004 Datenverarbeitung; Informatik
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A trending topic in Semantic Web research deals with the processing of queries over Linked Open Data (LOD). As has been shown in literature, the loose nature of the "web of data" and data sources within can be accounted for by employing federated query processing strategies. This approach, however, is all the more dependent on both up-to-date statistical summaries (data statistics) of the sources in use and accurate and precise estimation of cardinalities and selectivities. In general, federated data sources are to be seen as black-boxes w.r.t. data statistics, as no interchange of such information can be expected. Because of this, it is possible for individual data statistics to become obsolete, if the corresponding source is subjected to data changes cumulating over time. In this thesis an adaptive system is being proposed, that complements a given RDF-based query federator. Through observation and analysis of the error of the cardinality estimation of incoming queries, it tries to infer the obsolescence of individual data statistics, triggering updates of data statistics found to be obsolete. An evaluation of the system shows, that the approach to this solution is plausible. Yet, in practice no satisfying results could be acquired, that would prove a true practicality. Still, parts of the system proposed may be re-used for related tasks that could be more promising.
Computers assist humans in many every-day situations. Their advancing miniaturisation broadens their fields of use and leads to an even higher significance and spread throughout society. Already, these small and powerful machines are wide-spread in every-day objects and the spread increases still as the mobility-aspect grows in importance. From laptops, smartphones and tables to systems worn on the body (wearable computing) or even inside the body as cyber-implants, these systems help humans actively and context-sensitively in the accomplishment of their every-day business.
A part of the wearable-computing-domain is taken up by the development of Head-mounted displays (HMD). These helmets or goggles feature one or more displays enabling their users to see computer-rendered images or images of their environment enriched with computer-generated information. At the moment, most of this HMD feature LC-Displays, but newer systems start appearing that allow the projection of the image onto the user's retina. Newest break-throughs in the field of study already produced contact lenses with an integrated display. The data shown by a HMD is compiled using a multitude of sensors, like a Head-Tracker or a GPS. Increasing computational performance and miniaturisation lead to a wide spread of HMD in a lot of fields.rnThe multiple scenarios in which a HMD can be used to help improve human-perception and -interaction led the "Institut für Integrierte Naturwissenschaften" of the University of Koblenz-Landau to come up with a HMD on the basis of Apple's iOS-devices featuring Retina Displays. The high pixel density of these displays combined with condensor lenses into a HMD offer a highly immersive environment for stereoscopic imagery, while other systems only display a relatively small image projected a few feet away of the user. Furthermore, the iPhone/ iPod Touch and iPad exhibit a lot of potential given by their variety of offered sensors and computational power. While producing a similarly feature-rich HMD is very costy, using simple iPod Touches 4th Gen as the basis of a HMD results in a very inexpensive solution with a high potential. The increasing popularity and spread of Apple devices would reduce the costs even more, as users of the HMD could simply integrate their device into the system. A software designed with the specific intent to support a large variety of Apple iOS-devices that could easily be extended to support newer devices, would allow for a universal use of such a HMD-solution as the new device could simply replace an old device.rnrnThe focus of this thesis is the conception and development of an application designed for Apple's iOS 5 operating system that will be used in a HMD evolving around the use of Apple iOS-devices featuring Retina Displays. The Rollercoaster2000-project depicting a ride in a virtual rollercoaster will be used as the application's core. A server will syncronize the display of clients conntected to it which are combined to form a HMD. Furthermore the gyroscope of the iOS-devices combined into a HMD will be used to track the wearer's head-movements. Another feature will be the use of the devices cameras as a mean of orientation while wearing the HMD.
As a first step in the realization of a software meeting the set specifications is the introduction of the Objective-C programming languages used to develop iOS-Applications. In conjunction with the compiler and runtime environment, Objective-C makes up the base of the second step, the introduction of the iOS-SDK. Aimed with this iOS-app-development-knowledge, the last part of the thesis consists of the ascertainment of requirements and development of a software complying to the goals of a software written specifically for the used in a HMD.
Web-programming is a huge field of different technologies and concepts. Each technology implements a web-application requirement like content generation or client-server communication. Different technologies within one application are organized by concepts, for example architectural patterns. The thesis describes an approach for creating a taxonomy about these web-programming components using the free encyclopaedia Wikipedia. Our 101companies project uses implementations to identify and classify the different technology sets and concepts behind a web-application framework. These classifications can be used to create taxonomies and ontologies within the project. The thesis also describes, how we priorize useful web-application frameworks with the help of Wikipedia. Finally, the created implementations concerning web-programming are documented.
Large and unknown data sets can be easily and systematically discovered by using faceted search. If implementing applications for smartphones, it needs to be considered that unlike desktop applications you can only use smaller screen sizes and there are limited possibilities for interaction between user and smartphone. These limitations can negatively influence the usability of an application. With FaThumb and MobileFacets, two mobile applications exist, which implement and use faceted search, although only MobileFacets is designed for current smartphones with touchscreen. However, FaThumb provides a novel facet navigation, which is newly realized in MFacets for present smartphones within this work.
