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2016 11th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)最新文献

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Adaptive knowledge retrieval using semantically enriched folksonomies 使用语义丰富的大众分类法的自适应知识检索
Dimitrios Pappas, I. Paraskakis
Organizations invest considerable development effort in personalized systems to reap the benefits of knowledge management. Competition and the need for innovation imply in ever-changing and emerging needs that result in costly effort to redesign such systems. A flexible knowledge management approach should achieve personalization for organizations by adapting to the domain of the organization, meanwhile simplifying the incorporation of future knowledge retrieval needs. We describe such an approach that employs a knowledge management platform at its core, which supports adding and removing multiple folksonomies, constantly enriches them with semantics and provides domain-specific recommendations and semantic search capabilities. This approach to knowledge retrieval has been applied to the domain of homemade explosives and counter-terrorism efforts as part of the HOMER project. Preliminary evaluation from the perspective of the end-users - law enforcement, security and related agencies - is presented.
组织在个性化系统上投入了大量的开发工作,以获得知识管理的好处。竞争和创新的需要意味着不断变化和新出现的需求,导致重新设计这些系统的代价高昂。灵活的知识管理方法应该通过适应组织的领域来实现组织的个性化,同时简化对未来知识检索需求的整合。我们描述了这样一种方法,它以知识管理平台为核心,支持添加和删除多个大众分类法,不断地用语义丰富它们,并提供特定于领域的建议和语义搜索功能。作为HOMER项目的一部分,这种知识检索方法已应用于自制爆炸物和反恐工作领域。从最终用户-执法、安全和相关机构-的角度提出了初步评价。
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引用次数: 0
Community detection in complex networks based on DBSCAN* and a Martingale process 基于DBSCAN*和鞅过程的复杂网络社区检测
Ilias Gialampoukidis, T. Tsikrika, S. Vrochidis, Y. Kompatsiaris
Community detection is a valuable tool for analyzing and understanding the structure of complex networks. This work investigates the application of the density-based algorithm DBSCAN* to the community detection problem. Given, though, that this algorithm requires a lower bound for the community size to be determined a priori, this work proposes the application of a Martingale process to DBSCAN* so as to progressively detect communities at various levels of granularity, without the need to define in advance a single threshold for the minimum community size. In particular, the proposed DBSCAN*-Martingale community detection algorithm corresponds to an iterative process that progressively lowers the threshold of the size of the acceptable communities, while maintaining the communities detected for higher thresholds. Evaluation experiments are performed based on four realistic benchmark networks and the results indicate improvements in the effectiveness of the proposed DBSCAN*-Martingale community detection algorithm in terms of the Normalized Mutual Information and RAND metrics against several state-of-the-art community detection approaches.
社区检测是分析和理解复杂网络结构的重要工具。本文研究了基于密度的DBSCAN算法在社区检测问题中的应用。然而,鉴于该算法需要先验地确定社区规模的下界,本工作提出将鞅过程应用于DBSCAN*,以便在不同粒度级别上逐步检测社区,而无需事先定义最小社区规模的单个阈值。特别是,所提出的DBSCAN*-Martingale社区检测算法对应于一个迭代过程,该过程逐步降低可接受社区大小的阈值,同时保持较高阈值时检测到的社区。基于四个现实的基准网络进行了评估实验,结果表明,根据归一化互信息和RAND指标,与几种最先进的社区检测方法相比,所提出的DBSCAN*-鞅社区检测算法的有效性有所提高。
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引用次数: 11
Rudolf: An HTTP API for exposing semantically represented fiscal OLAP cubes 一个HTTP API,用于公开语义表示的财政OLAP多维数据集
Lazaros Ioannidis, Charalampos Bratsas, Sotiris Karabatakis, Panagiotis-Marios Filippidis, P. Bamidis
OpenSpending is the world's largest repository of open fiscal datasets. As of now it only supported loading datasets from CSV files, leaving out more heavily-structured formats like RDF. Rudolf, an RDF backend has been developed to expose Data Cube RDF triples and OLAP operations in JSON format through an OpenSpending-compatible HTTP API. This API can be directly utilized by the OpenSpending Viewer application to transparently offer aggregate visualizations for RDF fiscal datasets out of the box.
