This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. They have been trained on pseudo-sentences generated artificially from a random walk over the English WordNet taxonomy, and thus reflect taxonomic knowledge about words (rather than contextual)
The techniques of using neural networks to learn distributed word representations (i.e., word embedd...
Word embeddings serve as an useful resource for many downstream natural language processing tasks. T...
In this paper we present two methodologies for rapidly inducing multiple subject-specific taxonomies...
This archive contains a collection of computational models called word embeddings. These are vectors...
This is a resource description paper that describes the creation and properties of a set of pseudo-c...
This archive contains a collection of computational models called word embeddings. These are vectors...
This archive contains a collection of pseudo-corpora. These are text files that contain pseudo-sente...
Word embeddings trained on natural corpora (e.g., newspaper collections, Wikipedia or the Web) excel...
Creating word embeddings that reflect semantic relationships encoded in lexical knowledge resources ...
The digital era floods us with an excessive amount of text data. To make sense of such data automati...
Research on word representation has always been an important area of interest in the antiquity of Na...
Word representation or word embedding is an important step in understanding languages. It maps simil...
The present paper intends to draw the conception of language implied in the technique of word embedd...
What is a word embedding? Suppose you have a dictionary of words. The i th word in the dictionary is...
Real-valued word embeddings have transformed natural language processing (NLP) applications, recogni...
The techniques of using neural networks to learn distributed word representations (i.e., word embedd...
Word embeddings serve as an useful resource for many downstream natural language processing tasks. T...
In this paper we present two methodologies for rapidly inducing multiple subject-specific taxonomies...
This archive contains a collection of computational models called word embeddings. These are vectors...
This is a resource description paper that describes the creation and properties of a set of pseudo-c...
This archive contains a collection of computational models called word embeddings. These are vectors...
This archive contains a collection of pseudo-corpora. These are text files that contain pseudo-sente...
Word embeddings trained on natural corpora (e.g., newspaper collections, Wikipedia or the Web) excel...
Creating word embeddings that reflect semantic relationships encoded in lexical knowledge resources ...
The digital era floods us with an excessive amount of text data. To make sense of such data automati...
Research on word representation has always been an important area of interest in the antiquity of Na...
Word representation or word embedding is an important step in understanding languages. It maps simil...
The present paper intends to draw the conception of language implied in the technique of word embedd...
What is a word embedding? Suppose you have a dictionary of words. The i th word in the dictionary is...
Real-valued word embeddings have transformed natural language processing (NLP) applications, recogni...
The techniques of using neural networks to learn distributed word representations (i.e., word embedd...
Word embeddings serve as an useful resource for many downstream natural language processing tasks. T...
In this paper we present two methodologies for rapidly inducing multiple subject-specific taxonomies...