University of Hildesheim
Not a member yet
1144 research outputs found
Sort by
The FLOSSWALD Information System on Free and Open Source Software
No full textWe propose the implementation of an intelligent information system on free and open source software. This system will consist of a case-based reasoning (CBR) system and several machine learning modules to maintain the knowledge base and train the CBR system thus enhancing its performance. Our knowledge base will include data on free and open source software provided by the Debian project, the FLOSSmole project, and other public free and open source software directories. We plan to enrich these data by learning additional information such as concepts and different similarities. With this knowledge base, we hope to be able to create an information system that will be capable of answering queries based on precise as well as vague criteria and give intelligent recommendations on software based on the preferences of the user
Contextual Retrieval in Knowledge Intensive Business Environments
No full textKnowledge-intensive work plays an increasingly important role in organisations of all types. This work is characterized by a defined input and a defined output but not the way how to transform the input to an output. Within this context, the research project DYONIPOS aims at encouraging the two crucial roles in a knowledge-intensive organization - the process executer and the process engineer. Ad-hoc support will be provided for the knowledge worker by synergizing the development of context sensitive, intelligent, and agile semantic technologies with contextual retrieval. DYONIPOS provides process executers with guidance through business processes and just-in-time resource support based on the current user context, that are the focus of this paper
Knowledge Search within a Company-WIKI
No full textThe usage of Wikis for the purpose of knowledge management within a business company is only of value if the stored information can be found easily. The fundamental characteristic of a Wiki, its easy and informal usage, results in large amounts of steadily changing, unstructured documents. The widely used full-text search often provides search results of insufficient accuracy. In this paper, we will present an approach likely to improve search quality, through the use of Semantic Web, Text Mining, and Case Based Reasoning (CBR) technologies. Search results are more precise and complete because, in contrast to full-text search, the proposed knowledge-based search operates on the semantic layer
Einsatz von Entry Vocabulary Modulen zur Optimierung von mehrsprachigen Information Retrieval Systemen am Beispiel der Datenbank des Fachinformationsverbundes Internationale Beziehungen und Länderkunde
No full textThis thesis deals with the development and evaluation of an information retrieval system encorporating a dynamic entry vocabulary module (EVM). Furthermore, the evaluation of the system is covering an analysis of the potential performance gains that can be reached employing an evm. The data that the system is being developed for is the database of the Fachinformationsverbund Internationale Beziehungen und Länderkunde which has been kindly provided by the cooperating partner Stiftung Wissenschaft und Politik, Berlin. The system has also been evaluated on the data of the German Indexing and Retrieval Testdatabase (GIRT). In conclusion, this thesis compares two simpler evaluation runs without any additional modules and three advanced evaluation runs with all additional modules enabled. The evaluation resulted, alongside a series of other results and findings, in an advantage for the advanced runs and hence supports the theory of the potential of an entry vocabulary module.Diese Arbeit befasst sich mit der Entwicklung und Evaluierung eines Information Retrieval Systems. Im Vordergrund steht hierbei die Entwicklung eines dynamischen Entry Vocabulary Moduls (EVM). Im Laufe der Arbeit soll ein durch ein EVM unterstütztes Retrieval System in seiner Leistungsfähigkeit untersucht werden. Bei der Datenbasis, für die das System entwickelt und auf der es evaluiert wird, handelt es sich um den Datenbestand des Fachinformationsverbundes Internationale Beziehungen und Länderkunde, die als Auszug vom Kooperationspartner Stiftung Wissenschaft und Politik bereitgestellt wurde. Auÿerdem wurde das System auf die German Indexing and Retrieval Testdatabase (GIRT) angewendet. Diese Forschungsarbeit hat neben vielen weiteren Erkenntnissen ergeben, dass im direkten Vergleich zwischen zwei Evaluierungsläufen des Systems ohne zusätzliche Module und drei Läufen mit zusätzlichen Modulen die Retrievalleistung gesteigert werden konnte und das EVM daran maßgeblichen Anteil hatte
Validating Navigation Time Prediction Models for Menu Optimization
