In this paper, we propose the Automatic Taxonomy Construction from Text (ATCT) framework for building taxonomies from text-based Web corpora. The framework is composed of multiple processing steps. Firstly, domain terms are extracted using a filtering method. Subsequently, Word Sense Disambiguation (WSD) is optionally applied in order to determine the senses of these terms. Then, by means of a subsumption technique, the resulting concepts are arranged in a hierarchy. We construct taxonomies with and without WSD and we investigate the effect of WSD on the quality of concept type-of relations using an evaluation framework that uses a golden taxonomy. We find that WSD improves the quality of the built taxonomy in terms of the taxonomic F-Measu...
This article focuses on Word Sense Disambiguation (WSD), which is a Natural Lan-guage Processing tas...
textabstractObtaining a useful complete overview of Web-based product information has become difficu...
This paper introduces a method to improve supervised word sense disambiguation perfor-mance by inclu...
This paper proposes a framework to automatically construct taxonomies from a corpus of text document...
The unavailability of very large corpora with semantically disambiguated words is a major limitation...
Abstract. The term “knowledge acquisition bottleneck ” has been used in Word Sense Disambiguation Ta...
An important problem in Natural Language Processing is identifying the correct sense of a word in a ...
Automated Text Categorization has reached the levels of accuracy of human experts. Provided that eno...
This master thesis investigated automatic methods of Word Sense Disambiguation (WSD) in HTML pages. ...
We describe an algorithm that combines lexical information (from WordNet 1.7) with Web di-rectories ...
Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowled...
Word Sense Disambiguation (WSD) is traditionally considered an AI-hard problem. A break-through in t...
The unavailability of very large corpora with se-mantically disambiguated words is a major limi-tati...
This work proposes a basic framework for resolving sense disambiguation through the use of Semantic ...
This article focuses on Word Sense Disambiguation (WSD), which is a Natural Language Processing task...
This article focuses on Word Sense Disambiguation (WSD), which is a Natural Lan-guage Processing tas...
textabstractObtaining a useful complete overview of Web-based product information has become difficu...
This paper introduces a method to improve supervised word sense disambiguation perfor-mance by inclu...
This paper proposes a framework to automatically construct taxonomies from a corpus of text document...
The unavailability of very large corpora with semantically disambiguated words is a major limitation...
Abstract. The term “knowledge acquisition bottleneck ” has been used in Word Sense Disambiguation Ta...
An important problem in Natural Language Processing is identifying the correct sense of a word in a ...
Automated Text Categorization has reached the levels of accuracy of human experts. Provided that eno...
This master thesis investigated automatic methods of Word Sense Disambiguation (WSD) in HTML pages. ...
We describe an algorithm that combines lexical information (from WordNet 1.7) with Web di-rectories ...
Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowled...
Word Sense Disambiguation (WSD) is traditionally considered an AI-hard problem. A break-through in t...
The unavailability of very large corpora with se-mantically disambiguated words is a major limi-tati...
This work proposes a basic framework for resolving sense disambiguation through the use of Semantic ...
This article focuses on Word Sense Disambiguation (WSD), which is a Natural Language Processing task...
This article focuses on Word Sense Disambiguation (WSD), which is a Natural Lan-guage Processing tas...
textabstractObtaining a useful complete overview of Web-based product information has become difficu...
This paper introduces a method to improve supervised word sense disambiguation perfor-mance by inclu...