数据挖掘中基于最小遗憾度的偏好感知算法

交互学习是数据挖掘的一种重要手段。使用交互学习作为学习系统和用户的交互模型,以向用户提供最大效用结果为目标,通过对用户反馈质量进行定量描述,考察偏好反馈,提出一种基于最小遗憾度的偏好感知算法。此外,还对偏好感知算法的期望遗憾度界限进行分析,并给出该算法的几个扩展版本。最后利用电影推荐任务及网络搜索排名数据验证了该算法的有效性。     

煤矿物联网研究现状及发展趋势

阐述了国内外煤矿物联网的一些概念及发展历史,分别从系统架构、感知层、传输层、应用层及工程应用方面总结了国内外煤矿物联网研究现状;指出目前煤矿物联网研究存在的主要问题为缺乏低功耗智能传感器及装置、矿井环境能量捕获技术、数据与网络安全方法、公共服务平台以及煤矿物联网相关标准;从嵌入式智能信息传感技术、基于大数据的矿山安全生产云服务平台、安全性方面探讨了煤矿物联网可能的发展方向。     

Computational Problem Solving in Spatial Substrates -- A Cognitive Systems Engineering Approach

The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. A common artificial intelligence approach to accomplish spatial tasks is to represent spatial configurations and tasks in form of detailed knowledge about various aspects of space and time. Suitable algorithms then use the representations to compute solutions to spatial problems. In comparison, natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects that are due to spatio-temporal affordances in their bodies and environments. Accordingly, we propose a paradigm that makes the spatio-temporal substrate an integral part of the engine that drives spatial problem solving. We argue that spatial and temporal structures in body and environment can substantially support (and even replace) reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation. While the approach is well known – for example, we employ diagrams as spatial substrate for geometric problem solving and maps for wayfinding – the underlying principle has not been systematically investigated or formally analyzed as a paradigm of cognitive processing. Topology, distance, and orientation constraints are all integrated and interdependent in truly 2- or 3-dimensional space. Exploiting this fact may not only help overcome the need for acquiring detailed knowledge about the interrelationships between different aspects of space; it also can point to a way of avoiding exploding computational complexity that occurs when we deal with these aspects of space in complex real-world scenarios. Our approach employs affordance-based object-level problem solving to complement knowledge-level formal approaches. We will assess strengths and weaknesses of the new cognitive systems paradigm.     

基于移动终端日志数据的人群特征可视化

随着我国移动互联网的迅猛发展,如何从海量移动终端日志数据中提取出有效信息,并进行合理、清晰的可视化分析,为工业界等提供有价值的统计分析功能显得尤为重要.目前,对于移动终端日志数据的研究和分析多是基于对单一属性的统计结果分析,如应用下载排行、用户留存率等.为了进一步挖掘移动终端日志数据背后深层次的隐含信息,更加准确地概括出移动终端用户的特征,提出了一种基于移动应用程序日志数据的人群特征分析与画像计算方法,构造了基于移动应用程序数据的主题模型,并将移动设备用户按照与不同应用主题的相关度进行聚类,得到了具有不同特征的人群,从而提出了基于层次气泡图和Voronoi Treemap的可视化展现与分析方案.进一步将人群特征与时间信息、地理位置信息相结合,从多角度可视化展现人群特征.最后,根据该研究内容,实现了B/S架构的日志数据可视化分析原型系统,并通过案例分析验证了该方法的有效性.     

辽宁省植烟区烟草主要害虫的天敌研究

根据1992～1995年的调查,本文记述了辽宁省烟田植食性昆虫107种,螨类和蛞蝓各1种,它们隶属8目37科。其中1种为中国新记录;16种为辽宁省新记录。基本明确了辽宁省3大主要植烟区的主要害虫、害虫的为害特性及其区系分布。     

