University of Hildesheim
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Der benutzerorientierte Datenbankentwurf im Anwendungsfeld Car Multimedia
No full textIm vorliegenden Beitrag werden benutzerpartizipative Verfahren im Rahmen des Datenbankentwurfs für ein Informationssystem vorgestellt. Dabei wird aufgezeigt, wie Extreme Programming als zentraler Ansatz der agilen Software Entwicklung die synergetische Verflechtung des traditionell technologiebetriebenen Software Engineering (SE) mit benutzerzentrierten Verfahren des User-Centered Design (UCD) ermöglichen kann und welche Mehrwerte sich daraus ergeben. Da insbesondere die Kommunikation zwischen Systementwicklern und Experten im vorgestellten Projekt einen hohen Stellenwert einnahm, werden entsprechende Vorgehensweisen, aufgetretene Probleme sowie Lösungsansätze in der Anforderungsanalyse diskutiert. Der Einsatz von Interview- und Beobachtungstechniken wird dabei am Beispiel der Erfassung des Car Multimedia Anwendungsfeldes zum Zweck der Daten- und Systemmodellierung verdeutlicht
User Profiling and Privacy Protection for a Web Service oriented Semantic Web
No full textIn a Web Service-based Semantic Web long term usage of single Services will become unlikely. Therefore, user modeling on Web Service’s site might be imprecise due to a lack of a sufficient amount of user interaction. In our Personal Reader Framework, the user profile is stored centrally and can be used by different Web Services. By combining information about the user from different Web Services, the coverage and precision of such centralized user profile increases. To preserve user’s privacy, access to the user profile is restricted by policies
Predicting User Experiences through Cross-Context Reasoning
No full textThe existing personalization systems typically base their services on general user models that ignore the issue of context-awareness. This position paper focuses on developing mechanisms for cross-context reasoning of the user models, which can be applied for the context-aware personalization. The reasoning augments the sparse user models by inferring the missing information from other contextual conditions. Thus, it upgrades the existing personalization systems and facilitates provision of accurate context-aware services
Dedicated Backing-Off Distributions for Language Model Based Passage
No full textPassage retrieval is an essential part of question answering systems. In this paper we use statistical language models to perform this task. Previous work has shown that language modeling techniques provide better results for both, document and passage retrieval. The motivation behind this paper is to define new smoothing methods for passage retrieval in question answering systems. The long term objective is to improve the quality of question answering systems to isolate the correct answer by choosing and evaluating the appropriate section of a document. In this work we use a three step approach. The first two steps are standard document and passage retrieval using the Lemur toolkit. As a novel contribution we propose as the third step a re-ranking using dedicated backing-off distributions. In particular backing-off from the passage-based language model to a language model trained on the document from which the passage is taken shows a significant improvement. For a TREC question answering task we can increase the mean average precision from 0.127 to 0.176
Entwicklung empirischer Messmethoden zur Validierung der Handlungskompetenz der Piloten
No full textThis article deals with the development of an empirical test for monitoring basic competences of commercial pilots. The evaluation sheet is filled out by Lufthansa flight training instructors on a voluntary basis during the period of data collection. The skill ratings are entered during type ratings which are mandatory for all pilots of commercial airplanes due to the regulations of the Luftfahrtbundesamt. An essential part of this study is the development of indicators for operational competence of pilots in emergency situations and their transformation into criteria for measurement. The target of this study is the statistical analysis of the evaluated data to develop statements regarding the construct validity of the created evaluation form. In this context it is to be tested whether or not the results for each competence are independent from the specific method.Im Rahmen des vorligenden Artikels wird ein Bewertungsbogen zur Ermittlung der Handlungskompetenz von Piloten in Zusammenarbeit mit Flugtrainingsexperten der Deutschen Lufthansa AG entwickelt. Die Bewertungen erfolgen in Simulatortests, die vom Luftfahrtbundesamt vorgeschrieben sind und dem Erhalt der Flugzeugmusterberechtigung der Piloten dienen. Zunächst erfolgt die Analyse von Konstrukten und Methoden, die als Kriterien einer Messung zugänglich gemacht werden sollen. Das Ziel der Studie ist es, anhand dieser Konstrukte und Methoden in einer statistischen Analyse der erhobenen Daten Aussagen über das Ausmaß Konstruktvalidität des entwickelten Bewertungsbogens zu formulieren. In diesem Zusammenhang ist zu prüfen, ob die Bewertungen der Fähigkeiten in den klassifizierten Situationen im Flugsimulator generalisierbar sind, oder, ob diese von der spezifischen Situation abhängen
