In this study we address the problem of answering queries over information sources storing objects which are indexed by terms arranged in a taxonomy. We examine query languages of different expressivity and sources with different kinds of taxonomies. In the simplest kind, the taxonomy includes just term-to-term subsumption links. This case is used as a basis for further developments, in which w...

Taxonomies are an important resource for a variety of Natural Language Processing (NLP) applications. Despite this, the current stateof-the-art methods in taxonomy learning have disregarded word polysemy, in effect, developing taxonomies that conflate word senses. In this paper, we present an unsupervised method that builds a taxonomy of senses learned automatically from an unlabelled corpus. O...

Taxonomies can serve as browsing tools for document collections. However, given an arbitrary collection, pre-constructed taxonomies could not easily adapt to the specific topic/task present in the collection. This paper explores techniques to quickly derive task-specific taxonomies supporting browsing in arbitrary document collections. The supervised approach directly learns semantic distances ...

Taxonomy is indispensable in understanding natural language. A variety of large scale, usage-based, data-driven lexical taxonomies have been constructed in recent years. Hypernym-hyponym relationship, which is considered as the backbone of lexical taxonomies can not only be used to categorize the data but also enables generalization. In particular, we focus on one of the most prominent properti...

In this work we propose a formalization of a notion of contextual taxonomy, that is to say, a taxonomy holding only with respect to a specific context. To this aim, a new proposal for dealing with “contexts as abstract mathematical entities” is set forth, which is geared toward solving some problems arising in the area of normative system specifications for modeling multi-agent systems. Context...

Several real problems ranging from text classification to computational biology are characterized by hierarchical multi-label classification tasks. Most of the methods presented in literature focused on tree-structured taxonomies, but only few on taxonomies structured according to a Directed Acyclic Graph (DAG). In this contribution novel classification ensemble algorithms for DAG-structured ta...