Exploiting Structure and Semantics for Expressive Text Kernels (2008)
Stephan Bloehdorn, Alessandro Moschitti
Several problems in text categorization are too hard to be solved by standard bag-of-words representations. Work in kernel-based learning has approached this problem by (i) considering information...
Kosmas Petridis, Kai Kuehn, Siegfried H, Stephan Bloehdorn, Carsten Saathoff, Yannis Avrithis, ...
Annotations of multimedia documents typically have been pursued in two different directions. Either previous approaches have focused on low-level descriptors, such as dominant color, or they have...
UDDI project --- Universal Description, Discovery and Integration (2008)
Stephan Bloehdorn, Ro Moschitti
Abstract. The exploitation of syntactic structures and semantic background knowledge has always been an appealing subject in the context of text retrieval and information management. The usefulness...
Designing Semantic Kernels as Implicit Superconcept Expansions (2008)
Stephan Bloehdorn, Roberto Basili, Marco Cammisa, Ro Moschitti
Recently, there has been an increased interest in the exploitation of background knowledge in the context of text mining tasks, especially text classification. At the same time, kernel-based learning...
An Ontology-based framework for text mining (2008)
Stephan Bloehdorn, Andreas Hotho, Steffen Staab
Structuring of text document knowledge frequently appears either by ontologies and metadata or by automatic (un-)unsupervised text categorization. This paper describes our integrated framework OTTO...
2006. Clustering of Polysemic Words (2008)
Laurent Cicurel, Stephan Bloehdorn
Abstract. In this paper, we propose an approach for constructing clusters of related terms that may be used for deriving formal conceptual structures in a later stage. In contrast to previous...
EXPRESSIVE RESOURCE DESCRIPTIONS FOR ONTOLOGY-BASED INFORMATION RETRIEVAL (2008)
Thanh Tran, Stephan Bloehdorn, Peter Haase
Abstract: In this paper, we introduce an expressive ontology-based model for representing resources with respect to a domain ontology. Our resource model is based on semantic web standards as well as...
Organization Workshop Organizers (2008)
Stephan Bloehdorn, Marko Grobelnik, Peter Mika, Thanh Tran Duc, Bettina Berendt, Paul Buitelaar, ...
International Workshop located at the
TagFS --- Tag Semantics for Hierarchical File Systems (2006)
Today, most computer users work with traditional hierarchical file systems for organizing large amounts of personal files. Recently, tagging has grown popular as an alternative means of organizing...
Learning in Web Search Guest Editors: (2006)
Stephan Bloehdorn, Wray Buntine, Andreas Hotho, Anton P. Železnikar
Informatica is a journal primarily covering the European computer science and informatics community; scientific and educational as well as technical, commercial and industrial. Its basic aim is to...
Abstract — In this work, we will report on the use of selforganizing maps (SOMs) in a clustering and relation extraction task. Specifically, we use the approach of self-organizing maps for...
Tagfs - tag semantics for hierarchical file systems (2006)
Stephan Bloehdorn, Olaf Görlitz, Simon Schenk, Max Völkel, Forschungszentrum Informatik Karlsruhe
Abstract: Today, most computer users work with traditional hierarchical file systems for organizing large amounts of personal files. Recently, tagging has grown popular as an alternative means of...
Knowledge Representation and Semantic Annotation of Multimedia Content (2006)
Kosmas Petridis, Stephan Bloehdorn, Carsten Saathoff, Stamatia Dasiopoulou, Vassilis Tzouvaras, Yannis Avrithis, ...
Abstract. Knowledge representation and annotation of multimedia documents typically have been pursued in two different directions. Previous approaches have focused either on low level descriptors,...
Semantic annotation of images and videos for multimedia analysis (2005)
Stephan Bloehdorn, Kosmas Petridis, Carsten Saathoff, Nikos Simou, Yannis Avrithis, Siegfried H, ...
Abstract. Annotations of multimedia documents typically have been pursued in two different directions. Either previous approaches have focused on low level descriptors, such as dominant color, or...
Intelligent Community Lifecycle Support (2005)
Stephan Bloehdorn, Peter Haase, Mark Hefke, York Sure, Christoph Tempich
Knowledge sharing in communities has attracted much attention in the field of knowledge management in research and practice. In this paper we outline a view where the community lifecycle is supported...
2006): Learning Ontologies to Improve Text Clustering and Classification (2005)
Stephan Bloehdorn, Andreas Hotho
Abstract. Recent work has shown improvements in text clustering and classification tasks by integrating conceptual features extracted from ontologies. In this paper we present text mining experiments...
Lws Stephan Bloehdorn, Wray Buntine, Andreas Hotho, Stephan Bloehdorn, Wray Buntine, Andreas Hotho
The emerging world of search we see is one which makes increasing use of information extraction, gradually blends in semantic web technology and peer to peer systems, and uses grid computing as part...
Intelligent Community Lifecycle Support (2005)
Stephan Bloehdorn, Peter Haase
Abstract: Knowledge sharing in communities has attracted much attention in the field of knowledge management in research and practice. In this paper we outline a view where the community lifecycle is...
The swrc ontology - semantic web for research communities (2005)
York Sure, Stephan Bloehdorn, Peter Haase, Jens Hartmann, Daniel Oberle
Abstract. Representing knowledge about researchers and research communities is a prime use case for distributed, locally maintained, interlinked and highly structured information in the spirit of the...
Text classification by boosting weak learners based on terms and concepts (2004)
Document representations for text classification are typically based on the classical Bag-Of-Words paradigm. This approach comes with deficiencies that motivate the integration of features on a...
Boosting for text classification with semantic features (2004)
Stephan Bloehdorn, Andreas Hotho
Abstract. Current text classification systems typically use term stems for representing document content. Ontologies allow the usage of features on a higher semantic level than single words for text...