The Role of Information Retrieval in the Question Answering System IRSAW
No full textInformation on the internet is a vast resource for question answering. As the amount of available information from web pages increases, novel methods for finding precise answers to user queries and questions must be found. Standard information retrieval methods are efficient, but often fail to provide a user with short, precise answers. A deep linguistic analysis of all information is time consuming, but it offers more advanced means to find answers to a user’s question. Shallow natural language processing methods seem to work well on a limited range of questions, but they are not suitable for finding answers to more complex questions. This paper describes work in progress on the question answering system IRSAW (Intelligent Information Retrieval on the Basis of a Semantically Annotated Web), a system that combines information retrieval with a deep linguistic analysis of texts to obtain answers to natural language questions. In IRSAW, different techniques for finding answers lead to different sets of answer candidates, which are then merged to produce a final answer. The system’s architecture and functionality are described before evaluation results of a first prototype are presented
A Word Sense-Oriented User Interface for Interactive Multilingual Text Retrieval
No full textIn this paper we present an interface for supporting a user in an interactive cross-language search process using semantic classes. In order to enable users to access multilingual information, different problems have to be solved: disambiguating and translating the query words, as well as categorizing and presenting the results appropriately. Therefore, we first give a brief introduction to word sense disambiguation, cross-language text retrieval and document categorization and finally describe recent achievements of our research towards an interactive multilingual retrieval system. We focus especially on the problem of browsing and navigation of the different word senses in one source and possibly several target languages. In the last part of the paper, we discuss the developed user interface and its functionalities in more detail
The Effects of Topic Familiarity on User Search Behavior in Question Answering Systems
No full textThis paper reports on experiments that attempt to characterize the relationship between users and their knowledge of the search topic in a Question Answering (QA) system. It also investigates user search behavior with respect to the length of answers presented by a QA system. Two lengths of answers were compared; snippets (one to two sentences of text) and exact answers. A user test was conducted, 92 factoid questions were judged by 44 participants, to explore the participants’ preferences, feelings and opinions about QA system tasks. The conclusions drawn from the results were that participants preferred and obtained higher accuracy in finding answers from the snippets set. However, accuracy varied according to users’ topic familiarity; users were only substantially helped by the wider context of a snippet if they were already familiar with the topic of the question, without such familiarity, users were about as accurate at locating answers from the snippets as they were in exact set
Sound Multi-objective Feature Space Transformation for Clustering
No full textIn this work we propose a novel, generalized framework for feature space transformation in unsupervised knowledge discovery settings. Unsupervised feature space transformation inherently is a multi-objective optimization problem. In order to facilitate data exploration, transformations should increase the quality of the result and should still preserve as much of the original data set information as possible. We exemplify this relationship on the problem of data clustering. First, we show that existing approaches to multi-objective unsupervised feature selection do not pose the optimization problem in an appropriate way. Furthermore, using feature selection only is often not sufficient for real-world knowledge discovery tasks. We propose a new, generalized framework based on the idea of information preservation. This framework enables feature selection as well as feature construction for unsupervised learning. We compare our method against existing approaches on several real world data sets
Case-Based Characterization and Analysis of Subgroup Patterns
No full textIn this paper, we propose a case-based approach for characterizing and analyzing subgroup patterns: We present techniques for retrieving characteristic factors and cases, and merge these into prototypical cases for presentation to the user. In general, cases capture knowledge and concrete experiences of specific situations. By exploiting case-based knowledge for characterizing a subgroup pattern, we can provide additional information about the subgroup extension. We can then present the subgroup pattern in an alternative condensed form that characterizes the subgroup, and enables a convenient retrieval of interesting associated (meta-)information