OpenSpending是世界上最大的开放财政数据集存储库。到目前为止,它只支持从CSV文件加载数据集,而不支持像RDF这样更结构化的格式。Rudolf已经开发了一个RDF后端,通过与openspending兼容的HTTP API以JSON格式公开Data Cube RDF三元组和OLAP操作。OpenSpending Viewer应用程序可以直接利用这个API,以开箱即用的方式透明地提供RDF财政数据集的聚合可视化。
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引用次数: 2
Thematic labeling of Twitter accounts using DBpedia properties 使用DBpedia属性对Twitter帐户进行主题标记
Gerasimos Razis, Ioannis Anagnostopoulos, Petr Šaloun
In this paper, we propose an iterative algorithm towards the automatic labeling of Twitter accounts in respect to thematic categories derived from DBpedia properties. We describe the rationale behind the selection of these thematic categories, and discuss their evaluation assessment. Finally, we propose and analyze two generic and adaptable methodologies for discovering the necessary linked data resources for further enhancing the thematic description of Twitter accounts.
在本文中,我们提出了一种迭代算法,用于根据DBpedia属性派生的主题类别自动标记Twitter帐户。我们描述了选择这些主题类别背后的基本原理,并讨论了它们的评估评估。最后,我们提出并分析了两种通用和适应性强的方法,用于发现必要的关联数据资源,以进一步增强Twitter帐户的主题描述。
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引用次数: 4
Xenia: A context aware tour recommendation system based on social network metadata information Xenia:基于社交网络元数据信息的上下文感知旅游推荐系统
Michalis Korakakis, Phivos Mylonas, E. Spyrou
Tour planning and point-of-interest (POI) recommendation are two challenging and time-consuming tasks for tourists, predominately due to the large number of POIs a travel destination may contain and the complex constraints and parameters associated with the trip itself (e.g., time, budget, etc.). In this paper we present Xenia, a context-aware platform aiming to construct travel routes (i.e., ordered visits to various POIs that maximize the user's travel experience) that adhere to the aforementioned limitations by modeling and solving the tour planning dilemma through the Orienteering Problem (OP). To achieve this, we use geo-tagged photos, collected from Flickr and exploit their metadata (e.g., time-stamps, geolocation and user-generated tags). By utilizing these spatio-temporal data, we are able to identify the trajectory patterns of tourists during their vacations and determine the most popular POIs in any given city, along with the tourists sequential POIs visits and their corresponding durations. Finally, we evaluate the effectiveness of the proposed system against a set of typical baseline approaches.
对于游客来说,旅游规划和兴趣点(POI)推荐是两个具有挑战性和耗时的任务,主要是因为旅游目的地可能包含大量的兴趣点,以及与旅行本身相关的复杂约束和参数(例如,时间,预算等)。在本文中,我们提出了Xenia,这是一个上下文感知平台,旨在通过建模并通过定向问题(OP)解决旅行规划困境,构建符合上述限制的旅行路线(即有序访问各种poi,以最大化用户的旅行体验)。为此,我们使用从Flickr收集的带有地理标记的照片,并利用它们的元数据(例如,时间戳、地理位置和用户生成的标签)。利用这些时空数据,我们能够识别游客在假期中的轨迹模式,并确定任何给定城市中最受欢迎的poi,以及游客访问poi的顺序和相应的持续时间。最后,我们根据一组典型的基线方法来评估所提出系统的有效性。
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引用次数: 14
Walk the line: Toward an efficient user model for recommendations in museums 循规蹈矩:建立博物馆推荐的高效用户模型
Pierre-Edouard Osche, Sylvain Castagnos, A. Napoli, Y. Naudet
Contrary to many application domains, recommending items within a museum is not only a question of preferences. Of course, the visitors expect suggestions that are likely to interest or please them. However, additional factors should be taken into account. Recent works use the visiting styles [1] or the shortest distance between items [2] to adapt the list of recommendations. But, as far as we know, no model of the literature aims at inferring in real time an holistic user model which includes variables such as the crowd tolerance, the distance tolerance, the expected user control, the fatigue, the congestion points, etc. As a work-in-progress, we propose a new representation model which includes psychological, physical and social variables so as to increase user satisfaction and enjoyment. We show how we can infer these characteristics from the user observations (geolocalization over time, moving speed, ...) and we discuss how we can use them jointly for a sequence recommendation purpose. This work is still in an early stage of development and remains more theoretical than experimental.
