A novel method for unsupervised acquisition of knowledge for taxonomies of concepts from raw Wikipedia text is presented. We assume that the concepts classified under the same node in a taxonomy are described in a comparable way in Wikipedia. The concepts in 6 taxonomies extracted from WordNet are mapped onto Wikipedia pages and the lexico-syntactic patterns describing semantic structures expre...

Concept taxonomies offer a powerful means for organizing knowledge, but this organization must allow for many overlapping and fine-grained perspectives if a general-purpose taxonomy is to reflect concepts as they are actually employed and reasoned about in everyday usage. We present here a means of bootstrapping finely-discriminating taxonomies from a variety of different starting points, or se...

A number of approaches for automatic audio classification are based on hierarchical taxonomies since it is acknowledged that improved performance can be thereby obtained. In this paper, we propose a new strategy to automatically acquire hierarchical taxonomies, using machine learning methods, which are expected to maximize the performance of subsequent classification. It is shown that the optim...

We propose a simple, yet effective, approach towards inducing multilingual taxonomies from Wikipedia. Given an English taxonomy, our approach leverages the interlanguage links of Wikipedia followed by character-level classifiers to induce high-precision, high-coverage taxonomies in other languages. Through experiments, we demonstrate that our approach significantly outperforms the stateof-the-a...

The great variety of meditation techniques found in different contemplative traditions presents a challenge when attempting to create taxonomies based on the constructs of contemporary cognitive sciences. In the current issue of Consciousness and Cognition, Travis and Shear add 'automatic self-transcending' to the previously proposed categories of 'focused attention' and 'open monitoring', and ...

One trend in Human Computer Interaction is to extend the sensory-motor capabilities of computer systems to better match the natural communication means of humans. Parallel to the exploratory development of such systems, significant effort is being deployed in defining frameworks and taxonomies for reasoning about the design space of such systems. This article is a preliminary effort to review c...

In an increasingly digitalized world, financial institutions have become data hoarders and find it difficult to efficiently exploit and interpret data from various sources. XBRL provides a global standard to exchange financial information. Although XBRL solves the syntactic heterogeneity problem, it doesnt solve the semantic heterogeneity problem when involving multiple taxonomies. In this pape...

Lexical taxonomies have tree-like structures and can thus be extended to become decision trees that serve for their own extension. In this paper, a semi-automatic procedure for extending lexical taxonomies is proposed that makes use of term extraction methods for identifying new concepts and that uses cooccurrence data from large corpora to generate the necessary features (semantic descriptions...

Morphological Taxonomies are a widely popular tool in Information Systems to systematically deconstruct an artifact into designable dimensions and characteristics. Subsequently, these taxonomies have engraved them knowledge about the design of artifacts, i.e., descriptive knowledge. Most studies producing morphological refrain from giving prescriptive advice design, specific configuration artif...

We introduce EXTASEM!, a novel approach for the automatic learning of lexical taxonomies from domain terminologies. First, we exploit a very large semantic network to collect thousands of in-domain textual definitions. Second, we extract (hyponym, hypernym) pairs from each definition with a CRF-based algorithm trained on manually-validated data. Finally, we introduce a graph induction procedure...