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Classifying Web page features to detect DaaS 对Web页面特征进行分类以检测DaaS
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3431085
Israel Cerqueira Motta Neto, Daniela Barreiro Claro
A SaaS (Software as a Service) can transparently consume a DaaS (Data as a Service). However, heterogeneous DaaS and its evolution can disrupt the SaaS execution. In such cases, a middleware can provide such interoperability and monitor the DaaS trackback and its evolution by retrieving its metadata. For instance, the middleware MIDAS manually provides such interoperability. Considering the Web and the number of web pages and DaaS available, this task may be time-consuming and unfeasible. To automate this task, it is firstly important to distinguish a DaaS from a typical web page. Thus, this work aims to develop a model to identify DaaS from the Web. We collected a set of features from DaaS and non-DaaS pages to train our model, and we discuss some issues and strengths of our approach. We evaluate precision and recall, but we also measure the performance because this model will be embedded into a crawler in future versions of MIDAS. Our findings achieve high precision and low execution time, which can position our work in a proper direction to MIDAS evolution.
SaaS(软件即服务)可以透明地使用DaaS(数据即服务)。然而,异构的DaaS及其演变可能会破坏SaaS的执行。在这种情况下,中间件可以提供这种互操作性,并通过检索DaaS的元数据来监视DaaS的回溯及其演变。例如,中间件MIDAS手动提供这种互操作性。考虑到Web以及可用的Web页面和DaaS的数量,此任务可能非常耗时且不可行。为了自动化这项任务,首先要区分DaaS和典型的web页面。因此,本工作旨在开发一个从Web中识别DaaS的模型。我们从DaaS和非DaaS页面收集了一组特征来训练我们的模型,并讨论了我们方法的一些问题和优势。我们评估了精确度和召回率,但我们也测量了性能,因为这个模型将被嵌入到未来版本的MIDAS的爬虫中。我们的研究结果实现了高精度和低执行时间,这可以使我们的工作朝着MIDAS进化的正确方向发展。
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引用次数: 0
Analysis of the Subjectivity Level in Fake News Fragments 假新闻片段的主体性水平分析
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3430978
Lucas Lima Vieira, Caio Libânio Melo Jerônimo, C. E. Campelo, L. Marinho
The widespread of fake news is increasingly worrying society and demanding approaches for mitigation. Although many approaches have been proposed to fake news detection, there is still a lack of works that deeply investigate their structure. Our study has been motivated by two findings discussed in existing works: the first is the fact that fake news usually mix real and fake information to mislead readers; the second is that subjective language is a resource commonly exploited by fake news producers. Therefore, to better understand how fake news is structured, we perform an analysis on the way the subjective language is exploited in different situations inside the fake news documents. For this, we built a dataset by manually identifying fake parts of news articles, and we also propose tags to categorize the fragments in documents. The proposed tags categorize the fake news fragments according to their kind of falsehood in document. To reveal subjectivity nuances within the fragments, we use the Word Movers Distance and a set of subjectivity lexicons in the Portuguese language. Our results indicate that the fragmentation of news allows the identification of subjectivity markers that cannot be identified when considering the entire documents.
