Semantic Similarity of Spatial Scenes

The formalization of similarity in spatial information systems can unleash their functionality and contribute technology not only useful, but also desirable by broad groups of users. As a paradigm for information retrieval, similarity supersedes tedious querying techniques and unveils novel ways for user-system interaction by naturally supporting modalities such as speech and sketching. As a tool within the scope of a broader objective, it can facilitate such diverse tasks as data integration, landmark determination, and prediction making. This potential motivated the development of several similarity models within the geospatial and computer science communities. Despite the merit of these studies, their cognitive plausibility can be limited due to neglect of well-established psychological principles about properties and behaviors of similarity. Moreover, such approaches are typically guided by experience, intuition, and observation, thereby often relying on more narrow perspectives or restrictive assumptions that produce inflexible and incompatible measures. This thesis consolidates such fragmentary efforts and integrates them along with novel formalisms into a scalable, comprehensive, and cognitively-sensitive framework for similarity queries in spatial information systems. Three conceptually different similarity queries at the levels of attributes, objects, and scenes are distinguished. An analysis of the relationship between similarity and change provides a unifying basis for the approach and a theoretical foundation for measures satisfying important similarity properties such as asymmetry and context dependence. The classification of attributes into categories with common structural and cognitive characteristics drives the implementation of a small core of generic functions, able to perform any type of attribute value assessment. Appropriate techniques combine such atomic assessments to compute similarities at the object level and to handle more complex inquiries with multiple constraints. These techniques, along with a solid graph-theoretical methodology adapted to the particularities of the geospatial domain, provide the foundation for reasoning about scene similarity queries. Provisions are made so that all methods comply with major psychological findings about people’s perceptions of similarity. An experimental evaluation supplies the main result of this thesis, which separates psychological findings with a major impact on the results from those that can be safely incorporated into the framework through computationally simpler alternatives

Interaktive Suchprozesse in komplexen Arbeitssituationen - Ein Retrieval Framework

