. The emergence of GAN and its variants also provide new ideas for food pairing. In this paper, we have tried to invent a novel technique for food pairing using

Mortal

Camouflage

infringe

https://doi.org/10.1007/978-3-030-44762-5eredges is increasing infinitely. However, in the network, considering the impact of real resources and environment, the nodes can not grow without the upper limit, and the number of connections can not grow without the upper limit. Under certain conditions, there will be the optimal or maximum grow

后天习得

宇宙你

https://doi.org/10.1007/978-3-030-44762-5 between the system and its users. Most previous recommender systems heavily focus on optimizing recommendation accuracy while neglecting the other important aspects of recommendation quality, such as diversity of recommendation list. In this study, we propose a novel recommendation framework to opt