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In this paper we present Text2Onto, a framework for on-tology learning from textual resources. Three main features distinguish Text2Onto from our earlier framework TextToOnto as well as other state-of-the-art ontology learning frameworks. First, by representing the learned knowledge at a meta-level in the form of instantiated model-ing primitives within a(More)
While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic markup. In this paper, we examine semantic annotation, identify a(More)
We present a novel approach to the automatic acquisition of taxonomies or concept hierarchies from a text corpus. The approach is based on Formal Concept Analysis (FCA), a method mainly used for the analysis of data, i.e. for investigating and processing explicitly given information. We follow Harris' distributional hypothesis and model the context of a(More)
Without the proliferation of formal semantic annotations, the Semantic Web is certainly doomed to failure. In earlier work we presented a new paradigm to avoid this: the 'Self Annotating Web', in which globally available knowledge is used to annotate resources such as web pages. In particular, we presented a concrete method instantiating this paradigm,(More)
Irony is an important device in human communication , both in everyday spoken conversations as well as in written texts including books, websites, chats, reviews, and Twitter messages among others. Specific cases of irony and sarcasm have been studied in different contexts but, to the best of our knowledge, only recently the first publicly available corpus(More)
The goal of giving a well-defined meaning to information is currently shared by endeavors such as the Semantic Web as well as by current trends within Knowledge Management. They all depend on the large-scale formalization of knowledge and on the availability of formal metadata about information resources. However, the question how to provide the necessary(More)
This volume is a collection of extended versions of papers first presented at workshops held at the European Conference on Artificial Intelligence and the International Conference on Knowledge Engineering and Management in 2004. The editors have all made significant contributions to the field of ontology learning and have organized some of the important(More)
Named entity recognition and classification research has so far mainly focused on supervised techniques and has typically considered only small sets of classes with regard to which to classify the recognized entities. In this paper we address the classification of named entities with regard to large sets of classes which are specified by a given ontology.(More)