In recent years a steady increase of information produced in organizations can be noticed. In order to stay competitive, companies have a growing interest in reusing existing knowledge from past projects. Furthermore, a complete picture of the available information is necessary to be able to make informed decisions. The variety and complexity of information in modern organizations often exceeds the capabilities of the currently deployed enterprise search solutions. The reasons for that are manifold and range from non-linked information from multiple software systems to missing functionality to support users during search tasks. Existing search engines often do not support the search paradigms necessary in these environments. On many occasions, users are not aware of the results they will find during the formulation of the search queries. Additionally, the aspect of knowledge building and the identification of new insights into the available data is a priority for the users. Therefore, search paradigms are useful to provide users with tools that support exploratory navigation in a data set and help them to recognize relationships between search results. The goal of this publication is the introduction of a framework that supports exploratory searches in an organizational setting. The described LFRP-framework is built on top of four pillars. 1. The multi-layer functionality allows users to formulate complex search queries referring to more than one result type. Therewith, it enables search queries that - starting from a set of relevant projects - allow selections of documents that are linked to these projects. 2. The search paradigm of faceted searching supports users in formulating search queries incrementally by offering dynamic and valid filter criteria that avoid empty result sets. 3. By combining the concept of faceted search with the capability to influence the search result order based on filter criteria, users can define in a fine-grained way which criteria values shall be weighted stronger or weaker in the search results. The interaction with the ranking is conducted transparently by the so-called user preference functions. 4. The last pillar consists of the visualization type of parallel coordinates covering two tasks in the search user interface of the LFRP-Framework. On the one hand, users formulate their search queries solely graphically in the parallel coordinates and on the other hand they obtain a visual representation of the search results and are able to discover relationships between search results and their facets. The framework is introduced formally from a query model point of view as well as a prototypical implementation. It enables users to access large linked data sets by navigation and constitutes a contribution to a comprehensive information strategy for organizations.Seit einigen Jahren ist ein stetiges Ansteigen der Menge an Informationen, die in Unternehmen erzeugt werden, festzustellen. Um als Unternehmen wettbewerbsfähig zu bleiben, ist es notwendig, vorhandenes Wissen wiederzuverwenden, um aus vergangenen Projektergebnissen profitieren zu können. Weiterhin ist ein vollständiges Informationsbild unabdingbar, um informierte Entscheidungen treffen zu können. Die Informationsvielfalt in modernen Unternehmen übersteigt häufig die Fähigkeiten aktuell anzutreffender unternehmensweiter Suchlösungen. Die Gründe hierfür sind vielfältig und reichen von nicht verknüpften Informationen aus verschiedenen Softwaresystemen bis hin zu fehlenden Funktionen, um den Nutzer bei der Suche zu unterstützen. Vorhandene Suchfunktionen im Unternehmen unterstützen häufig nicht die Suchparadigmen, die in diesem Umfeld notwendig sind. Vielfach ist den Suchenden bei der Formulierung ihrer Suchanfrage nicht bekannt, welche Ergebnisse sie finden werden. Stattdessen steht der Aspekt des Wissensaufbaus und der Gewinnung neuer Einsichten in den vorhandenen Daten im Vordergrund. Hierzu werden Suchparadigmen benötigt, die dem Nutzer Werkzeuge zur Verfügung stellen, die ein exploratives Navigieren im Datenbestand erlauben und ihnen bei der Erkennung von Zusammenhängen in den Suchergebnissen unterstützen. Das Ziel dieser Arbeit ist die Vorstellung eines Rahmenwerks, dass explorative Suchvorhaben im Unternehmensumfeld unterstützt. Das beschriebene LFRP-Framework baut auf vier Säulen auf. 1. Die Multi-Layer Funktionalität erlaubt es Nutzern, komplexe Suchanfragen zu formulieren, die sich auf mehr als einen Ergebnistyp beziehen. Dies ermöglicht beispielsweise Suchabfragen, die - ausgehend von einer Menge von relevanten vergangenen Projekten - Selektionen auf den dazugehörigen Dokumenten erlauben. 2. Das Suchparadigma der facettierten Suche unterstützt Nutzer bei der inkrementellen Formulierung von Suchanfragen mithilfe von dynamisch angebotenen Filterkriterien und vermeidet leere Ergebnismengen durch die Bereitstellung gültiger Filterkriterien. 3. Die Erweiterung der facettierten Suche um die Möglichkeit, die Suchergebnisreihenfolge basierend auf Filterkriterien zu beeinflussen, erlaubt es Nutzern feingranular vorzugeben, welche Kriterienausprägungen im Suchergebnis stärker gewichtet werden sollen. Für den Nutzer geschieht die Beeinflussung des Rankings transparent über sogenannte Nutzerpräferenzfunktionen. 4. Die letzte Säule umfasst die Visualisierung der parallelen Koordinaten, die in der Suchoberfläche des LFRP-Frameworks zwei Aufgaben übernimmt. Zum einen formuliert der Nutzer damit die Suchanfrage ausschließlich grafisch über die Visualisierung und zum anderen erhält er eine grafische Repräsentation der Suchergebnisse und kann so leichter Beziehungen zwischen Suchergebnissen und deren Facetten erkennen. Das Framework, welches in dieser Arbeit formal aus Sicht des Anfragemodells sowie als prototypische Umsetzung betrachtet wird, ermöglicht Nutzern den navigierenden Zugriff auf große vernetze Datenbestände und stellt einen Baustein einer umfassenden Informationsstrategie für Unternehmen dar

Three dimensional finite element modeling, when drilling of Ti-6Al-4V

Finite element modeling (FEM) is widely used to optimize machining processes, to predict and analyze the cutting force, cutting temperature and other related responses. Most of the FEM studies were conducted under the two dimensional orthogonal cutting. Drilling process, which involves oblique cutting is not suitable for orthogonal cutting modelling. Therefore, an attempt to simulate a three dimensional simulation of the drilling process is required. A commercially available software called DEFORM is used to accomplish the task. The value of thrust force from the simulation is compared with the experimental results and they are both in a good agreement. Comparison of the drill temperature at TC1 and TC2 are within an error margin of 12%

Using Ontology-Based Approaches to Representing Speech Transcripts for Automated Speech Scoring

