Persistent problems and practices in information systems development: a study of mobile applications development and distribution

The widespread uptake of mobile technologies has witnessed a re‐structuring of the mobile market with major shifts in the predominance of particular firms and the emergence of new business models. These sociotechnical trends are significant in the ways that they are influencing and shaping the working lives of software professionals. Building on prior research investigating the persistent problems and practices of systems development, this paper examines mobile applications development and distribution. A qualitative study of 60 developers based in Sweden, the UK and the USA was analysed around the interrelated problems of diversity, knowledge and structure. The analysis revealed how platform‐based development in an evolving mobile market represents significant changes at the business environment level. These changes ripple through and accentuate ongoing trends and developments, intensifying the persistent problems and challenges facing software developers.     

移动终端智能引擎平台研究

随着移动终端的不断发展与普及,它已经变成了一个交流、传感的设备。普通市民只需要通过移动设备就可以从周围的环境中获取海量信息以及分享自己的信息。文中研究了群智感知原理,结合普适环境下情境信息的特点,提出了移动终端智能引擎平台。该平台通过接口能实时、有效地获取、处理用户的感知数据,还原用户情境,获取用户需求,并把用户需求和处理好的数据供第三方应用使用,第三方应用通过平台提供的接口提供应用服务。实验证明,该平台能够有效地获取用户情境信息,提供给第三方应用。     

移动终端群智感知研究

随着移动终端集成了越来越多的内置传感器,移动群智感知成为近几年来的研究热点。通过对移动终端传感器感知数据的收集分析处理,用户所处情境便能被识别,还原用户所处场景,为用户提供个性化服务。文中通过归纳国内外的最新研究成果,提出了移动终端群智感知模型,并从数据处理、激励机制和群智感知应用、群智感知平台等几个方面具体归纳概括了国内外的研究趋势。文中归纳了最新的数据处理技术和群智感知应用场景,并提出了竞争和协作相辅相成的激励模式。     

Find truth in the hands of the few: acquiring specific knowledge with crowdsourcing

Crowdsourcing has been a helpful mechanism to leverage human intelligence to acquire useful knowledge.However, when we aggregate the crowd knowledge based on the currently developed voting algorithms, it often results in common knowledge that may not be expected. In this paper, we consider the problem of collecting specific knowledge via crowdsourcing. With the help of using external knowledge base such as WordNet, we incorporate the semantic relations between the alternative answers into a probabilisticmodel to determine which answer is more specific. We formulate the probabilistic model considering both worker’s ability and task’s difficulty from the basic assumption, and solve it by the expectation-maximization (EM) algorithm. To increase algorithm compatibility, we also refine our method into semi-supervised one. Experimental results show that our approach is robust with hyper-parameters and achieves better improvement thanmajority voting and other algorithms when more specific answers are expected, especially for sparse data.     

Survey on differential privacy and its progress

With the arrival of the era of big data sharing,data privacy protection issues will be highlighted.Since its introduction in 2006,differential privacy technology has been widely researched in data mining and data publishing.In recent years,Google,Apple and other companies have introduced differential privacy technology into the latest products,and differential privacy technology has become the focus of academia and industry again.Firstly,the traditional centralized model of differential privacy was summarized,from the perspective of analysis of data mining and data released in the differential privacy way.Then the latest local differential privacy regarding data collection and data analysis based on the local model was described,involving crowdsourcing with random response technology,BloomFilter,statistical inference techniques.Finally,the main problems and solutions of differential privacy technology were summarized.     

Factors influencing bid-winning performance in mixed crowdsourcing: The persuasive effect of credible information sources

Mixed crowdsourcing is increasingly becoming the main organizational model of domestic crowdsourcing platforms. However, research on the interpretation of winning performance fails to focus on the persuasive effect of the credibility of the contractor's information source on the contractee's decision making. Based on source credibility theory (SCT), this study constructs a model of the factors influencing the contractor's bid-winning performance based on three aspects—credibility, professionalism, and attractiveness—and examines the moderating effect of positive contractor evaluations from previous tasks on the bid decision. The results reveal that integrity guarantee and contact authentication (which belong to the credibility dimension), as well as ability level and professional identity (professionalism dimension) positively affect the contractor's bid-winning performance, and that an inverted-U-shaped relationship exists between the number of services displayed by the contractors (attractiveness dimension) and bid-winning performance.     

基于组合双向拍卖的物联网搜索任务分配机制

如何合理地分配搜索任务,进而激励用户加入到搜索中是物联网搜索亟需解决的关键问题。针对物联网中数据实效性强的特点,结合物联网搜索中用户的高异构性和动态性,提出一种基于组合双向拍卖的搜索任务分配模型,从市场供求关系的角度描述了搜索发起者、搜索参与者和搜索引擎之间的关系。首先引入了竞价价值的概念,提出了一种基于贪心策略的启发式算法确定竞拍成功的用户集合,然后提出一种基于临界价格的定价算法,确保用户的竞价反映了其真实估价。理论分析及实验结果证明所提任务分配机制在保证激励相容性、合理性的基础上,有效提高了物联网搜索引擎的效率。     

WUDAPT项目：城市形式与功能信息的众包解决方案及其应用

面对全球城市气候研究中的数据鸿沟,一个城市气候领域的先锋研究小组提出了WUDAPT项目以克服获取城市数据的障碍。文章基于“众包”理念,从城市形式与功能信息收集的视角,介绍了WUDAPT项目的概念和数据分级,分析了城市尺度（0级）、街区与建筑尺度（1、2级）的数据收集与应用的研究进展。文章指出WUDAPT将促进基于城市气候视角的城市形态研究方法的重大转变,并探讨了其在气候敏感型城市设计与规划中的应用潜力。     

具有隐私保护的车联网空间众包任务分配方法

为了解决传统车联网空间众包中集中式空间众包服务器不可信和易遭受攻击给用户隐私带来极大威胁的问题,提出区块链架构下具有隐私保护的车联网空间众包任务分配方法. 基于区块链技术,设计分布式可信的车联网空间众包系统. 采用多密钥全同态加密算法实现任务分配,支持对不同车辆用户 (密钥) 的密文数据进行任务分配,降低隐私泄露的可能性. 实验分析表明,采用该方法能够有效地保护用户隐私信息,任务分配的计算时间开销与现有研究方法相比下降了34.3%,提高了任务分配的效率.     

基于众包的外卖配送订单选择研究

各外卖平台均提供了兼职配送员参与众包服务的渠道。与专职配送员相比,兼职配送员有着“路径开放、时间有限、最终目的地确定”等诸多不同的特点。基于兼职配送特点,为了提高众包配送员的接单效率,提高兼职收益,对众包模式下的订单选择及订单执行路径进行深入分析,提出将二者进行统一考虑的双层算法：在底层建立众包外卖配送路径规划模型,并使用改进的遗传算法求解;第2层利用贪心算法调用底层模型,通过比较配送收益进行订单选择,使得兼职人员的配送收益最大。通过算例实验,验证模型及算法的合理性及有效性条件,发现算法的计算时间随备选订单数量增加线性增加。在现实应用中,需要通过对备选订单进行打分排序,控制“订单池”规模,则能在可接受时间内得到较高质量的选择结果。