假新闻的广泛传播日益令社会担忧,并要求采取缓解措施。虽然人们提出了许多检测假新闻的方法,但对其结构进行深入研究的工作仍然缺乏。我们的研究受到现有研究中讨论的两个发现的推动:第一,假新闻通常将真实信息和虚假信息混合起来误导读者;第二,主观语言是假新闻制造者经常利用的资源。因此,为了更好地理解假新闻的结构,我们对假新闻文档中不同情况下主观语言的利用方式进行了分析。为此,我们通过手动识别新闻文章的虚假部分建立了一个数据集,并且我们还提出了标记来对文档中的片段进行分类。所提出的标签根据其在文件中的虚假程度对假新闻片段进行分类。为了揭示碎片中主体性的细微差别,我们使用了单词移动距离和一套葡萄牙语主体性词汇。我们的研究结果表明,新闻的碎片化可以识别主体性标记,而在考虑整个文档时无法识别主体性标记。
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引用次数: 6
Let's talk about the role and impact of Social Computing in our lives 让我们来谈谈社会计算在我们生活中的作用和影响
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3431927
Jonice Oliveira
Social Computing refers to digital systems that support social interactions. The use of online social networks is intensifying every day, increasing the number of users and the different ways of content access. Collaborative platforms are growing and expanding their use, from basic health care to entrepreneurship. What are the new users' behaviors? What do they look for? How do they interact? Computing is increasingly present in social relationships. Consequently, social relationships have changed the way Computing is done. We can chat with other people who are physically distant or discover new resources and a range of services. Can events be identified only by monitoring social media? Can we use online social networks to promote citizens' participation in the decisions of a community or city? What is behind people's access to online social networks? How are transparency, filter bubbles, echo chambers, bias, and users' addiction issues handled? Can human behavior be modeled, simulated, and predicted? What are the precautions that users need to take? Trying to answer these questions, we will show some works developed by the Laboratory of Social Computing and Network Analysis (Lab CORES).
社会计算指的是支持社会互动的数字系统。在线社交网络的使用每天都在加强,用户数量和访问内容的不同方式都在增加。从基本医疗保健到创业,协作平台的使用正在不断扩大。新用户的行为是什么?他们在寻找什么?它们是如何相互作用的?计算越来越多地出现在社会关系中。因此,社会关系改变了计算的方式。我们可以和距离遥远的人聊天,或者发现新的资源和一系列的服务。仅仅通过监控社交媒体就能识别事件吗?我们能否利用在线社交网络促进公民参与社区或城市的决策?人们访问在线社交网络的背后是什么?如何处理透明度、过滤气泡、回音室、偏见和用户成瘾问题?人类行为可以被建模、模拟和预测吗?用户需要采取哪些预防措施?为了回答这些问题,我们将展示社会计算和网络分析实验室(Lab CORES)开发的一些作品。
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引用次数: 2
Technologies applied in the care of patients with Alzheimer's disease: a systematic review 阿尔茨海默病患者护理中应用的技术:系统综述
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3431753
Savanna Denega Machado, J. Barbosa
About 50 million people around the world have Alzheimer's disease. The main characteristic of the disease is the deterioration of cognitive function, and as a result of the fact that the disease has no cure or treatment. This article presents a systematic mapping of the literature to identify articles that use technological devices to assist patients with Alzheimer's disease, in order to show an overview of the literature, identifying gaps and research opportunities. The systematic mapping study was conducted out in six databases, including articles from January 2015 to July 2020. An initial search resulted in 12,177 articles, of which 28 were selected after applying the filter criteria. The main results obtained are: (1) most articles (25.71%, 7/28) reported solutions used in devices with sensor development; (2) most technologies (22.06%, 6/28) were focused on monitoring; (3) most papers (82.14%, 23/28) address solutions for dementia, citing Alzheimer's disease indirectly; (4) more than half of the studies aimed at monitoring patients (54%, 15/28); (5) most studies (82.14%, 23/28) performed an experiment with patients with the disease. The results corroborate the need for technological devices to help caregivers monitor patients, in addition to evidence of research opportunities in palliative care and support for daily activities.