与许多应用程序领域相反,在博物馆中推荐物品不仅仅是一个偏好问题。当然,访问者希望得到可能使他们感兴趣或满意的建议。然而,还应考虑到其他因素。最近的作品使用访问方式[1]或项目之间的最短距离[2]来适应推荐列表。但是,据我们所知,文献中没有一个模型旨在实时推断一个包含人群容限、距离容限、预期用户控制、疲劳、拥塞点等变量的整体用户模型。为了提高用户的满意度和享受度,我们提出了一个包含心理、生理和社会变量的新的表征模型。我们展示了如何从用户观察中推断这些特征(随时间的地理定位、移动速度等),并讨论了如何将它们联合起来用于序列推荐。这项工作仍处于早期发展阶段,理论多于实验。
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引用次数: 14
Cyber security risks for minors: A taxonomy and a software architecture 未成年人网络安全风险:分类和软件架构
Andreas Tsirtsis, N. Tsapatsoulis, M. Stamatelatos, Kostantinos Papadamou, Michael Sirivianos
The explosion of the Internet provides a variety possibilities for communication, finding information and many other activities, turning into an essential tool in our modern everyday life. However, its huge expansion globally has created some serious safety issues, which require a special approach. One of these issues and perhaps the most important one concerns the safety of children on the Internet, as they are more exposed to dangers and threats in comparison with adults. In order to design effective measures against these threats and dangers deep understanding of minors' activities on the Internet, along with their motivation, is a first necessary step. It is shown in this report that minors' Internet activity tends heavily, and in an increasing manner, towards Online Social Networks (OSN). Thus, Internet filtering techniques designed and applied so far for child online protection need to be reconsidered and redesigned in a smarter way such as data analytics, advanced content analysis and data mining techniques are incorporated. OSN fake account identification, sexual content detection and flagging of multiple OSN accounts of the same person are examples that require such sophisticated techniques. This study deals with a literature review concerning the Internet activity and motivation of use by minors and presents in a coherent manner the identified risks and threats that children using the web and online social networks are exposed to. It also presents a systematic process for designing and developing modern and state of the art techniques to prevent minors' exposure to those risks and dangers.
互联网的爆炸为交流、查找信息和许多其他活动提供了各种可能性,成为我们现代日常生活中必不可少的工具。然而,它在全球的巨大扩张带来了一些严重的安全问题,这需要一种特殊的方法。其中一个问题,也许是最重要的一个问题是儿童在互联网上的安全,因为与成年人相比,他们更容易受到危险和威胁。为了设计有效的措施来应对这些威胁和危险,深入了解未成年人在互联网上的活动以及他们的动机是第一步。该报告显示,未成年人的互联网活动严重倾向于在线社交网络(OSN),并且越来越多。因此,需要以更智能的方式重新考虑和重新设计迄今为止为保护儿童在线而设计和应用的互联网过滤技术,例如纳入数据分析、高级内容分析和数据挖掘技术。OSN虚假账户识别、性内容检测、同一人的多个OSN账户标记等都需要用到这种复杂的技术。本研究对未成年人的互联网活动和使用动机进行了文献综述,并以连贯的方式提出了儿童使用网络和在线社交网络所面临的风险和威胁。它还提出了一个系统的过程,设计和发展现代和最先进的技术,以防止未成年人接触这些风险和危险。
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引用次数: 22
ViSTPro: A platform for visualization of spatiotemporal processes on Google Earth 一个在Google Earth上可视化时空过程的平台
Yiannis Sifakis, S. Christodoulakis, Nektarios Moumoutzis
The presentation of spatiotemporal processes is a recurring theme in learning. Such processes are part of the standard curricula in subjects like geography, history, environmental education etc., as well as in professional learning tools like serious games. Learners face several difficulties in studying learning topics without strong spatiotemporal process visualization and explanation support. This paper presents an approach to tackle these problems by providing a spatiotemporal process modeling, visualization and explanation platform on top of Google Earth. The platform is based on a generic conceptual model that adapts to various types of spatiotemporal processes and enables learners to make rich inquiries in a playful manner that resembles their experiences with digital games.
