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Proceedings of the XV Brazilian Symposium on Information Systems最新文献

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Exploring Deep Features and Transfer Learning for Plant Species Recognition 探索植物物种识别的深度特征和迁移学习
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330264
Marcondes Coelho Feitoza, Wanderson Barcelos da Silva, R. Calumby
In recent years, with the evolution of the Convolutional Neural Networks, the automatic recognition of plant species from images became a very relevant research topic for scientists, researchers, and students in the field of botany. However, some problems related to the selection of features that best represent the characteristics of a particular species are still challenging due to the great variability of these characteristics within images from the same species and also the similarity of some characteristics between different species. In this sense, we propose a comparative study of Deep Convolutional Neural Networks to extract the feature vectors, here called "Deep Features", from the images of multi-organ plant observations. Moreover, eight variations of the Support Vector Machine (SVM) classifier were used for the assessment of the impact of three different Deep Features on the automatic image-based recognition of plant species. The evaluation protocol adopted for the classifiers was the Stratified 10-fold Cross Validation. As a result, the experiments demonstrate that higher dimensional Deep Features, in our case based on VGG-16 and VGG-19 networks, when exploited with the polynomial kernel SVM classifier and the One-vs-Rest decomposition method presented better classification effectiveness in the proposed study. Beyond it, this work highlights the fact that even in the context of transfer learning with deep features, the adequate selection of the baseline network is extremely important.
近年来,随着卷积神经网络的发展,从图像中自动识别植物物种成为植物学领域的科学家、研究人员和学生非常关注的研究课题。然而,一些与选择最能代表特定物种特征的特征相关的问题仍然具有挑战性,因为这些特征在同一物种的图像中具有很大的可变性,并且不同物种之间的某些特征具有相似性。在这个意义上,我们提出了一种深度卷积神经网络的比较研究,从多器官植物观测图像中提取特征向量,这里称为“深度特征”。此外,利用支持向量机(SVM)分类器的8种变体,评估了3种不同深度特征对植物物种自动图像识别的影响。对分类器采用的评价方案为分层10倍交叉验证。实验结果表明,基于VGG-16和VGG-19网络的高维深度特征与多项式核支持向量机分类器和One-vs-Rest分解方法相结合,在本文研究中具有更好的分类效果。除此之外,这项工作强调了这样一个事实,即即使在具有深度特征的迁移学习背景下,充分选择基线网络也是极其重要的。
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引用次数: 3
ICT Governance: A View of Adoption of Best Practices in Enterprises of Sergipe State 信息通信技术治理:对塞尔希佩州企业采用最佳做法的看法
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330268
Claudio Junior Nascimento da Silva, Quelita A. D. S. Ribeiro, M. S. Soares, R. Nascimento
Information and Communication Technologies (ICT) have become fundamental in the organizational process. In order to align ICT objectives with business objectives, many organizations make use of governance practices that not only help in the management of ICT, but also allow for transparency and control over spending, investment and objectives. This study aims to identify, through the application of a survey, the use of the best practices of ICT governance in the scope of companies of the State of Sergipe. It also seeks to understand how is the strategic planning and alignment between ICT and business in these companies.
信息和通信技术(ICT)已经成为组织过程中的基础。为了使ICT目标与业务目标保持一致,许多组织使用治理实践,这些实践不仅有助于ICT的管理,而且还允许对支出、投资和目标进行透明和控制。本研究旨在通过一项调查的应用,确定在塞尔吉佩州的公司范围内使用信息通信技术治理最佳实践的情况。它还试图了解这些公司如何在信息通信技术和业务之间进行战略规划和协调。
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引用次数: 5
Louvre 罗浮宫
Pub Date : 2019-05-20 DOI: 10.5040/9781350096462.0141
Marcelo Iury S. Oliveira, Bernadette Farias Lóscio
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引用次数: 3
Semantic Enrichment of Web Data for the Provision of an Unified Data Repository of Brazilian Missing Persons 为提供巴西失踪人员统一数据存储库而对Web数据进行语义充实
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330267
Jorão Gomes Jr., Nicolas Ferranti, Jairo Francisco de Souza
Communication and data technologies are becoming closely linked to people's lives. Therefore it is natural to make use of all this progress to reduce and solve social problems. In order for government and society to make the most appropriate decisions to deal with civilian disappearance, it's necessary to have a well-structured source of information. In several countries, it's difficult to access government data, since information is dispersed, not connected and poorly structured. So this work presents a framework to gather information on civil disappearance in Brazil through techniques such as Data Scraping and Linked Data. The goal is to make available an automatic data centralization of these individual cases, and to encourage the use of standards for the publication of data that are frequently ignored by organizations, hindering analysis and decision making on data.