全世界大约有5000万人患有阿尔茨海默病。这种疾病的主要特征是认知功能的恶化,而且由于这种疾病无法治愈或治疗。这篇文章提出了一个系统的文献映射,以识别使用技术设备来帮助阿尔茨海默病患者的文章,以显示文献的概述,找出差距和研究机会。系统的制图研究在六个数据库中进行,包括2015年1月至2020年7月的文章。最初的搜索结果是12177篇文章,其中28篇在应用过滤标准后被选中。得到的主要结果是:(1)大多数文章(25.71%,7/28)报道了用于传感器开发的设备的解决方案;(2)以监测为主的技术占22.06% (6/28);(3)大多数论文(82.14%,23/28)涉及痴呆症的解决方案,间接引用阿尔茨海默病;(4)半数以上的研究以监测患者为目的(54%,15/28);(5)大多数研究(82.14%,23/28)采用患者实验。研究结果证实了技术设备的必要性,以帮助护理人员监测患者,以及缓和治疗和日常活动支持方面的研究机会。
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引用次数: 4
Combining complementary diversification models for personalized POI recommendations 结合互补的多样化模型,个性化推荐POI
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3431754
Heitor Werneck, N. Silva, Fernando Mourão, A. Pereira, L. Rocha
Location-Based Social Networks (LBSNs) have become important tools for people interested in exploring new places. And, similar to traditional recommendation domains, handling the trade-off between accuracy and diversity is a major challenge to provide useful recommendations. However, this domain adds an equally relevant dimension to this challenge: the geographical distance between users and each point-of-interest (POI). Besides understanding how the characteristics of services offered by each POI fit the user needs, realizing how far users are willing to move to fulfill these needs is of paramount relevance. Moreover, the users present distinct levels of interest in diversification. In this paper, we propose a strategy to provide POI recommendations linearly combining categorical and geographical diversifications in a personalized way. Indeed, our strategy is able to prioritize quality dimensions that better suit the personalized needs of each user, with gains up to 10% when compared with unpersonalized versions.
基于位置的社交网络(LBSNs)已经成为人们探索新地方的重要工具。而且,与传统的推荐领域类似,处理准确度和多样性之间的权衡是提供有用推荐的主要挑战。然而,这个领域为这一挑战增加了一个同样相关的维度:用户和每个兴趣点(POI)之间的地理距离。除了了解每个POI提供的服务的特征如何满足用户需求之外,了解用户愿意在多大程度上满足这些需求也是至关重要的。此外,用户对多样化表现出不同程度的兴趣。在本文中,我们提出了一种策略,以个性化的方式将类别多样化和地理多样化线性结合起来提供POI建议。事实上,我们的策略能够优先考虑更适合每个用户个性化需求的质量维度,与非个性化版本相比,收益高达10%。
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引用次数: 1
Characterization and Analysis of Open Brazilian Judiciary Data 巴西司法公开数据的特征与分析
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3430979
Danilo B. Seufitelli, Weverton R. R. Mata, Rafael Souza, Michele A. Brandão, Mirella M. Moro
Govern transparency is widely accepted as an effective democratic process in many countries. In Brazil, the information-access law contributes to public administration transparency, as public data is available on the Web. However, such data are in different formats and not standardized, which makes it difficult to obtain information, mainly in an automated way. Hence, this work presents an enrichment methodology for an existing open Brazilian judiciary database, a characterization of the available data, and an analysis of the data about judiciary professionals and their earns. The results reveal a lack of linear correlations between the high salaries and their personal benefits. Also, there is a discrepancy between Judiciary salaries and advantages through Brazilian regions, which may be explained by the higher living costs in some regions. Finally, our study reveals the administrative Brazilian Judiciary data do not conform to all Open Government Data principles, and the enriched database helps to solve such problems.
在许多国家,政府透明度被广泛认为是一种有效的民主进程。在巴西,信息获取法有助于提高公共行政的透明度,因为公共数据可以在网上获得。然而,这些数据格式不同,没有标准化,这使得难以获取信息,主要是通过自动化的方式获取。因此,这项工作为现有的开放巴西司法数据库提供了一种丰富的方法,对现有数据进行了描述,并对司法专业人员及其收入的数据进行了分析。研究结果显示,高薪与个人福利之间缺乏线性相关性。此外,巴西各地区司法人员的工资和福利也存在差异,这可能是一些地区生活成本较高的原因。最后,我们的研究揭示了巴西司法行政数据并不符合所有的开放政府数据原则,而丰富的数据库有助于解决这一问题。
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引用次数: 0
MSL-DE: A Lexical Substitution Method based on Dictionaries and Embeddings 基于字典和嵌入的词汇替换方法
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3430982
Isaias Frederick Januario, Álvaro R. Pereira
Lexical Substitution has a noticeable evolution in the literature, mainly in the data sources used for the generation of substitutes that feed the process. Of course, dictionaries and thesauri are widely used for grouping synonyms in their structure, but the polysemy of words prevents a direct exchange of terms without analyzing the context. Vector space models, such as embeddings, are used to represent substitutes and also contexts. However, the representation of words considering only contextual factors, in many cases, may incur the approximation of terms that are not exactly synonyms. The characteristics mentioned above suggest that the simultaneous use of dictionaries and embeddings is a promising alternative for the process. Thus, we present a method using information contained in merged dictionaries, in addition to their linguistic relations structured in taxonomies. The method measures the preservation of the meaning of the sentence with the potential synonym by observing its frequency of application in small contexts. In addition, we also consider a complete context to generate input from vector operations highlighting the best synonyms in a previously selected set. The results show the efficiency of the method, surpassing many methods consolidated in the literature in the prediction of the best substitute for words contained in instances of a known benchmark.
