OBJECTIVES This paper proposes a novel semantic method for auditing associative relations in biomedical terminologies. We tested our methodology on two Unified Medical Language System (UMLS) knowledge sources. METHODS We use the UMLS semantic groups as high-level representations of the domain and range of relationships in the Metathesaurus and in the Semantic Network. A mapping created betwee...

The need to guarantee digital archive interoperability has driven the standardization of resources forward. The tendency to make searchable on-line databases has stopped at data accessibility, often presented as a synthesis of the interpretation procedure. During data computerization, the creation of the database requires the selection of a model whose representation is left out of the encoding...

This paper presents a practical application of context for the evaluation of semantic similarity. The work is based on a new model for the assessment of semantic similarity among entity classes that satisfies cognitive properties of similarity and integrates contextual information. The semantic similarity model represents entity classes by their semantic relations (is-a and part-whole) and thei...

Deriving knowledge from information stored in unstructured documents is a major challenge. More specifically, binary relationships representing facts between entities can be extracted to populate semantic triple stores or large knowledge bases. The main constraint of all knowledge extraction approaches is to find a trade-off between quality and scalability. Thus, we propose in this paper SPIDER...

In automatic speech grading systems, rare research is followed through addressing the issue of GOR (Goodness Of pRosody). In this paper we propose a novel method by taking the advantage of our QBH (Query By Humming) techniques in 2008 MIREX evaluation task. A set of standard samples related to the top-cream students are initially picked up as templates, a cascade QBH structure is then taken fro...

Semantic Web knowledge bases, in particular large cross-domain data, are often noisy, incorrect, and incomplete with respect to type information. This incompleteness can be reduced, as previous work shows, with automatic type prediction methods. Most knowledge bases contain an ontology defining a type hierarchy, and, in general, entities are allowed to have multiple types (classes of an instanc...

Inconsistency handling is an aspect of requirements engineering that has attracted considerable research attention. We explore novel ways to applying semantic Web technologies to this problem, in the context of a Web-based agent-mediated environment for distributed requirements engineering. Disciplines Physical Sciences and Mathematics Publication Details This article was originally published a...

ASPI is a project that aims at creating a digital library of historical documents of Italian Psychology and extending it with semantic data. The extension makes it possible to retrieve archival documents not only on the basis of archival metadata, but also according to the connections the documents have with specific activities of researchers, groups and institutions, as well as with more gener...

In this paper, we provide a theoretical framework for feature selection in tree kernel spaces based on gradient-vector components of kernel-based machines. We show that a huge number of features can be discarded without a significant decrease in accuracy. Our selection algorithm is as accurate as and much more efficient than those proposed in previous work. Comparative experiments on three inte...

Selectional preferences, the tendencies of predicates to select for certain semantic classes of arguments, have been successfully applied to a number of tasks in computational linguistics including word sense disambiguation, semantic role labeling, relation extraction, and textual inference. Here we leverage the information encoded in selectional preferences to the task of predicting fine-grain...