A thesaurus and an ontology provide a set of structured terms, phrases, and metadata, often in a hierarchical arrangement, that may be used to index, search, and mine documents. We describe the decisions that should be made when including a term, deciding whether a term should be subdivided into its subclasses, or determining which of more than one set of possible subclasses should be used. Bas...

Systems for learning text classiiers recently gained considerable interest. One technique to implement such systems is rule induction. While most other approaches rely on a relatively simple document representation and do not make use of any background knowledge, rule induction algorithms ooer a good potential for improvements in both of these areas. In this paper , we show how an operator-base...

We considered the tolerance matrix generated using tolerance rough set model as a kind of an associative thesaurus. The effectiveness of the thesaurus was measured using performance measures commonly used in information retrieval, recall and precision, where they were used for the terms rather than documents. A corpus consists of keywords defined as highly related with particular topic by human...

The focus of our study is zero-hit queries in keyword subject searches and the effort of increasing recall in these cases by reformulating and, then, expanding the initial queries using an external source of knowledge, namely a thesaurus. To this end, the objectives of this study are twofold. First, we perform the mapping of query terms to the thesaurus terms. Second, we use the matched terms t...

Roget’s Thesaurus and WordNet are very widely used lexical reference works. We describe an automatic mapping procedure that effectively produces French translations of the terms in these two resources. Our approach to the challenging task of disambiguation is based on structural statistics as well as measures of semantic relatedness that are utilized to learn a classification model for associat...

Thesauri are possible building blocks of a web of linked data. As DBpedia for large data sets in general, specialized thesauri could be useful as interlinking hubs for professional communities – if they are available on the linked data web. The paper describes the conversion of a large economics thesaurus to RDF/SKOS, using the enhancement mechanisms of SKOS to dispose some nonstandard features...

Building a thesaurus is very costly and time-consuming task. To alleviate this problem, this paper proposes a new method for extending a thesaurus by adding taxonomic information automatically extracted from an MRD. The proposed method adopts a machine learning algorithm in acquiring rules for identifying a taxonomic relationship to minimize human-intervention. The accuracy of our method in ide...

This paper describes a thesaurus-based class n-gram model for broadcast news transcription. The most important issue concerned with class n-gram models is how to develop a word classification. We construct a word classification mapping based on a thesaurus so as to maximize the average mutual information function on a training corpus. To examine the effectiveness of the new method, we compare i...

In this paper, we argue on the interest of anchoring Dutch Cultural Heritage controlled vocabularies to WordNet, and demonstrate a reusable methodology for achieving this anchoring. We test it on two controlled vocabularies, namely the GTAA thesaurus, used at the Netherlands Institute for Sound and Vision (the Dutch radio and television archives), and the GTT thesaurus, used to index books of t...

Auditing biomedical terminologies often results in the identification of inconsistencies and thus helps to improve their quality. In this paper, we present a method based on Semantic Web technologies for auditing biomedical terminologies and apply it to the NCI thesaurus. We stored the NCI thesaurus concepts and their properties in an RDF triple store. By querying this store, we assessed the co...