时空过程的呈现是学习中反复出现的主题。这些过程是地理、历史、环境教育等学科标准课程的一部分,也是严肃游戏等专业学习工具的一部分。如果没有强大的时空过程可视化和解释支持,学习者在学习主题时会遇到一些困难。本文提出了一种解决这些问题的方法,即在Google Earth之上提供一个时空过程建模、可视化和解释平台。该平台基于一个通用的概念模型,适应各种类型的时空过程,使学习者能够以一种有趣的方式进行丰富的查询,就像他们在数字游戏中的体验一样。
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引用次数: 3
Identifying and classifying learning entities for designing location-based serious games 识别和分类学习实体,设计基于位置的严肃游戏
D. Anastasiadou, Petros Lameras
This paper investigates the development of a classification of features inherent in the design and development of Location Based Experiences (LBEs) with a special focus on games for teaching and learning. The paper aims to identify and associate learning features, such as feedback, activities, outcomes and assessment with location-driven mechanics, such as location-based activities, entities, conditions and actions that constitute the overarching elements of a proprietary location-based games authoring tool. We anticipate that this will pave the way for developing a model taxonomy that may be utilised to support and optimise future end-user profiles for serious game creation, games design for informal learning paths in science museums, science centres and field trips, learning methodologies development and metadata creation. The classification draws on the findings of a tailored approach applied to design and develop an authoring environment, the MAGELLAN platform, for creating location-based games and mobile location-driven scenarios directly influenced by end-user requirements and evaluation of trainee's feedback. Ultimately, the classification is conceived as part of a broader framework that defines and enables the creation of location-driven games by associating them with learning elements, through visualised design for expert and non-expert users as potential game authors. In an iterative process, the MAGELLAN Authoring Tool and subsequent user training and piloting process is featured as a test-bed, where the proposed taxonomy will be applied and evaluated.
本文研究了基于位置的体验(LBEs)设计和开发中固有特征分类的发展,并特别关注教学游戏。本文旨在识别学习功能(游戏邦注:如反馈、活动、结果和评估)与位置驱动机制(游戏邦注:如基于位置的活动、实体、条件和行动)之间的联系,并将其与构成专有基于位置的游戏创作工具的首要元素联系起来。我们预计这将为开发一种模型分类法铺平道路,该分类法可用于支持和优化未来的最终用户配置文件,用于严肃游戏创建,科学博物馆,科学中心和实地考察的非正式学习路径的游戏设计,学习方法开发和元数据创建。该分类基于一种定制方法的发现,该方法应用于设计和开发一个创作环境,即MAGELLAN平台,用于创建基于位置的游戏和移动位置驱动的场景,这些场景直接受最终用户需求和学员反馈评估的影响。最终,这种分类被认为是一个更广泛的框架的一部分,该框架通过将位置驱动游戏与学习元素联系起来,通过可视化设计将专家和非专家用户作为潜在的游戏作者,来定义和创造位置驱动游戏。在迭代过程中,麦哲伦创作工具和随后的用户培训和试点过程作为试验台,将应用和评估拟议的分类法。
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引用次数: 3
Library Linked Data: The case of Public Library of Veroia 图书馆关联数据:维罗亚公共图书馆的案例
Sotirios Karampatakis, Charalampos Bratsas, Ioannis Antoniou
We describe the Public Library of Veroia dataset. This dataset was created by transforming the bibliographic records of the Public Library of Veroia catalogue into Linked Open Data. We present the data model that is used, consisting of a mix of well-established vocabularies such as BIBO, RDA, DC, FOAF between others. We developed a new tool for the transformation process which implies simple configuration for the end user and rich data extraction. Silk Link Discovery Framework was used to make connections with other datasets like DBpedia. Finally, we developed a new service for author profiling using enriched information gathered from the Linked Open Data Cloud.
我们描述了维罗亚公共图书馆的数据集。该数据集是通过将维罗亚公共图书馆目录的书目记录转换为链接开放数据而创建的。我们介绍了所使用的数据模型,它由BIBO、RDA、DC、FOAF等成熟词汇表组成。我们为转换过程开发了一个新的工具,它意味着为最终用户提供简单的配置和丰富的数据提取。Silk Link发现框架用于与其他数据集(如DBpedia)建立连接。最后,我们开发了一个新的服务,利用从关联开放数据云收集的丰富信息对作者进行分析。
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引用次数: 1
期刊
2016 11th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)
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