词汇替代在文献中有一个明显的演变,主要是在用于生成代用品的数据源中。当然,字典和同义词典被广泛用于对其结构中的同义词进行分组,但是单词的多义性阻止了在不分析上下文的情况下直接交换术语。向量空间模型,如嵌入,用于表示替代品和上下文。然而,在许多情况下,仅考虑上下文因素的单词表示可能会导致不完全是同义词的术语的近似。上述特征表明,同时使用字典和嵌入是该过程的一个有希望的替代方案。因此,我们提出了一种使用合并字典中包含的信息的方法,以及它们在分类法中结构的语言关系。该方法通过观察潜在同义词在小语境中的使用频率来衡量其对句子意义的保留。此外,我们还考虑了一个完整的上下文,以从矢量操作中生成输入,突出显示先前选择的集合中的最佳同义词。结果表明了该方法的有效性,在预测已知基准实例中包含的单词的最佳替代方面超过了文献中整合的许多方法。
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引用次数: 0
A Generative Approach for Android Sensor-based Applications 基于Android传感器的应用生成方法
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3430976
Tarik Ponciano, D. Tabosa, Windson Viana, P. A. S. Duarte, Rafael Carmo
As smartphones increased in popularity, mobile devices became a crucial technological element of our time. Beyond the end-user platform, smartphones have several sensors to capture and characterise the user's context. Current Context-Aware Mobile (CAM) applications use this data to improve user experience by filtering data, services, and, even, adapting their behaviour. The development of CAM applications can be challenging for mobile developers, due to the diversity of mobile hardware ecosystem and sensor APIs' complexity. This paper presents EasyContext, a visual tool for designing and generating contextual rules for mobile devices, using the Google Awareness API as its contextual information provider. Mobile developers specify what to capture and when to react to context-changes in the visual tool and these contextual rules are exported to Android projects. We evaluated our approach with developers, which were selected to participate in a quasi-experiment. The experiment involves developing two mobile applications using both EasyContext and Google Awareness API. Preliminary results show that it is possible to build applications with fewer lines of code compared to the Google Awareness API. According to the developers, the proposed approach has better readability and makes it easier to design contextual rules.
随着智能手机的普及,移动设备成为我们这个时代至关重要的技术元素。除了终端用户平台,智能手机还有几个传感器来捕捉和描述用户的环境。当前的上下文感知移动(CAM)应用程序使用这些数据来过滤数据、服务,甚至调整用户的行为,从而改善用户体验。由于移动硬件生态系统的多样性和传感器api的复杂性,CAM应用程序的开发对移动开发人员来说是具有挑战性的。本文介绍了EasyContext,一个用于设计和生成移动设备上下文规则的可视化工具,使用Google Awareness API作为其上下文信息提供者。移动开发人员在可视化工具中指定捕获什么以及何时对上下文变化做出反应,这些上下文规则被导出到Android项目中。我们与开发人员一起评估了我们的方法,这些开发人员被选中参加了一个类似的实验。该实验包括使用EasyContext和Google Awareness API开发两个移动应用程序。初步结果表明,与Google Awareness API相比,用更少的代码行构建应用程序是可能的。根据开发人员的说法,该方法具有更好的可读性,并且更容易设计上下文规则。
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引用次数: 1
An approach to recommendation systems oriented towards the perspective of tourist experiences 基于旅游体验视角的推荐系统研究
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3430977
B. K. Santos, G. C. Filho, Yuri Almeida Lacerda
The Community-Contributed Geotagged Photos has widely contributed to the construction of tourism recommendation systems that facilitate the task of choosing points of interest (POIs) to visit, organizing itineraries, managing activities and improving tourist experiences when they are visiting an unfamiliar city. Tourists have driven by their aspirations, desires, and preferences. There is a new kind of traveler who instead to explore the most popular places in a city; they would like to have contact with local people and culture, exploring areas where the local people usually visit considering temporal issues, such as: parts of day, day of week, vacations, events, holidays, etc. This work presents the new recommendation model, a tourist recommender system that makes POIs recommendations considering the different interaction of tourists and residents around a city over time. This new model was constructed using Naive Bayes classifier and Collaborative Filtering. The experiments used data of 83.302 photos taken in the city of Rio de Janeiro published on Flickr and 242 locations identified through OpenStreetMap. The results demonstrated that this approach could make predictions based on the temporal context and considering differences between resident and tourist perspective being this work one of the first to consider the data yielded by residents like relevant to the build of recommendations.
