WORD SIMILARITY FROM DICTIONARIES: INFERRING FUZZY MEASURES FROM FUZZY GRAPHS The computation of similarities between words is a basic element of information retrieval systems, when retrieval is not solely based on word matching. In this work we consider a measure between words based on dictionaries. This is achieved assuming that a dictionary is formalized as a fuzzy graph. We show that the approach permits to compute measures not only for pairs of words but for sets of them
Abstract—In this paper we explore the practical application of the previously introduced approach [1...
Many systems for tasks such as question answering, multi-document summarization, and information ret...
This paper describes an unsupervised graph-based method for word sense disambiguation, and presents ...
The computation of similarities between words is a basic element of information retrieval systems, w...
The computation of similarities between words is a basic element of information retrieval systems, w...
In this paper we present a hybrid measure of semantic word similarity using fuzzy inference system w...
Top-k words selection is a technique used to detect and return the k most similar words to a given w...
Word similarity is a semantic measure that evaluates the similarity of words. The goal of the master...
Short text semantic similarity (STSS) measures are algorithms designed to compare short texts and re...
Sentence similarity measures the similarity between two blocks of text. A semantic similarity measur...
AbstractMany measures of similarity among fuzzy sets have been proposed in the literature, and some ...
Human language is naturally fuzzy by nature, with words meaning different things to different people...
Understanding concepts expressed in natural language is a challenge in Natural Language Processing a...
Many measures of similarity among fuzzy sets have been proposed in the literature, and some have bee...
Fuzzy sentence semantic similarity measures are designed to be applied to real world problems where ...
Abstract—In this paper we explore the practical application of the previously introduced approach [1...
Many systems for tasks such as question answering, multi-document summarization, and information ret...
This paper describes an unsupervised graph-based method for word sense disambiguation, and presents ...
The computation of similarities between words is a basic element of information retrieval systems, w...
The computation of similarities between words is a basic element of information retrieval systems, w...
In this paper we present a hybrid measure of semantic word similarity using fuzzy inference system w...
Top-k words selection is a technique used to detect and return the k most similar words to a given w...
Word similarity is a semantic measure that evaluates the similarity of words. The goal of the master...
Short text semantic similarity (STSS) measures are algorithms designed to compare short texts and re...
Sentence similarity measures the similarity between two blocks of text. A semantic similarity measur...
AbstractMany measures of similarity among fuzzy sets have been proposed in the literature, and some ...
Human language is naturally fuzzy by nature, with words meaning different things to different people...
Understanding concepts expressed in natural language is a challenge in Natural Language Processing a...
Many measures of similarity among fuzzy sets have been proposed in the literature, and some have bee...
Fuzzy sentence semantic similarity measures are designed to be applied to real world problems where ...
Abstract—In this paper we explore the practical application of the previously introduced approach [1...
Many systems for tasks such as question answering, multi-document summarization, and information ret...
This paper describes an unsupervised graph-based method for word sense disambiguation, and presents ...