基于区域特性的压缩感知多聚焦融合算法

传统的基于压缩感知的图像融合算法是对整个系数进行稀疏处理,而小波分解后的低频系数不稀疏,导致压缩重构质量降低,并且传统的融合规则不易简单、全面地提取高频系数的特征值。针对这一问题,分别对小波分解得到的高、低频系数采取不同的融合规则进行处理,提出了一种改进的区域特性高频压缩感知的融合算法。其中,低频系数采用区域方差加权绝对值最大融合;高频系数首先通过具有较好RIP性质的随机观测矩阵进行压缩采样,得到的观测值基于能量匹配度的不同进行相加或加权融合,以融合不同方向的高频子带特征信息,再用正交匹配追踪重构算法对高频部分进行信号重构。最后,低频、高频信息在小波逆变换下重构出融合图像。实验结果表明,与以往的基于压缩感知的融合方法相比,此算法的融合图像更清晰,新算法无论是在主观评价还是客观评价指标上都有利于图像信号重构,并具有较好的使用性。     

The roles of user motivation to perform a task and decision support system (DSS) effectiveness and efficiency in DSS use

The purposes of this study are to: (1) obtain measures of actual decision support system (DSS) use that include the three elements of DSS use proposed by Burton-Jones and Straub (Burton-Jones, A., & Straub, D.W., Jr., (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246), and (2) identify an important psychological construct – a user’s motivation to perform a task – and examine how it interacts with two DSS characteristics – effectiveness and efficiency – to affect actual DSS use. As predicted, the findings indicated that individuals who used a more effective DSS to work on a task that they were motivated in increased usage of the DSS, while DSS use did not differ between individuals who used either a more or less effective DSS to complete a task that they were less motivated in. The results also showed significant difference for two measures of DSS use (i.e., STEP and TIME) and no significant difference for one measure of DSS use (i.e., USE) between individuals who used either a more or less efficient DSS to perform a task that they were more motivated in. As expected, significant differences were found for individuals who used either a more or less efficient DSS to complete a task that they were less motivated in. Finally, the results showed that DSS use increased when perceived ease of use and perceived usefulness of the DSS were high; therefore, these results corroborate the findings of prior research in the context of actual DSS use.     

移动端加载动效时距知觉影响机制研究

摘 要：移动端加载动效是降低用户等待焦躁感的重要方式,探究其设计要素如何影响等待 焦躁感对于设计创意具有重要意义。研究采用时距知觉来表征等待焦躁感,通过预期式实验范式 和时距复制法,以设计要素速度、样式为自变量进行模拟情境下被试的时距知觉对比实验。实验 结果表明：移动端加载动效均对降低等待焦躁感产生正向影响;动效速度主效应显著,加速条件 下用户时距知觉最短;加载动效速度与类型交互作用显著,加速与卡通类组合的加载动效时距知 觉最短、匀速与文字类组合的加载动效时距知觉最短,减速与 3 种动效样式组合对时距知觉的影 响无显著差异。个体的时距知觉与加载动效速度和样式有关,通过对速度与样式的合理组合能够 有效降低用户时距知觉,减少焦躁感,由此提出了基于科学实证的移动端加载动效设计策略。     

基于聚类和流量传播图的P2P流量识别方法

为有效监管网络,快速精确识别P2P流量,通过分析P2P网络流量中节点与节点、节点与链路之间的交互和行为特征,将聚类方法与流量传播图方法相结合,提出了一种基于网络行为特征的P2P流量识别方法。该方法首先通过采集网络流的包级和流级统计特征对不同种类的网络应用的流量进行聚类,然后利用流量传播图对P2P流量进行识别。实验结果表明,提出的方法在骨干网络数据上能够有效识别P2P网络应用流量,◢F◣▼1▽-measure达到95%以上。     

苹果酒发酵过程中绿原酸胁迫对酿酒酵母生理特性的影响

在苹果酒发酵过程中,酿酒酵母会对各种胁迫和环境变化做出代谢应答.绿原酸是苹果和苹果酒中含量相对较高的一种苹果多酚类物质.本文以绿原酸为代表性苹果多酚,考察不同质量浓度的绿原酸胁迫对酿酒酵母生理特性的影响.结果表明:酿酒酵母CICC 31084在绿原酸胁迫下,主要通过改变胞内超氧化物歧化酶(SOD)活性、过氧化氢酶(CA...