Text representation is a process of transforming text into some formats that computer systems can use for subsequent information-related tasks such as text classification. Representing text faces two main challenges: meaningfulness of representation and unknown terms. Research has shown evidence that these challenges can be resolved by using the rich semantics in ontologies. This study aims to address these challenges by using ontology-based representation and unknown term reasoning approaches in the context of content scoring of speech, which is a less explored area compared to some common ones such as categorizing text corpus (e.g. 20 newsgroups and Reuters). From the perspective of language assessment, the increasing amount of language learners taking second language tests makes automatic scoring an attractive alternative to human scoring for delivering rapid and objective scores of written and spoken test responses. This study focuses on the speaking section of second language tests and investigates ontology-based approaches to speech scoring. Most previous automated speech scoring systems for spontaneous responses of test takers assess speech by primarily using acoustic features such as fluency and pronunciation, while text features are less involved and exploited. As content is an integral part of speech, the study is motivated by the lack of rich text features in speech scoring and is designed to examine the effects of different text features on scoring performance. A central question to the study is how speech transcript content can be represented in an appropriate means for speech scoring. Previously used approaches from essay and speech scoring systems include bag-of-words and latent semantic analysis representations, which are adopted as baselines in this study; the experimental approaches are ontology-based, which can help improving meaningfulness of representation units and estimating importance of unknown terms. Two general domain ontologies, WordNet and Wikipedia, are used respectively for ontology-based representations. In addition to comparison between representation approaches, the author analyzes which parameter option leads to the best performance within a particular representation. The experimental results show that on average, ontology-based representations slightly enhances speech scoring performance on all measurements when combined with the bag-of-words representation; reasoning of unknown terms can increase performance on one measurement (cos.w4) but decrease others. Due to the small data size, the significance test (t-test) shows that the enhancement of ontology-based representations is inconclusive. The contributions of the study include: 1) it examines the effects of different representation approaches on speech scoring tasks; 2) it enhances the understanding of the mechanisms of representation approaches and their parameter options via in-depth analysis; 3) the representation methodology and framework can be applied to other tasks such as automatic essay scoring

Intelligent Information Access to Linked Data - Weaving the Cultural Heritage Web

The subject of the dissertation is an information alignment experiment of two cultural heritage information systems (ALAP): The Perseus Digital Library and Arachne. In modern societies, information integration is gaining importance for many tasks such as business decision making or even catastrophe management. It is beyond doubt that the information available in digital form can offer users new ways of interaction. Also, in the humanities and cultural heritage communities, more and more information is being published online. But in many situations the way that information has been made publicly available is disruptive to the research process due to its heterogeneity and distribution. Therefore integrated information will be a key factor to pursue successful research, and the need for information alignment is widely recognized. ALAP is an attempt to integrate information from Perseus and Arachne, not only on a schema level, but to also perform entity resolution. To that end, technical peculiarities and philosophical implications of the concepts of identity and co-reference are discussed. Multiple approaches to information integration and entity resolution are discussed and evaluated. The methodology that is used to implement ALAP is mainly rooted in the fields of information retrieval and knowledge discovery. First, an exploratory analysis was performed on both information systems to get a first impression of the data. After that, (semi-)structured information from both systems was extracted and normalized. Then, a clustering algorithm was used to reduce the number of needed entity comparisons. Finally, a thorough matching was performed on the different clusters. ALAP helped with identifying challenges and highlighted the opportunities that arise during the attempt to align cultural heritage information systems

Corpus linguistics: A guide to the methodology

Corpora are widely used in linguistics, but not always wisely. This book attempts to frame corpus linguistics systematically as a variant of the observational method. The first part introduces the reader to the general methodological discussions surrounding corpus data as well as the practice of doing corpus linguistics, including issues such as the scientific research cycle, research design, extraction of corpus data and statistical evaluation. The second part consists of a number of case studies from the main areas of corpus linguistics (lexical associations, morphology, grammar, text and metaphor), surveying the range of issues studied in corpus linguistics while at the same time showing how they fit into the methodology outlined in the first part

Corpus linguistics: A guide to the methodology

Corpora are widely used in linguistics, but not always wisely. This book attempts to frame corpus linguistics systematically as a variant of the observational method. The first part introduces the reader to the general methodological discussions surrounding corpus data as well as the practice of doing corpus linguistics, including issues such as the scientific research cycle, research design, extraction of corpus data and statistical evaluation. The second part consists of a number of case studies from the main areas of corpus linguistics (lexical associations, morphology, grammar, text and metaphor), surveying the range of issues studied in corpus linguistics while at the same time showing how they fit into the methodology outlined in the first part

Corpus linguistics: A guide to the methodology

Corpora are widely used in linguistics, but not always wisely. This book attempts to frame corpus linguistics systematically as a variant of the observational method. The first part introduces the reader to the general methodological discussions surrounding corpus data as well as the practice of doing corpus linguistics, including issues such as the scientific research cycle, research design, extraction of corpus data and statistical evaluation. The second part consists of a number of case studies from the main areas of corpus linguistics (lexical associations, morphology, grammar, text and metaphor), surveying the range of issues studied in corpus linguistics while at the same time showing how they fit into the methodology outlined in the first part