Moreover, this work deals with the performance of a summative evaluation between both applications, MFacets and MobileFacets, with regards to usability and presents the evaluated results.
Standards are widely-used in the computer science and IT industry. Different organizations like the International Organization for Standardization (SO) are involved in the development of computer related standards. An important domain of standardization is the specification of data formats enabling the exchange of information between different applications. Such formats can be expressed in a variety of schema languages thereby defining sets of conformant documents. Often the use of multiple schema languages is required due to their varying expressive power and different kind of validation requirements.rnThis also holds for the Specification Common Cartridge which is maintained by the IMS Global Learning Consortium. The specification defines valid zip packages that can be used to aggregate different learning objects. These learning objects are represented by a set of files which are a part of the package and can be imported into a learning management system. The specification makes use of other specifications to constrain the contents of valid documents. Such documents are expressed in the eXtensible Markup Language and may contain references to other files also part of the package. The specification itself is a so-called domain profile. A domain profile allows the modification of one or more specifications to meet the needs of a particular community. Test rules can be used to determine a set of tasks in order to validate a concrete package. The execution is done by a testsystem which, as we will show, can be created automatically. Hence this method may apply to other package based data formats that are defined as a part of a specification.
This work will examine the applicability of this generic test method to the data formats that are introduced by the so called Virtual Company Dossier. These formats are used in processes related to public e-procurement. They allow the packaging of evidences that are needed to prove the fulfillment of criteria related to a public tender. The work first examines the requirements that are common to both specifications. This will introduce a new view on the requirements by introducing a higher level of abstraction. The identified requirements will then be used to create different domain profiles each capturing the requirements of a package based data format. The process is normally guided by supporting tools that ease the capturing of a domain profile and the creation of testsystems. These tools will be adapted to support the new requirements. Furtheron the generic testsystem will be modified. This system is used as a basis when a concrete testsystem is created.
Finally the author comes to a positive conclusion. Common requirements have been identified and captured. The involved systems have been adapted allowing the capturing of further types of requirements that have not been supported before. Furthermore the background of the specifications quite differ. This indicates that the use of domain profiles and generic test technologies may be suitable in a wide variety of other contexts.
In automated theorem proving, there are some problems that need information on the inequality of certain constants. In most cases this information is provided by adding facts which explicitly state that two constants are unequal. Depending on the number of constants, a huge amount of this facts can clutter the knowledge base and distract the author and readers of the problem from its actual proposition. For most cases it is save to assume that a larger knowledge base reduces the performance of a theorem prover, which is another drawback of explicit inequality facts. Using the unique name assumption in those reasoning tasks renders the introduction of inequality facts obsolete as the unique name assumptions states that two constants are identical iff their interpretation is identical. Implicit handling of non-identical constants makes the problems easier to comprehend and reduces the execution time of reasoning. In this thesis we will show how to integrate the unique name assumption into the E-hyper tableau calculus and that the modified calculus is sound and complete. The calculus will be implemented into the E-KRHyper theorem prover and we will show, by empiric evaluation, that the changed implementation, which is able to use the unique name assumption, is superior to the traditional version of E-KRHyper.
In dieser Ausarbeitung beschreibe ich die Ergebnisse meiner Untersuchungen zur Erweiterung des LogAnswer-Systemsmit nutzerspezifischen Profilinformationen. LogAnswer ist ein natürlichsprachliches open-domain Frage-Antwort-System. Das heißt: es beantwortet Fragen zu beliebigen Themen und liefert dabei konkrete (möglichst knappe und korrekte) Antworten zurück. Das System wird im Rahmen eines Gemeinschaftsprojekts der Arbeitsgruppe für künstliche Intelligenz von Professor Ulrich Furbach an der Universität Koblenz-Landau und der Arbeitsgruppe Intelligent Information and Communication Systems (IICS) von Professor Hermann Helbig an der Fernuniversität Hagen entwickelt. Die Motivation meiner Arbeit war die Idee, dass der Prozess der Antwortfindung optimiert werden kann, wenn das Themengebiet, auf das die Frage abzielt, im Vorhinein bestimmt werden kann. Dazu versuchte ich im Rahmen meiner Arbeit die Interessensgebiete von Nutzern basierend auf Profilinformationen zu bestimmen. Das Semantic Desktop System NEPOMUK wurde verwendet um diese Profilinformationen zu erhalten. NEPOMUK wird verwendet um alle Daten, Dokumente und Informationen, die ein Nutzer auf seinem Rechner hat zu strukturieren. Dazu nutzt das System ein sogenanntes Personal Information Model (PIMO) in Form einer Ontologie. Diese Ontologie enthält unter anderem eine Klasse "Topic", welche die wichtigste Grundlage für das Erstellen der in meiner Arbeit verwendeten Nutzerprofile bildete. Konkret wurde die RDF-Anfragesprache SPARQL verwendet, um eine Liste aller für den Nutzer relevanten Themen aus der Ontologie zu filtern. Die zentrale Idee meiner Arbeit war es nun diese Profilinformationen zur Optimierung des Ranking von Antwortkandidaten einzusetzen. In LogAnswer werden zu jeder gestellten Frage bis zu 200 potentiell relevante Textstellen aus der deutschen Wikipedia extrahiert. Diese Textstellen werden auf Basis von Eigenschaften (wie z.B. lexikalische Übereinstimmungen zwischen Frage und Textstelle) geordnet, da innerhalb des zur Verfügung stehenden Zeitlimits nicht alle Kandidaten bearbeitet werden können.
