Text mining and multimedia search in a large content repository (2009)
Paaß, G., Eickeler, S., Wrobel, S.
Methods of acquiring, seeking and processing knowledge are a strategically vital issue in the context of globalized competition. One of the main subjects currently being researched is the development...
Text mining and multimedia search in a large content repository (2009)
Paaß, G., Eickeler, S., Wrobel, S.
Methods of acquiring, seeking and processing knowledge are a strategically vital issue in the context of globalized competition. One of the main subjects currently being researched is the development...
Information and knowlege management (2009)
Paaß, G., Schneider, D., Wrobel, S.
In recognition of knowledge as a valuable resource, there is a whole spectrum of processes, methods and systems for the generation, identification, representation, distribution and communication of...
Context-based clustering of image search results (2009)
Wang, H., Missura, O., Gärtner, T., Wrobel, S.
In this work we propose to cluster image search results based on the textual contents of the referring webpages. The natural ambiguity and context-dependence of human languages lead to problems that...
Metadata extraction using text mining (2009)
Seth, S., Rüping, S., Wrobel, S.
Grid technologies have proven to be very successful in the area of eScience, and healthcare in particular, because they allow to easily combine proven solutions for data querying, integration, and...
Optimistic estimate pruning strategies for fast exhaustive subgroup discovery (2008)
Grosskreutz, H., Rüping, S., Shabaani, N., Wrobel, S.
Subgroup discovery is the task of finding subgroups of a population which exhibit both distributional unusualness and high generality at the same time. Since the corresponding evaluation functions...
Optimistic estimate pruning strategies for fast exhaustive subgroup discovery (2008)
Grosskreutz, H., Rüping, S., Shabaani, N., Wrobel, S.
Subgroup discovery is the task of finding subgroups of a population which exhibit both distributional unusualness and high generality at the same time. Since the corresponding evaluation functions...
Geppert, H., Horváth, T., Gärtner, T., Wrobel, S., Bajorath, J.
Similarity searching using molecular fingerprints is computationally efficient and a surprisingly effective virtual screening tool. In this study, we have compared ranking methods for similarity...
Data mining for security and crime detection (2008)
Paaß, G., Reinhardt, W., Rüping, S., Wrobel, S.
As the Internet becomes more pervasive in all areas of human activity, attackers can use the anonymity of cyberspace to commit crimes and compromise the IT infrastructure. As currently there is no...
Tight optimistic estimates for fast subgroup discovery (2008)
Grosskreutz, H., Rüping, S., Wrobel, S.
Subgroup discovery is the task of finding subgroups of a population which exhibit both distributional unusualness and high generality. Due to the non monotonicity of the corresponding evaluation...
Vorrichtung und Verfahren zum Bestimmen einer pharmazeutischen Aktivitaet eines Molekuels (2008)
Horvath, T., Gaertner, T., Wrobel, S.
DE 102008005062 A1 UPAB: 20090806 NOVELTY - The device comprises a first mechanism (110) for determining atomic structures occurring in the molecules, a mechanism (120) for assigning characteristic...
Geovisual analytics for spatial decision support: Setting the research agenda (2007)
Andrienko, G., Andrienko, N., Jankowski, P., Keim, D., MacEachren, A., ...
This article summarizes the results of the workshop on Visualization, Analytics & Spatial Decision Support, which took place at the GIScience conference in September 2006. The discussions at the...
Visual analytics tools for analysis of movement data (2007)
Andrienko, G., Andrienko, N., Wrobel, S.
With widespread availability of low cost GPS devices, it is becoming possible to record data about the movement of people and objects at a large scale. While these data hide important knowledge for...
Visual analytics methods for movement data (2007)
Andrienko, G., Andrienko, N., Kopanakis, I., Litgenberg, A., Wrobel, S.
A refinement operator for outerplanar graphs (2006)
Horváth, T., Akutsu, T., Wrobel, S.
Outerplanar graphs form a practically relevant class of graphs which appear efficiently computable bottom-up refinement operator for tenuous outerplanar graphs defined by combining techniques from...
Frequent subgraph mining in outerplanar graphs (2006)
Horváth, T., Ramon, J., Wrobel, S.
In recent years there has been an increased interest in algorithms that can perform frequent pattern discovery in large databases of graph structured objects. While the frequent connected subgraph...
Kernels for predictive graph mining (2006)
Wrobel, S., Gärtner, T., Horváth, T.
In many application areas, graphs are a very natural way of representing structural aspects of a domain. While most classical algorithms for data analysis cannot directly deal with graphs, recently...
Effective rule induction from labeled graphs (2006)
Horváth, T., Hoche, S., Wrobel, S.
Labeled graphs provide a natural way of representing objects and the way they are connected. They have various applications in different fields, such as for example in computational chemistry. They...
Bias-free hypothesis evaluation in multirelational domains (2006)
In propositional domains using a separate test set via random sampling or cross validation is generally considered to be an unbiased estimator of true error. In multirelational domains previous work...
