Integration by communication: knowledge exchange in global outsourcing of product software development

Global outsourcing is a growing trend among independent software vendors. In these projects like other distributed work, distances have negative effects on communication and coordination, directly impacting performance. We present a normative model designed to address this issue by improving communication and knowledge exchange. The model consists of six distinct practices and a tool blueprint, each coming with practical guidelines. It is based in part on two case studies of Dutch software vendors who have successfully outsourced part of their activities to an Eastern European outsourcing vendor, and validated by a panel of six experts from industry and the scientific community. It is concluded that knowledge exchange in global software outsourcing is a by‐product of efforts to enhance communication and coordination, rather than specific technical solutions. By committing to sharing knowledge, emphasizing transparency and integrating the outsourcing team into their organizations, customers from the product software business can realize the benefits of global outsourcing.     

Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.     

Credit rating with a monotonicity-constrained support vector machine model

Deciding whether borrowers can fulfill their obligations is a major issue for financial institutions, and while various credit rating models have been developed to help achieve this, they cannot reflect the domain knowledge of human experts. This paper proposes a new rating model based on a support vector machine with monotonicity constraints derived from the prior knowledge of financial experts. Experiments conducted on real-world data sets show that the proposed method, not only data driven but also domain knowledge oriented, can help correct the loss of monotonicity in data occurring during the collecting process, and performs better than the conventional counterpart.     

基于先验知识的自适应多叉树防碰撞算法

为提高无线射频识别(RFID)系统快速识别大量标签的能力,提出一种基于先验知识的自适应多叉树防碰撞算法。利用标签访问的规律性和标签分布的随机性,在不同的搜索深度,根据已有的先验知识和碰撞比特信息估计待识别的标签数量,从而动态地自适应选择搜索叉树。通过有效减少碰撞和空闲时隙数,大幅提高读写器搜索和识别标签的能力。理论分析与仿真实验结果表明,该算法能克服传统自适应多叉树防碰撞算法的缺点,合理选择初始搜索叉树,尤其在待识别标签数量较多的场合,可有效提高RFID系统的吞吐率。     

An exploratory study on ontology engineering for software architecture documentation

The usefulness of Software Architecture (SA) documentation depends on how well its Architectural Knowledge (AK) can be retrieved by the stakeholders in a software project. Recent findings show that the use of ontology-based SA documentation is promising. However, different roles in software development have different needs for AK, and building an ontology to suit these needs is challenging. In this paper we describe an approach to build an ontology for SA documentation. This approach involves the use of typical questions for eliciting and constructing an ontology. We outline eight contextual factors, which influence the successful construction of an ontology, especially in complex software projects with diverse AK users. We tested our ‘typical question’ approach in a case study and report how it can be used for acquiring and modeling AK needs.     

大数据系统和分析技术综述

首先根据处理形式的不同,介绍了不同形式数据的特征和各自的典型应用场景以及相应的代表性处理系统,总结了大数据处理系统的三大发展趋势;随后,对系统支撑下的大数据分析技术和应用(包括深度学习、知识计算、社会计算与可视化等)进行了简要综述,总结了各种技术在大数据分析理解过程中的关键作用;最后梳理了大数据处理和分析面临的数据复杂性、计算复杂性和系统复杂性挑战,并逐一提出了可能的应对之策.     

基于自然语言处理的算法知识名称发现

网络中的很多程序资源在知识概念上有内在的联系,却没有超链接将它们连接在一起。将网络程序资源中的算法知识名称获取出来,组织成一个算法知识专家库文件,用于识别程序设计资源所含的知识点,即可将程序设计资源按知识点相互联系。为了自动获取程序资源中的算法知识名称,提出一种基于自然语言处理的算法知识名称发现方法。通过发现含有算法知识名称语句的字符串模式,从程序资源中提取可能含算法知识名称的字符串,从中找出最有可能出现在算法知识名称中的分词,并根据这些分词获取算法知识名称。实验结果表明,与原有人工整理出的算法知识名称集合相比,该方法新增了11.2%的算法知识点和13.6%的算法知识名称。     

语言真值直觉模糊逻辑的知识推理

针对格蕴涵代数、直觉模糊集及知识表示、基于语言真值直觉模糊代数的相关性质及运算方法,提出了六元语言真值直觉模糊代数的相关逻辑性质,并在六元语言真值直觉模糊知识表示的基础上,将模糊推理的CRI方法进行扩展,研究得出了六元语言真值直觉模糊推理的方法即6LTV-CRI算法。而后将直觉模糊推理与六元语言真值直觉模糊推理方法进行对比分析,验证了6LTV-CRI推理算法的合理性,并分析了其优缺点。     

企业大数据治理研究

介绍了面对大数据的数据量大、种类多、速度快和高价值的处理技术挑战,企业应当如何建立可靠的大数据平台。利用信息架构原则和实践,实现大数据与企业数据的灵活集成,通过结合使用分布式文件系统、NoSQL与关系型数据库,企业可以获取、组织和分析其所有企业数据(包括结构化和非结构化数据),从而做出最科学的决策。