No full textAuthors of menu optimization methods often use navigation time prediction models without validating whether the model is adequate for the site and its users. We review the assumptions underlying navigation time prediction models and present a method to validate these assumptions offline. Experiments on four web sites show how accurate the various model features describe the behavior of the users. These results can be used to select the best model for a new optimization task. In addition, we find that the existing optimization methods all use suboptimal models. This indicates that our results can significantly contribute to more effective menu optimization
Exploring the Potential of Semantic Relatedness in Information Retrieval
No full textEmploying lexical-semantic knowledge in information retrieval (IR) is recognised as a promising way to go beyond bag-of-words approaches to IR. However, it has not yet become a standard component of IR systems due to many difficulties which arise when knowledge-based methods are applied in IR. In this paper, we explore the use of semantic relatedness in IR computed on the basis of GermaNet, a German wordnet [Kunze, 2004]. In particular, we present several experiments on the German IR benchmarks GIRT’2005 (training set) and GIRT’2004 (test set) aimed at investigating the potential of semantic relatedness in IR as opposed to bag-of-words models, as implemented e.g. in Lucene [Gospodnetic and Hatcher, 2005]. These experiments shed some light upon how to combine the strengths of both models in our future work. Our evaluation results show some improvement in IR performance over the bag-of-words model, i.e. a significant increase in mean average precision of about 5 percent points for the training set, but only 1 percent increase for our test set
Dynamisches Relevanz-Feedback im Patent-Retrievalsystem PatentAide
No full textIm Patent Retrieval haben sich Rankingverfahren und Methoden wie Relevanz- Feedback noch nicht etabliert. An Ranking Systemen wird vor allem die mangelnde Transparenz für den Benutzer bemängelt. Das System PatentAide versucht, aufbauend auf einer Analyse der Rechercheprozesse im Patent Retrieval, ein Ranking-System zu implementieren. PatentAide unterstützt wichtige Techniken im Patent-Retrieval Prozess wie Term-Erweiterung, bietet ein geranktes Ergebnis und erlaubt darüber hinaus dynamisches Relevanz-Feedback
Information Retrieval is for Everybody – Beobachtungen und Thesen
No full textIn this paper, the idea of ubiquitous information retrieval is presented in a storytelling manner. Starting from a rough review of information retrieval system usage, some empirical hints on IR in everyday life are given. Ch. 4 explores the heterogeneity of interaction with IRS for one day in the life of a (common search engine) user. In ch. 5 summarizes these observations and suggests research approaches for modelling information retrieval as an essential component of interaction in the information society
LWA 2006 : Lernen – Wissensentdeckung – Adaptivität (9.–11.10.2006 in Hildesheim)
No full textDie Workshop-Woche "Lernen, Wissen und Adaptivität 2006" (LWA 06) versteht sich als Forum, bei dem etablierte und neu auf einem Gebiet arbeitende Wissenschaftlerinnen und Wissenschaftler ihre aktuellen Arbeiten vorstellen und intensiv miteinander diskutieren können. Dies macht den besonderen Reiz dieser Veranstaltung aus, welche erstmals 1999 in Magdeburg stattfand. Der diesjährige Austragungsort war die Universität Hildesheim und wie in den Jahren zuvor wurden von verschiedenen Fachgruppen der Gesellschaft für Informatik e. V. (GI) eine Reihe interessanter Workshops organisiert. Dies waren im Einzelnen: FG-ABIS (Workshop der Fachgruppe "Adaptivität und Benutzermodellierung in interaktiven Softwaresystemen"); FG-IR (Workshop der Fachgruppe "Information Retrieval"); FG-KDML / AK-KD (Workshop der Fachgruppe "Knowledge Discovery, Data Mining und Maschinelles Lernen" sowie des Arbeitskreises "Knowledge Discovery"); FG-WM (Workshop der Fachgruppe "Wissensmanagement")
Can Log Files Analysis Estimate Learners’ Level of Motivation?
No full textThe learners’ motivation has an impact on the quality of learning, especially in e-Learning environments. Most of these environments store data about the learner’s actions in log files. Logging the users’ interactions in educational systems gives the possibility to track their actions at a refined level of detail. Data mining and machine learning techniques can “give meaning” to these data and provide valuable information for learning improvement. An area where improvement is absolutely necessary and of great importance is motivation, known to be an essential factor for preventing attrition in e-Learning. In this paper we investigate if the log files data analysis can be used to estimate the motivational level of the learner. A decision tree is build from a limited number of log files from a web-based learning environment. The results suggest that time spent reading is an important factor for predicting motivation; also, performance in tests was found to be a relevant indicator of the motivational level