Bias-free hypothesis evaluation in multirelational domains (2005)
In propositional domains, using a separate test set via random sampling or cross validation is generally considered to be an unbiased estimator of true error. In multirelational domains, previous...
Bias-free hypothesis evaluation in multirelational domains (2005)
In propositional domains, using a separate test set via random sampling or cross validation is generally considered to be an unbiased estimator of true error. In multirelational domains, previous...
Object correspondence as a machine learning problem (2005)
Schölkopf, B., Steinke, F., Blanz, V., Raedt, L. De, Wrobel, S.
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspondence. The fields...
Intrinsic Dimensionality Estimation of Submanifolds in Euclidean space (2005)
Hein, M., Audibert, Y., Raedt, L. De, Wrobel, S.
We present a new method to estimate the intrinsic dimensionality of a submanifold M in Euclidean space from random samples. The method is based on the convergence rates of a certain U-statistic on...
Healing the Relevance Vector Machine through Augmentation (2005)
Rasmussen, C.E., Candela, J., Raedt, L. De, Wrobel, S.
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties have the unintuitive...
Propagating Distributions on a Hypergraph by Dual Information Regularization (2005)
Tsuda, K., Raedt, L. De, Wrobel, S.
In the information regularization framework by Corduneanu and Jaakkola (2005), the distributions of labels are propagated on a hypergraph for semi-supervised learning. The learning is efficiently...
Large Margin Non-Linear Embedding (2005)
Zien, A., Candela, J., Raedt, L. De, Wrobel, S.
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, we...
Learning from Labeled and Unlabeled Data on a Directed Graph (2005)
Zhou, D., Huang, J., Schölkopf, B., Raedt, L. De, Wrobel, S.
We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is considered. The time...
Building Sparse Large Margin Classifiers (2005)
Wu, M., Schölkopf, B., BakIr, G., Raedt, L. De, Wrobel, S.
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The added constraint...
Implicit Surface Modelling as an Eigenvalue Problem (2005)
Walder, C., Chapelle, O., Schölkopf, B., Raedt, L. De, Wrobel, S.
We discuss the problem of fitting an implicit shape model to a set of points sampled from a co-dimension one manifold of arbitrary topology. The method solves a non-convex optimisation problem in the...
A Brain Computer Interface with Online Feedback based on Magnetoencephalography (2005)
Lal, T.N., Schröder, M., Hill, J., Preissl, H., Hinterberger, T., Mellinger, J., ...
The aim of this paper is to show that machine learning techniques can be used to derive a classifying function for human brain signal data measured by magnetoencephalography (MEG), for the use in a...
Comparative Evaluation of Approaches to Propositionalization (2003)
Rawles, S., Zelezny, F., Flach, P.A., Lavrac, N., Wrobel, S.
Propositionalization has already been shown to be a promising approach for robustly and effectively handling relational data sets for knowledge discovery. In this paper, we compare up-to-date methods...
A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting (2003)
Boosting has established itself as a successful technique for decreasing the generalization error of classification learners by basing predictions on ensembles of hypotheses. While previous research...
Comparative evaluation of approaches to propositionalization (2003)
S. Rawles, P. A. Flach, N. Lavrač, S. Wrobel
Propositionalization has already been shown to be a particularly promising approach for robustly and effectively handling relational data sets for knowledge discovery. In this paper, we compare...
Feature Selection for Propositionalization (2002)
Following the success of inductive logic programming on structurally complex but small problems, recently there has been strong interest in relational methods that scale to real-world databases....
Learning Hidden Markov Models for Information Extraction Actively from Partially Labeled Text (2002)
Scheffer, T., Wrobel, S., Popov, B., Ognianov, D., Decomain, C., Hoche, S.
Finding the most interesting patterns in a database quickly by using sequential sampling (2002)
Many discovery problems, e.g., subgroup or association rule discovery, can naturally be cast as n-best hypotheses problems where the goal is to find the n hypotheses from a given hypothesis space...
On the stability of example-driven learning systems: A case study in multirelational learning (2002)
Relational Instance-Based Learning with Lists and Terms (2001)
Horváth, T., Wrobel, S., Bohnebeck, U.
The similarity measures used in first-order IBL so far have been limited to the function-free case. In this paper we show that a lot of power can be gained by allowing lists and other terms in the...
Interactive Configuration in KIKon (1997)
Beilken, C., Börding, J., Orth, W., Petersen, U., Rahmer, J., Schaaf, J.W., ...
Workshop Lernen, Adaption und Selbstorganisation in verteilten intelligenten Systemen (1996)
Haugeneder, H., Kraetzschmar, G., Müller, J., Weiß, G., Wrobel, S.
Lernen, Adaption und Selbstorganisation in verteilten intelligenten Systemen (1996)
Haugeneder, H., Krätzschmar, G., Müller, J., Weiß, G., Wrobel, S.
Configuration of telecommunication systems in KIKON (1996)
Emde, W., Beilken, C., Börding, J., Petersen, U., Spenke, M., Voß, A., ...