004 Datenverarbeitung; Informatik
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In recent years, the ever-growing amount of documents on the Web as well as in closed systems for private or business contexts led to a considerable increase of valuable textual information about topics, events, and entities. It is a truism that the majority of information (i.e., business-relevant data) is only available in unstructured textual form. The text mining research field comprises various practice areas that have the common goal of harvesting high-quality information from textual data. These information help addressing users' information needs.
In this thesis, we utilize the knowledge represented in user-generated content (UGC) originating from various social media services to improve text mining results. These social media platforms provide a plethora of information with varying focuses. In many cases, an essential feature of such platforms is to share relevant content with a peer group. Thus, the data exchanged in these communities tend to be focused on the interests of the user base. The popularity of social media services is growing continuously and the inherent knowledge is available to be utilized. We show that this knowledge can be used for three different tasks.
Initially, we demonstrate that when searching persons with ambiguous names, the information from Wikipedia can be bootstrapped to group web search results according to the individuals occurring in the documents. We introduce two models and different means to handle persons missing in the UGC source. We show that the proposed approaches outperform traditional algorithms for search result clustering. Secondly, we discuss how the categorization of texts according to continuously changing community-generated folksonomies helps users to identify new information related to their interests. We specifically target temporal changes in the UGC and show how they influence the quality of different tag recommendation approaches. Finally, we introduce an algorithm to attempt the entity linking problem, a necessity for harvesting entity knowledge from large text collections. The goal is the linkage of mentions within the documents with their real-world entities. A major focus lies on the efficient derivation of coherent links.
For each of the contributions, we provide a wide range of experiments on various text corpora as well as different sources of UGC.
The evaluation shows the added value that the usage of these sources provides and confirms the appropriateness of leveraging user-generated content to serve different information needs.
Students of computer science studies enter university education with very different competencies, experience and knowledge. 145 datasets collected of freshmen computer science students by learning management systems in relation to exam outcomes and learning dispositions data (e. g. student dispositions, previous experiences and attitudes measured through self-reported surveys) has been exploited to identify indicators as predictors of academic success and hence make effective interventions to deal with an extremely heterogeneous group of students.
Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)]
Blockchain
(2018)
The term blockchain has recently become a buzzword, but only few know what exactly lies behind this approach. According to a survey, issued in the first quarter of 2017, the term is only known by 35 percent of German medium-sized enterprise representatives. However, the blockchain technology is very interesting for the mass media because of its rapid development and global capturing of different markets.
For example, many see blockchain technology either as an all-purpose weapon— which only a few have access to—or as a hacker technology for secret deals in the darknet. The innovation of blockchain technology is found in its successful combination of already existing approaches: such as decentralized networks, cryptography, and consensus models. This innovative concept makes it possible to exchange values in a decentralized system. At the same time, there is no requirement for trust between its nodes (e.g. users).
With this study the Hasso Plattner Institute would like to help readers form their own opinion about blockchain technology, and to distinguish between truly innovative properties and hype.
The authors of the present study analyze the positive and negative properties of the blockchain architecture and suggest possible solutions, which can contribute to the efficient use of the technology. We recommend that every company define a clear target for the intended application, which is achievable with a reasonable cost-benefit ration, before deciding on this technology. Both the possibilities and the limitations of blockchain technology need to be considered. The relevant steps that must be taken in this respect are summarized /summed up for the reader in this study.
Furthermore, this study elaborates on urgent problems such as the scalability of the blockchain, appropriate consensus algorithm and security, including various types of possible attacks and their countermeasures. New blockchains, for example, run the risk of reducing security, as changes to existing technology can lead to lacks in the security and failures.
After discussing the innovative properties and problems of the blockchain technology, its implementation is discussed. There are a lot of implementation opportunities for companies available who are interested in the blockchain realization. The numerous applications have either their own blockchain as a basis or use existing and widespread blockchain systems. Various consortia and projects offer "blockchain-as-a-serviceänd help other companies to develop, test and deploy their own applications.
This study gives a detailed overview of diverse relevant applications and projects in the field of blockchain technology. As this technology is still a relatively young and fast developing approach, it still lacks uniform standards to allow the cooperation of different systems and to which all developers can adhere. Currently, developers are orienting themselves to Bitcoin, Ethereum and Hyperledger systems, which serve as the basis for many other blockchain applications.
The goal is to give readers a clear and comprehensive overview of blockchain technology and its capabilities.
Blockchain
(2018)
Der Begriff Blockchain ist in letzter Zeit zu einem Schlagwort geworden, aber nur wenige wissen, was sich genau dahinter verbirgt. Laut einer Umfrage, die im ersten Quartal 2017 veröffentlicht wurde, ist der Begriff nur bei 35 Prozent der deutschen Mittelständler bekannt. Dabei ist die Blockchain-Technologie durch ihre rasante Entwicklung und die globale Eroberung unterschiedlicher Märkte für Massenmedien sehr interessant.
So sehen viele die Blockchain-Technologie entweder als eine Allzweckwaffe, zu der aber nur wenige einen Zugang haben, oder als eine Hacker-Technologie für geheime Geschäfte im Darknet. Dabei liegt die Innovation der Blockchain-Technologie in ihrer erfolgreichen Zusammensetzung bereits vorhandener Ansätze: dezentrale Netzwerke, Kryptographie, Konsensfindungsmodelle. Durch das innovative Konzept wird ein Werte-Austausch in einem dezentralen System möglich. Dabei wird kein Vertrauen zwischen dessen Knoten (z.B. Nutzer) vorausgesetzt.