通信和数据技术与人们的生活紧密相连。因此,利用所有这些进步来减少和解决社会问题是很自然的。为了让政府和社会做出最恰当的决定来处理平民失踪,有必要有一个结构良好的信息来源。在一些国家,很难获得政府数据,因为信息是分散的,没有联系,结构也很差。因此,这项工作提出了一个框架,通过数据抓取和关联数据等技术收集巴西民事失踪信息。目标是提供这些个案的自动数据集中,并鼓励使用标准来发布经常被组织忽视、妨碍对数据进行分析和决策的数据。
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引用次数: 0
LaNa2
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330281
Adolfo P. Guimarães, T. Bispo, A. Azevedo, Hendrik T. Macedo
Many tasks in various areas of science and society depend on interaction with the computer. The more transparent and simple the interaction, the better and faster the results will become. The gain in productivity is most evident when the tasks become more complex and the amount of data available increases exponentially. For example, amount of data produced in social networks. In these case, the manual evaluation is almost impossible. Thus, the study of techniques and applications that extract and interpret this data automatically has become an essential task in the decision making of the most diverse areas. This work aims at the extension and demonstration of LaNa2: a web platform for the collection, processing, analysis and visualization of textual contents in a clear and objective way. The main differential in comparison with other tools is its free access, in addition to the adoption of Machine Learning models for textual classification. We compare LaNa2 with other tools available in the market and run experiments to demonstrate their functionality.
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引用次数: 0
A Domain-Sensitive Threshold Derivation Method 一种域敏感阈值推导方法
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330252
Allan Mori, Gustavo Vale, Elder Cirilo, Eduardo Figueiredo
Software metrics provide means to quantify several attributes of information systems. The effective measurement is dependent of appropriate metric thresholds as they allow characterizing the quality of information systems. Several methods have been proposed to derive metric thresholds, however, previous methods do not take characteristics of software domains into account, such as the difference between size and complexity of systems from different domains. Instead, they rely on (generic) thresholds that are derived from heterogeneous systems. Although derivation of reliable thresholds has long been a concern, we also lack empirical evidence about threshold variation across distinct mobile software domains. This paper proposes a domain-sensitive method to derive thresholds that respects metric statistics and is based on benchmarks of systems from the same domain. To evaluate our method, we manually mined one hundred mobile systems from Fossdroid, measured them using a set of seven well-known metrics, derived thresholds, and validated them through qualitative and quantitative analyses. As a result, we observed that our method gathered more reliable thresholds considering software domain as a factor when building benchmarks for threshold derivation.
软件度量提供了量化信息系统的几个属性的方法。有效的度量依赖于适当的度量阈值,因为它们允许表征信息系统的质量。已经提出了几种方法来推导度量阈值,然而,以前的方法没有考虑到软件领域的特征,例如不同领域系统的大小和复杂性之间的差异。相反,它们依赖于来自异构系统的(通用)阈值。虽然可靠阈值的推导长期以来一直受到关注,但我们也缺乏关于不同移动软件领域阈值变化的经验证据。本文提出了一种基于同一领域系统基准的、尊重度量统计的阈值的领域敏感方法。为了评估我们的方法,我们从Fossdroid中手动挖掘了100个移动系统,使用一组7个众所周知的指标来测量它们,推导出阈值,并通过定性和定量分析来验证它们。因此,我们观察到,在为阈值派生构建基准时,我们的方法将软件域作为一个因素来收集更可靠的阈值。
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引用次数: 1
UFJF-MLTK: a framework for machine learning algorithms UFJF-MLTK:一个机器学习算法框架
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330273
Mateus Coutinho Marim, A. M. Oliveira, Saulo Moraes Villela
Machine learning techniques have become increasingly common due to the extension of their application domains and because they can improve their performance when exposed to new data. Several methods have been proposed to address problems of the area, bringing the challenge of comparing different methods to find the one that best solves a problem. Frameworks and libraries focused on learning algorithms can reduce this effort. This paper describes the UFJF-MLTK, an object-oriented framework that helps to choose between different methods, in the development of new algorithms through the instantiation of a C++ class architecture that covers various types of learning algorithms and also helps in teaching the subject. We discuss the problems faced in the project architecture, the components of the framework, the algorithms that currently compose it, how it was documented and examples of its instantiation.
机器学习技术已经变得越来越普遍,因为它们的应用领域的扩展,因为它们可以在暴露于新数据时提高它们的性能。已经提出了几种方法来解决该地区的问题,这带来了比较不同方法以找到最好解决问题的方法的挑战。专注于学习算法的框架和库可以减少这种工作量。本文描述了UFJF-MLTK,一个面向对象的框架,有助于在不同的方法之间进行选择,在新算法的开发中,通过实例化一个c++类体系结构,涵盖了各种类型的学习算法,也有助于教学的主题。我们讨论了项目架构中面临的问题,框架的组件,当前构成它的算法,它是如何被记录的以及它的实例化的例子。
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引用次数: 0
Level UP: Mapping Hard Skills of IT Practitioners to support the Project Management 升级:映射IT从业者的硬技能,以支持项目管理
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330211
V. Milon, Ricardo Araújo, Osenias Oliveira, Andréia Vieira, Adriano Mendes, Luís Braga, B. Ferreira
Mapping skills is important for software development organizations. Knowing the skills of the company practitioners helps the managers in making decisions to team building and to know what skills are necessary to development of projects. Identifying the adequate practitioner can contribute to good quality and minimize the time spent on the project. To optimize the process of team formation and management of competences, a software company carried out a process of mapping the skills of professionals in the area of software development. The process of identifying and organizing the competencies was carried out between the members of the development teams and the managers. From the mapping, we developed a tool that helped managers to have an overview of the company's competencies and facilitate the decisions making about which practitioners to allocate in each project, identify training needed to acquire competencies, and if was necessary contracting other practitioners. In addition, practitioners could gain insight into skills they could improve or acquire to fulfill certain roles within the company.
