This paper develops and evaluates an enhanced corpus based approach for semantic processing. Corpus based models that build representations of words directly from text do not require pre-existing linguistic knowledge, and have demonstrated psychologically relevant performance on a number of cognitive tasks. However, they have been criticised in the past for not incorporating sufficient structural information.\ud \ud Using ideas underpinning recent attempts to overcome this weakness, we develop an enhanced tensor encoding model to build representations of word meaning for semantic processing. Our enhanced model demonstrates superior performance when compared to a robust baseline model on a number of semantic processing tasks
Objective Semantic concepts are coherent entities within our minds. They underpin our thought proces...
This tutorial presents a corpus-driven, pattern-based empirical approach to meaning representation a...
Comunicació presentada a: 2009 Conference on Empirical Methods in Natural Language Processing celebr...
Models of word meaning, built from a corpus of text, have demonstrated success in emulating human pe...
Vector space models (VSMs) represent word meanings as points in a high dimen-sional space. VSMs are ...
One of the most significant recent advances in the study of semantic processing is the advent of mod...
One of the most significant recent advances in the study of semantic processing is the advent of mod...
In order to describe how humans represent meaning in the brain, one must be able to account for not ...
Rich semantic representations of linguistic data are an essential component to the development of ma...
The semantic concept processing mechanism of the brain shows that different neural activity patterns...
In the literature, tensors have been effectively used for capturing the context information in langu...
This paper investigates the learning of 3rd-order tensors representing the seman-tics of transitive ...
How is semantic information stored in the human mind and brain? Some philosophers and cognitive scie...
Important advances have recently been made using computational semantic models to decode brain activ...
Motivated by the widespread use of distributional models of semantics within the cognitive science c...
Objective Semantic concepts are coherent entities within our minds. They underpin our thought proces...
This tutorial presents a corpus-driven, pattern-based empirical approach to meaning representation a...
Comunicació presentada a: 2009 Conference on Empirical Methods in Natural Language Processing celebr...
Models of word meaning, built from a corpus of text, have demonstrated success in emulating human pe...
Vector space models (VSMs) represent word meanings as points in a high dimen-sional space. VSMs are ...
One of the most significant recent advances in the study of semantic processing is the advent of mod...
One of the most significant recent advances in the study of semantic processing is the advent of mod...
In order to describe how humans represent meaning in the brain, one must be able to account for not ...
Rich semantic representations of linguistic data are an essential component to the development of ma...
The semantic concept processing mechanism of the brain shows that different neural activity patterns...
In the literature, tensors have been effectively used for capturing the context information in langu...
This paper investigates the learning of 3rd-order tensors representing the seman-tics of transitive ...
How is semantic information stored in the human mind and brain? Some philosophers and cognitive scie...
Important advances have recently been made using computational semantic models to decode brain activ...
Motivated by the widespread use of distributional models of semantics within the cognitive science c...
Objective Semantic concepts are coherent entities within our minds. They underpin our thought proces...
This tutorial presents a corpus-driven, pattern-based empirical approach to meaning representation a...
Comunicació presentada a: 2009 Conference on Empirical Methods in Natural Language Processing celebr...