Predictive Model of Live Shopping Interest Degree Based on Eye Movement Characteristics and Deep Factorization Machine

In the live broadcast process,eye movement characteristics can reflect people’s attention to the product.However,the existing interest degree predictive model research does not consider the eye movement characteristics.In order to obtain the users’interest in the product more effectively,we will consider the key eye movement indicators.We first collect eye movement characteristics based on the self-developed data processing algorithm fast discriminative model prediction for tracking(FDIMP),and then we add data dimensions to the original data set through information filling.In addition,we apply the deep factorization machine(DeepFM)architecture to simultaneously learn the combination of low-level and high-level features.In order to effectively learn important features and emphasize relatively important features,the multi-head attention mechanism is applied in the interest model.The experimental results on the public data set Criteo show that,compared with the original DeepFM algorithm,the area under curve(AUC)value was improved by up to 9.32%.

Evolution mechanism of Weibo top news competition

In a certain period,some news will compete for the top news to gain the most attention and influence,and more news will be submerged in the ocean of news and become mediocre.This article deeply studies the evolution process and competition mechanism of the dissemination of Weibo news.In this paper,we innovatively propose a pre-processing scheme for traditional small-world networks and scale-free networks and divide nodes into three roles:fans,passersby,and anti-fans.The competition mechanism of Weibo top news is defined from the aspects of node role and node aggregation degree.A network evolution model is established based on the competition mechanism.The propagation characteristics of the network evolution model are deeply analyzed,and simulation experiments are performed on the small-world network and the scale-free network.Finally,the validity and rationality of the new model are verified through comparative experiments,and a feasible scheme for the propagation of top news on Weibo is given.

A point-based rendering approach for real-time interaction on mobile devices

Mobile device is an important interactive platform. Due to the limitation of computation, memory, display area and energy, how to realize the efficient and real-time interaction of 3D models based on mobile devices is an important research topic. Considering features of mobile devices, this paper adopts remote rendering mode and point models, and then, proposes a transmission and rendering approach that could interact in real time. First, improved simplification algorithm based on MLS and display resolution of mobile devices is proposed. Then, a hierarchy selection of point models and a QoS transmission control strategy are given based on interest area of operator, interest degree of object in the virtual environment and rendering error. They can save the energy consumption. Finally, the rendering and interaction of point models are completed on mobile devices. The experiments show that our method is efficient.