映射技能对于软件开发组织来说非常重要。了解公司从业者的技能可以帮助管理者做出团队建设的决策,并了解开发项目所需的技能。确定合适的执行者有助于提高质量,并最大限度地减少在项目上花费的时间。为了优化团队组建和能力管理的过程,一家软件公司在软件开发领域开展了一个绘制专业人员技能的过程。识别和组织能力的过程是在开发团队成员和管理人员之间进行的。从映射中,我们开发了一个工具,帮助管理人员对公司的能力有一个概览,并促进有关在每个项目中分配哪些从业者的决策,确定获得能力所需的培训,以及是否有必要与其他从业者签订合同。此外,从业者可以深入了解他们可以改进或获得的技能,以履行公司内的某些角色。
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引用次数: 1
Sequential Sentiment Pattern Mining to Predict Churn in CRM Systems: A Case Study with Telecom Data 顺序情感模式挖掘预测客户关系管理系统的流失:电信数据的案例研究
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330220
Thiago P. Pimentel, R. Goldschmidt
Competitive markets have driven companies to engage in customer retention. Therefore, anticipating client churn (i.e., cancellation) became a significant challenge. Sequential pattern detection is one of the most popular approaches to the churn prediction problem. Although promising, initiatives based on this approach do not take into account information that can be useful to detect churn: the underlying sentiment in the interactions between client and company. This study raises the hypothesis that considering such information may improve churn prediction, since they may indicate the client's satisfaction level with services and products. Hence, the present study aims to evaluate the validity of the formulated hypothesis. For this purpose, it applies a method that generates churn prediction models from the combination of sequential pattern detection with sentiment extraction from customer-company interactions. Experimental results from telecom data confirm the adequacy of the generated models and of the raised hypothesis.
竞争激烈的市场促使公司致力于留住客户。因此,预测客户流失(即取消)成为一个重大挑战。序列模式检测是客户流失预测最常用的方法之一。虽然很有希望,但基于这种方法的举措并没有考虑到可能对检测客户流失有用的信息:客户和公司之间互动中的潜在情绪。本研究提出假设,考虑这些信息可能会改善流失预测,因为它们可能表明客户对服务和产品的满意度。因此,本研究旨在评估所制定的假设的有效性。为此,它应用了一种方法,该方法结合顺序模式检测和从客户-公司交互中提取情感来生成流失预测模型。来自电信数据的实验结果证实了所生成模型和所提出假设的充分性。
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引用次数: 0
Vulnerability detection techniques and tools and their relationship to agile methods and software quality and service models 漏洞检测技术和工具及其与敏捷方法、软件质量和服务模型的关系
Pub Date : 2019-05-20 DOI: 10.1145/3330204.3330257
Lígia Cássia M. C. Santos, E. Prado, M. Chaim
Information systems need to be safe to achieve their goals. Thus, during development one needs to detect possible vulnerabilities present in the software. This paper aims to describe the use of vulnerability detection techniques and tools (VDTT) in complex environments and its relationship to software quality and service models in teams that use agile methods. To do so, a survey was carried out listing 18 techniques and tools that used three well-known processes of secure software development. The survey was applied to 76 members of agile software development teams who have already deployed, are in the process of deploying, or are going to deploy vulnerability detection techniques and tools in the projects. From the data collected, we were able describe the use of VDTT in complex development environments and associations between the adoption of software quality and service models and the use of VDTTs. For this purpose, Fischer's exact test was used to analyze and interpret the associations found.
信息系统需要安全才能实现其目标。因此,在开发过程中需要检测软件中可能存在的漏洞。本文旨在描述在复杂环境中使用漏洞检测技术和工具(VDTT)及其与使用敏捷方法的团队中的软件质量和服务模型的关系。为此,我们进行了一项调查,列出了使用三种众所周知的安全软件开发过程的18种技术和工具。这项调查应用于敏捷软件开发团队的76名成员,他们已经部署了、正在部署过程中,或者准备在项目中部署漏洞检测技术和工具。从收集到的数据中,我们能够描述VDTT在复杂开发环境中的使用,以及采用软件质量和服务模型与使用VDTT之间的关联。为此,Fischer的精确检验被用来分析和解释所发现的关联。
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引用次数: 0
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Proceedings of the XV Brazilian Symposium on Information Systems
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