Mein Ansatz verfolgte das Ziel, diesen Algorithmus durch Nutzerprofile so zu erweitern, dass Antwortkandidaten, welche für den Benutzer relevante Informationen enthalten, höher in der Rangfolge eingeordnet werden. Zur Umsetzung dieser Idee musste eine Methode gefunden werden, um zu bestimmen ob ein Antwortkandidat mit dem Profil übereinstimmt. Da sich die in einer Textstelle enthaltenen Informationen in den meisten Fällen auf das übergeordnete Thema des Artikels beziehen, ohne den Namen des Artikels explizit zu erwähnen, wurde in meiner Implementierung der Artikelname betrachtet, um zu ermitteln, zu welchem Themengebiet die Textstelle Informationen liefert. Als zusätzliches Hilfsmittel wurde außerdem die DBpedia-Ontologie eingesetzt, welche die Informationen der Wikipedia strukturiert im RDF Format enthält. Mit Hilfe dieser Ontologie war es möglich, jeden Artikel in Kategorien einzuordnen, die dann mit den im Profil enthaltenen Stichworten verglichen wurden. Zur Untersuchung der Auswirkungen des Ansatzes auf das Ranking-Verfahren wurden mehrere Testläufe mit je 200 Testfragen durchgeführt. Die erste Testmenge bestand aus zufällig ausgewählten Fragen, die mit meinem eigenen Nutzerprofil getestet wurden. Dieser Testlauf lieferte kaum nutzbare Ergebnisse, da nur bei 29 der getesteten Fragen überhaupt ein Antwortkandidat mit dem Profil in Verbindung gebracht werden konnte. Außerdem konnte eine potentielle Verbesserung der Ergebnisse nur bei einer dieser 29 Fragen festgestellt werden, was zu der Schlussfolgerung führte, dass der Einsatz von Profildaten nicht für Anwendungsfälle geeignet ist, in denen die Fragen keine Korrelation mit dem genutzten Profil aufweisen.
Da die Grundannahme meiner Arbeit war, dass Nutzer in erster Linie Fragen zu den Interessensgebieten stellen, welche sich aus ihrem Profil ableiten lassen, sollten die weiteren Testläufe genau diesen Fall beleuchten. Dazu wurden 200 Testfragen aus dem Bereich Sport ausgewählt und mit einem Profil getestet, welches Stichworte zu unterschiedlichen Sportarten enthielt. Die Tests mit den Sportfragen waren wesentlich aussagekräftiger. Auch hier deuteten die Ergebnisse darauf hin, dass der Ansatz kein großes Potential zur Verbesserung des Rankings hat. Eine genauere Betrachtung einiger ausgewählter Beispiele zeigte allerdings, dass die Integration von Profildaten für bestimmte Anwendungsfälle, wie z.B. offene Fragen für die es mehr als eine korrekte Antwort gibt, durchaus zu einer Verbesserung der Ergebnisse führen kann. Außerdem wurde festgestellt, dass viele der schlechten Ergebnisse auf Inkosistenzen in der DBpedia-Ontologie und grundsätzliche Probleme im Umgang mit Wissensbasen in natürlicher Sprache beruhen.
Die Schlussfolgerung meiner Arbeit ist, dass der in dieser Arbeit vorgestellte Ansatz zur Integration von Profilinformationen für den aktuellen Anwendungsfall von LogAnswer nicht geeignet ist, da vor allem Faktenwissen aus sehr unterschiedlichen Domänen abgefragt wird und offene Fragen nur einen geringen Anteil ausmachen.
Robotics research today is primarily about enabling autonomous, mobile robots to seamlessly interact with arbitrary, previously unknown environments. One of the most basic problems to be solved in this context is the question of where the robot is, and what the world around it, and in previously visited places looks like " the so-called simultaneous localization and mapping (SLAM) problem. We present a GraphSLAM system, which is a graph-based approach to this problem. This system consists of a frontend and a backend: The frontend- task is to incrementally construct a graph from the sensor data that models the spatial relationship between measurements. These measurements may be contradicting and therefore the graph is inconsistent in general. The backend is responsible for optimizing this graph, i. e. finding a configuration of the nodes that is least contradicting. The nodes represent poses, which do not form a regular vector space due to the contained rotations. We respect this fact by treating them as what they really are mathematically: manifolds. This leads to a very efficient and elegant optimization algorithm.