A personalized recommendation method under the cloud platform based on users’ long-term preferences and instant interests

Rich consumer online text data are embedded in the cloud platform. Using new technologies has become a central issue for acquiring consumer preference, analyzing consumer demand, and performing personalized recommendation services. In order to recommend the cloud platform services efficiently and accurately, this paper proposes a personalized recommendation model referred to as Residual bi-directional Recurrent Neural Network with Dual Attentive mechanism (BiRDA) for the service recommend to cloud platforms, by combining users’ long-term preferences with instant interest. The proposed recommender prototype is summarized as follows. (1) Analyzing the relationship between long-term preferences and instant interests based on co-opetition theory. (2) Extracting users’ online text data from the cloud platform. (3) Deriving the product attribute words of user preference using an analysis of online text data. (4) Product attribute words are transformed into the form of word vectors. (5) The word vector is input into the Residual bi-directional Recurrent Neural Network (Res-BiRNN) to make the prediction. On the one hand, the long-term preference is expressed by the user's field of expertise (i.e., answer content). On the other hand, the even interest is expressed by the user's changing interest (i.e., question data). (6) Assigning different weights to long-term preferences and instant interest using the dual attention mechanism to output predictions. (7) Generating recommendation lists for users based on the predicted values. Accordingly, BiRDA is compared with five state-of-the-art recommendation methods (i.e., DREAM, BINN, SHAN, Caser, and DeepMove), as well as six variants of the BiRDA model, Using users’ Q&A datasets from NiorcngeCDS cloud platform, XMAKE cloud platform, and Asksubarme cloud platform as examples. The experiments show that the proposed method is more efficient and accurate than the other models. Therefore, the study offers some important insights into allowing a large number of resources under the cloud platform to be fully utilized and provides a novel idea for the construction of the cloud platform front-end.     

一种改进的基于梯度提升回归算法的 O2O 电子商务推荐模型

位置属性对于线下消费的用户具有重要影响。为了有效提高个性化推荐精度,在对O2O电子商务特点进行用户特征分析的基础上,在推荐算法中引入当前时间参数和位置参数,提出了一种改进的基于梯度提升回归算法的O2O电子商务推荐模型。实验结果表明,改进的基于梯度提升回归算法的O2O电子商务推荐模型在实时性和准确性方面明显优于传统的推荐算法。     

资讯类新闻套图系统

考虑到图片具有对事件诠释力强,传播便利的特点,研究了从大量数据密集的新闻Web页面中自动提取数据,并组织成套图结构展现给用户。基于页面模板实现动态页面抽取和解析,处理转换为对应的套图数据结构。基于余弦相关性对来自不同网站的新闻套图数据进行去重,并根据相应的标准,为数据集进行评分排序。考虑巨大的新闻数据和用户数量,本系统基于hadoop分布式平台,满足系统的高可扩展性。本文将详细描述我们的系统设计和实现,并公布在百度资讯图片栏目上的运行结果。     

电厂烟气脱硫技术推广应用战略模式研究

针对我国电厂烟气脱硫技术推广应用中存在的问题,设计出“政府主推,各部门联动,多种政策互补,完善产业链条”的电厂烟气脱硫技术推广宏观战略模式,并提出相应的政策建议。     

“十一五”期间我国能源市场供需前景研究

本文深入分析了“十一五”期间我国能源市场发展的环境、面临的问题与挑战,对“十一五”期间我国能源供需总量变化趋势做出了预测,最后提出了发展能源市场的政策建议。     

Red meat in global nutrition

The influence of data and recommendations from developed countries on nutrition guidance has overshadowed recognition of the key micronutrients and protein contributed by red meat to the global food supply. Relative to the energy it contributes, the impact of red meat on the nutritional quality of the human diet via its contribution of protein and key micronutrients is under-appreciated. The current discussion will review red meat nutrient composition and global consumption rates and discuss the evidence underpinning current dietary recommendations. The beneficial role of red meat in reducing risk factors associated with noncommunicable disease in developed countries and improving the nutritional status of developing nations will also be reviewed.     

论酒文化与酒业发展的关系

酒文化的表现形式主要有历史文化、企业文化、人文文化、旅游文化、健康文化和酒道文化。酒文化是酒业发展的历史积淀,是酒业发展的助推器;同时,酒业发展又促进了酒文化的发展和丰富酒文化内涵。     

基于Kano模型和亲和图法的地域性刺绣产品需求研究

目的 探讨中国传统地区刺绣产品如何实现更高的消费者满意度,并为该产品如何实现更多元化的顾客感受提出创新设计的建议。方法 围绕消费者需求偏好,综合采用田野调查、亲和图法、问卷调查法,并结合使用Kano模型、Better-Worse系数、四象限分析法,以及其他相关研究方法,从产品设计、产品生产、产品性能、产品文化四个需求纬度出发,全面准确地把握消费者对刺绣产品的需求。结果 消费者更加看重产品本身的文化属性和产品所提供的优质服务,同时消费者对服务的感受和满足程度会受到一些因素的影响,如绣活文化的保留程度,或是否有独特的个人定制体系。结论 通过Kano模型和亲和图法了解了消费者的真实需求,并且能够更好地实现这些需求。这种方式不仅能够增强消费者的满意度,实现区域特色刺绣产品的传播与普及,也为地域性刺绣产品设计提供了新思路。     

我国既有公共建筑的节能改造研究

分析了我国既有公共建筑的耗能现状与问题,对作为当前能耗大户的既有公共建筑的节能改造提出了一些具体建议。