Mit dieser Studie möchte das Hasso-Plattner-Institut den Lesern helfen, ihren eigenen Standpunkt zur Blockchain-Technologie zu finden und dabei dazwischen unterscheiden zu können, welche Eigenschaften wirklich innovativ und welche nichts weiter als ein Hype sind.
Die Autoren der vorliegenden Arbeit analysieren positive und negative Eigenschaften, welche die Blockchain-Architektur prägen, und stellen mögliche Anpassungs- und Lösungsvorschläge vor, die zu einem effizienten Einsatz der Technologie beitragen können. Jedem Unternehmen, bevor es sich für diese Technologie entscheidet, wird dabei empfohlen, für den geplanten Anwendungszweck zunächst ein klares Ziel zu definieren, das mit einem angemessenen Kosten-Nutzen-Verhältnis angestrebt werden kann. Dabei sind sowohl die Möglichkeiten als auch die Grenzen der Blockchain-Technologie zu beachten. Die relevanten Schritte, die es in diesem Zusammenhang zu beachten gilt, fasst die Studie für die Leser übersichtlich zusammen.
Es wird ebenso auf akute Fragestellungen wie Skalierbarkeit der Blockchain, geeigneter Konsensalgorithmus und Sicherheit eingegangen, darunter verschiedene Arten möglicher Angriffe und die entsprechenden Gegenmaßnahmen zu deren Abwehr. Neue Blockchains etwa laufen Gefahr, geringere Sicherheit zu bieten, da Änderungen an der bereits bestehenden Technologie zu Schutzlücken und Mängeln führen können.
Nach Diskussion der innovativen Eigenschaften und Probleme der Blockchain-Technologie wird auf ihre Umsetzung eingegangen. Interessierten Unternehmen stehen viele Umsetzungsmöglichkeiten zur Verfügung. Die zahlreichen Anwendungen haben entweder eine eigene Blockchain als Grundlage oder nutzen bereits bestehende und weitverbreitete Blockchain-Systeme. Zahlreiche Konsortien und Projekte bieten „Blockchain-as-a-Service“ an und unterstützen andere Unternehmen beim Entwickeln, Testen und Bereitstellen von Anwendungen.
Die Studie gibt einen detaillierten Überblick über zahlreiche relevante Einsatzbereiche und Projekte im Bereich der Blockchain-Technologie. Dadurch, dass sie noch relativ jung ist und sich schnell entwickelt, fehlen ihr noch einheitliche Standards, die Zusammenarbeit der verschiedenen Systeme erlauben und an die sich alle Entwickler halten können. Aktuell orientieren sich Entwickler an Bitcoin-, Ethereum- und Hyperledger-Systeme, diese dienen als Grundlage für viele weitere Blockchain-Anwendungen.
Ziel ist, den Lesern einen klaren und umfassenden Überblick über die Blockchain-Technologie und deren Möglichkeiten zu vermitteln.
Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the 'argumentative microtext corpus' [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp. 801-815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance.
Das Training sozioemotionaler Kompetenzen ist gerade für Menschen mit Autismus nützlich. Ein solches Training kann mithilfe einer spielbasierten Anwendung effektiv gestaltet werden. Zwei Minispiele, Mimikry und Emo-Mahjong, wurden realisiert und hinsichtlich User Experience evaluiert. Die jeweiligen Konzepte und die Evaluationsergebnisse sollen hier vorgestellt werden.
Remote sensing technology, such as airborne, mobile, or terrestrial laser scanning, and photogrammetric techniques, are fundamental approaches for efficient, automatic creation of digital representations of spatial environments. For example, they allow us to generate 3D point clouds of landscapes, cities, infrastructure networks, and sites. As essential and universal category of geodata, 3D point clouds are used and processed by a growing number of applications, services, and systems such as in the domains of urban planning, landscape architecture, environmental monitoring, disaster management, virtual geographic environments as well as for spatial analysis and simulation.
While the acquisition processes for 3D point clouds become more and more reliable and widely-used, applications and systems are faced with more and more 3D point cloud data. In addition, 3D point clouds, by their very nature, are raw data, i.e., they do not contain any structural or semantics information. Many processing strategies common to GIS such as deriving polygon-based 3D models generally do not scale for billions of points. GIS typically reduce data density and precision of 3D point clouds to cope with the sheer amount of data, but that results in a significant loss of valuable information at the same time.
This thesis proposes concepts and techniques designed to efficiently store and process massive 3D point clouds. To this end, object-class segmentation approaches are presented to attribute semantics to 3D point clouds, used, for example, to identify building, vegetation, and ground structures and, thus, to enable processing, analyzing, and visualizing 3D point clouds in a more effective and efficient way. Similarly, change detection and updating strategies for 3D point clouds are introduced that allow for reducing storage requirements and incrementally updating 3D point cloud databases. In addition, this thesis presents out-of-core, real-time rendering techniques used to interactively explore 3D point clouds and related analysis results. All techniques have been implemented based on specialized spatial data structures, out-of-core algorithms, and GPU-based processing schemas to cope with massive 3D point clouds having billions of points.
All proposed techniques have been evaluated and demonstrated their applicability to the field of geospatial applications and systems, in particular for tasks such as classification, processing, and visualization. Case studies for 3D point clouds of entire cities with up to 80 billion points show that the presented approaches open up new ways to manage and apply large-scale, dense, and time-variant 3D point clouds as required by a rapidly growing number of applications and systems.
Business processes constantly generate, manipulate, and consume data that are managed by organizational databases. Despite being central to process modeling and execution, the link between processes and data is often handled by developers when the process is implemented, thus leaving the connection unexplored during the conceptual design. In this paper, we introduce, formalize, and evaluate a novel conceptual view that bridges the gap between process and data models, and show some kinds of interesting insights that can be derived from this novel proposal.