社区贡献的地理标记照片对旅游推荐系统的构建做出了广泛的贡献,这些系统有助于游客在游览陌生城市时选择兴趣点(poi)、组织行程、管理活动和改善游客体验。游客们是由他们的愿望、欲望和偏好驱动的。有一种新的旅行者,他们宁愿去探索城市中最受欢迎的地方;他们想接触当地人和文化,探索当地人通常访问的地区,考虑时间问题,例如:一天的一部分,一周的一天,假期,事件,假期等。这项工作提出了一个新的推荐模型,一个游客推荐系统,它根据城市周围的游客和居民随时间的不同互动进行poi推荐。该模型采用朴素贝叶斯分类器和协同过滤技术构建。实验使用了在Flickr上发布的里约热内卢市拍摄的83.302张照片和通过OpenStreetMap确定的242个地点的数据。结果表明,这种方法可以根据时间背景进行预测,并考虑到居民和游客视角之间的差异,这是这项工作中第一个考虑到居民所产生的数据与建议的构建相关的工作之一。
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引用次数: 0
Analyzing YouTube Videos Shared on Whatsapp in the Early COVID-19 Crisis 分析在COVID-19危机早期在Whatsapp上分享的YouTube视频
Pub Date : 2020-11-30 DOI: 10.1145/3428658.3431090
Marisa Vasconcelos, É. Pereira, Samuel S. Guimarães, Manoel Horta Ribeiro, P. Melo, Fabrício Benevenuto
Whatsapp is the most popular messaging app in the world. It is not only used as a one-to-one messaging app but also as a platform for group discussion. Recently, Whatsapp has gained the spotlight for its role in disseminating (often low-quality) information. Our study focuses on YouTube videos shared by political-oriented public groups on Whatsapp for a month during the COVID-19 pandemic. Through a careful analysis of the topical distribution and the lexicon present in the videos shared, we shed light on the COVID-19 debate happening in these groups. Moreover, we compare COVID-19 related videos with other political videos being shared in the groups. We observe that videos that discuss political themes have more emotional attributes as well as topics related to typical right-wing concerns such as family, work, and religion than videos discussing both pandemic and politics.
Whatsapp是世界上最受欢迎的即时通讯应用。它不仅是一个一对一的消息应用程序,也是一个小组讨论的平台。最近,Whatsapp因其在传播(通常是低质量的)信息方面的作用而受到关注。我们的研究重点是在COVID-19大流行期间,以政治为导向的公共团体在Whatsapp上分享的一个月的YouTube视频。通过仔细分析分享视频中的主题分布和词汇,我们了解了这些群体中发生的关于COVID-19的辩论。此外,我们还将与COVID-19相关的视频与群中分享的其他政治视频进行了比较。我们观察到,与讨论流行病和政治的视频相比,讨论政治主题的视频具有更多的情感属性,以及与典型的右翼关注点(如家庭、工作和宗教)相关的主题。
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引用次数: 5
期刊
Proceedings of the Brazilian Symposium on Multimedia and the Web
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