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1.
Viewer gifting is an important business mode in live streaming industry, which closely relates to the income of the platforms and streamers. Previous studies on gifting prediction are often limited to cross-section data and consider the problem from the macro perspective of the whole live streaming. However, the multimodal information and the time accumulation effect of live streaming content on viewer gifting behavior are ignored. In this paper, we put forward a multimodal time-series method (MTM) for predicting real-time gifting. The core module of the method is the multimodal time-series analysis (MTA), which targets at effectively fusing multimodal information. Specifically, the proposed orthogonal projection (OP) model can promote cross-modal information interaction without introducing additional parameters. To achieve the interaction of multi-modal information at the same level, we also design a stackable joint representation layer, which makes each target modality's representation (visual, acoustic and textual modality) can benefit from all the other modalities. The residual connections are introduced as well to ensure the integration of low-level and high-level information. On our dataset, our model shows improved performance compared to other advanced models by at least 8% on F1. Meanwhile, the MTA is able to meet the real-time requirements of the live streaming setting, and has demonstrated its robustness and transferability in other tasks. Our research may offer some insights about how to efficiently fuse multimodal information, and contribute to the research on viewer gifting behavior prediction in the live streaming context.  相似文献   
2.
随着我国教学体制改革的不断完善,人们愈发的重视到了在实际教学过程中有关教学方法的应用,适当的教学方法应用不仅仅能够在很大程度上帮助教师获得更好的教学效果,同时还能够在根本上提升学生对于高校排球课程的理解。由此,本文拟通过对现阶段高校排球课教学过程中有关异质分组教学的方法应用进行研究,从而探究其实际的使用效果,同时帮助这一教学模式在后续高校排球课程中推广的不断深入,进而促进未来我国高校排球课程的发展。  相似文献   
3.
网球是一项非常有益身心健康的运动,可以帮助人们提高自身的运动能力、增强体质,很多高校开设了网球课程。如何提高学生对网球的兴趣,使其积极参与到网球课程中来成为了高校网球教学面临的主要难题。对此,笔者从高校当前的网球教学现状出发,为提高学生网球兴趣提出相应的建议。  相似文献   
4.
Scientific collaboration contributes to the innovation of science and technology. For individual scholars, it is valuable to find potential and valuable collaborators to improve the quality and quantity of research. Previous research mainly recommends collaborators by exploring one kind of relationship between authors, such as the research topics or co-authorship. Some research tries to utilize more relationships, but they simply integrate the recommendation results of different relationships rather than integrating them. This study proposes a novel Heterogeneous Network Embedding Recommendation (HNERec) model for scientific collaborator recommendation. The HNERec model employs a random walk to develop a heterogeneous network considering four kinds of meta-path illustrating the topic relationship, authorship, citation relationship, and venue relationship. It utilizes the skip-gram model to embed the nodes, and finally generates a recommendation list based on the similarity between the corresponding node vectors. Experiments on a DBLP dataset and an AMiner dataset demonstrate the reliability of the HNERec model. The HNERec model outperforms the mainstream collaborator recommendation baselines in metrics such as F1, MRR, and nDCG. The results can not only be applied to the selection of collaborators by individual scholars but also allow scientific and conference institutions to recommend collaborators.  相似文献   
5.
Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior results in many sequence modeling tasks. The ability of Transformer to capture long-range dependencies and interactions makes it possible to apply it in the field of portfolio management (PM). However, the built-in quadratic complexity of the Transformer prevents its direct application to the PM task. To solve this problem, in this paper, we propose a deep reinforcement learning-based PM framework called LSRE-CAAN, with two important components: a long sequence representations extractor and a cross-asset attention network. Direct Policy Gradient is used to solve the sequential decision problem in the PM process. We conduct numerical experiments in three aspects using four different cryptocurrency datasets, and the empirical results show that our framework is more effective than both traditional and state-of-the-art (SOTA) online portfolio strategies, achieving a 6x return on the best dataset. In terms of risk metrics, our framework has an average volatility risk of 0.46 and an average maximum drawdown risk of 0.27 across the four datasets, both of which are lower than the vast majority of SOTA strategies. In addition, while the vast majority of SOTA strategies maintain a poor turnover rate of approximately greater than 50% on average, our framework enjoys a relatively low turnover rate on all datasets, efficiency analysis illustrates that our framework no longer has the quadratic dependency limitation.  相似文献   
6.
[目的/意义] 面对多学科领域、多类型用户的专题情报服务需求,建立专题情报数据管理与智能分析平台。实现专题情报分析的流程化和智能化,同时对融入专家智慧的专题情报分析过程数据进行管理,丰富服务模式,提升服务需求响应速度。[方法/过程] 在调研已有相关研究与实践分析基础上,提出平台设计思路、建设框架,对平台主要功能和关键技术进行剖析。[结果/结论] 专题情报数据管理与智能分析平台已建设完成。平台集成了多来源多类型数据,打通了从数据到分析的服务链条。嵌入了多种情报分析方法和深度学习算法,实现了多维多层次分析服务。能够对分析过程和情报分析人员历史积累数据进行管理,实现数据共享和重复利用。  相似文献   
7.
大胆变革 锐意创新 深化高校实验用房改革   总被引:1,自引:0,他引:1  
分析高校实验用房使用中的弊端,结合本校实验用房管理改革的有益实践,探讨通过高校实验用房管理改革达到实验用房使用效益最大化的目的。  相似文献   
8.
实验室安全管理是影响我国高校发展至关重要的基础管理环节。多年来,管理理念滞后和科学性、规范性不足制约了高校实验室安全管理水平的提升。借鉴EHS管理系统的先进理念,为我国高校实验室安全管理工作提供了新的思路。  相似文献   
9.
大学生课外科技创新活动体系构建的探索与实践   总被引:1,自引:0,他引:1  
结合国外高校成功经验,阐述了如何构建大学生课外科技创新活动体系,为学生提供科技创新的学习实践平台,使其将所学理论知识进行实践综合与创造,培养其创新意识和创新精神,促进创新型工程人才的培养。  相似文献   
10.
通过制订本院2010级高职人才培养方案的实践探索,阐述了人才培养方案制订的基本原则和思路,通过对人才培养方案的具体要求,以及人才培养方案的内容和制订过程中的组织工作,说明国家示范校重点专业建设成果在校内其他专业的辐射的意义,加强后示范校建设,是摆在国家示范院校面前的一个重要任务。  相似文献   
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