In this paper, we present an on-going project aiming at extending the Word-Net lexical database by encoding common sense featural knowledge elicited from language speakers. Such extension of WordNet is required in the framework of the STaRS.sys project, which has the goal of building tools for supporting the speech therapist during the preparation of exercises to be submitted to aphasic patients for rehabilitation purposes. We review some preliminary results and illustrate what extensions of the existing WordNet model are needed to accommodate for the encoding of commonsense (featural) knowledge
International audienceWordNet has facilitated important research in natural language processing but ...
This paper presents a general method to automatically build large knowledge bases from online lexica...
AbstractIn the last two decades, WordNet has evolved as the most comprehensive computational lexicon...
This thesis investigates the possibility to exploit human language resources and knowledge extractio...
In this paper, we propose an extension of the WordNet conceptual model, with the final purpose of en...
The difficulties of navigating vocabulary in an assistive com-munication device are exacerbated for ...
A long time passed from the first word said by Homo sapiens to the first word said by a machine. The...
Because meaningful sentences are composed of meaningful words, any system that hopes to process natu...
Princeton WordNet is one of the most widely-used resources for natural language processing, but is u...
As part of a project to construct an interactive program which will encourage children to play with ...
The role of generic lexical resources as well as specialized terminology is crucial in the design of...
In this paper we present a linguistic resource for the lexical representation of affective knowledge...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
In this paper we present a proposal to extend WordNet-like lexical databases by adding information a...
WordNet is currently the most widely used lexicon resource for general English language. We here arg...
International audienceWordNet has facilitated important research in natural language processing but ...
This paper presents a general method to automatically build large knowledge bases from online lexica...
AbstractIn the last two decades, WordNet has evolved as the most comprehensive computational lexicon...
This thesis investigates the possibility to exploit human language resources and knowledge extractio...
In this paper, we propose an extension of the WordNet conceptual model, with the final purpose of en...
The difficulties of navigating vocabulary in an assistive com-munication device are exacerbated for ...
A long time passed from the first word said by Homo sapiens to the first word said by a machine. The...
Because meaningful sentences are composed of meaningful words, any system that hopes to process natu...
Princeton WordNet is one of the most widely-used resources for natural language processing, but is u...
As part of a project to construct an interactive program which will encourage children to play with ...
The role of generic lexical resources as well as specialized terminology is crucial in the design of...
In this paper we present a linguistic resource for the lexical representation of affective knowledge...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
In this paper we present a proposal to extend WordNet-like lexical databases by adding information a...
WordNet is currently the most widely used lexicon resource for general English language. We here arg...
International audienceWordNet has facilitated important research in natural language processing but ...
This paper presents a general method to automatically build large knowledge bases from online lexica...
AbstractIn the last two decades, WordNet has evolved as the most comprehensive computational lexicon...