Add to ORKGAbstract. In this paper, we propose a new methodology based on directed graphs and the TextRank algorithm to automatically induce general-specific noun relations from web corpora frequency counts. Different asymmetric association measures are implemented to build the graphs upon which the TextRank algorithm is applied and produces an ordered list of nouns from the most general to the most specific. Experiments are conducted based on the WordNet noun hierarchy and both quantitative and qualitative evaluations are proposed.
For our system we use the SMO implementation of a support vector machine provided with the WEKA mac...
Collections of relational paraphrases have been automatically constructed from \u000Alarge text corp...
Word similarity is a semantic measure that evaluates the similarity of words. The goal of the master...
In this paper, we propose a new methodology based on directed weighted graphs and the TextRank algor...
In this paper, we propose a new metho-dology based on directed graphs and the TextRank algorithm to ...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
Text mining process proceeds in different directions where key word identification is the core compo...
This study investigated the use of the lexical database WordNet to solve vocabulary matching quizzes...
Collections of relational paraphrases have been automatically constructed from large text cor-pora, ...
Current WordNet-based measures of distance or similarity focus almost exclusively on WordNet's ...
This article presents and evaluates a model to automatically derive word association networks from t...
We address the problem of automatic classification of associative and semantic relations between wor...
Graph-based similarity over WordNet has been previously shown to perform very well on word similarit...
The method of organization of word mean-ings is a crucial issue with lexical databases. Our purpose ...
Many systems for tasks such as question answering, multi-document summarization, and information ret...
For our system we use the SMO implementation of a support vector machine provided with the WEKA mac...
Collections of relational paraphrases have been automatically constructed from \u000Alarge text corp...
Word similarity is a semantic measure that evaluates the similarity of words. The goal of the master...
In this paper, we propose a new methodology based on directed weighted graphs and the TextRank algor...
In this paper, we propose a new metho-dology based on directed graphs and the TextRank algorithm to ...
Lexical databases following the wordnet paradigm capture information about words, word senses, and t...
Text mining process proceeds in different directions where key word identification is the core compo...
This study investigated the use of the lexical database WordNet to solve vocabulary matching quizzes...
Collections of relational paraphrases have been automatically constructed from large text cor-pora, ...
Current WordNet-based measures of distance or similarity focus almost exclusively on WordNet's ...
This article presents and evaluates a model to automatically derive word association networks from t...
We address the problem of automatic classification of associative and semantic relations between wor...
Graph-based similarity over WordNet has been previously shown to perform very well on word similarit...
The method of organization of word mean-ings is a crucial issue with lexical databases. Our purpose ...
Many systems for tasks such as question answering, multi-document summarization, and information ret...
For our system we use the SMO implementation of a support vector machine provided with the WEKA mac...
Collections of relational paraphrases have been automatically constructed from \u000Alarge text corp...
Word similarity is a semantic measure that evaluates the similarity of words. The goal of the master...