Cognitively Motivated Distributional Representations of Meaning
نویسندگان
چکیده
Although meaning is at the core of human cognition, state-of-the-art distributional semantic models (DSMs) are often agnostic to the findings in the area of semantic cognition. In this work, we present a novel type of DSMs motivated by the dual–processing cognitive perspective that is triggered by lexico–semantic activations in the short–term human memory. The proposed model is shown to perform better than state-of-the-art models for computing semantic similarity between words. The fusion of different types of DSMs is also investigated achieving results that are comparable or better than the state-of-the-art. The used corpora along with a set of tools, as well as large repositories of vectorial word representations are made publicly available for four languages (English, German, Italian, and
منابع مشابه
Of Words, Eyes and Brains: Correlating Image-Based Distributional Semantic Models with Neural Representations of Concepts
Traditional distributional semantic models extract word meaning representations from cooccurrence patterns of words in text corpora. Recently, the distributional approach has been extended to models that record the cooccurrence of words with visual features in image collections. These image-based models should be complementary to text-based ones, providing a more cognitively plausible view of m...
متن کاملDistributional Semantic Models
Distributional semantic models (DSM) -also known as "word space" or "distributional similarity" models -are based on the assumption that the meaning of a word can (at least to a certain extent) be inferred from its usage, i.e. its distribution in text. Therefore, these models dynamically build semantic representations -in the form of highdimensional vector spaces -through a statistical analysis...
متن کاملImproving Vector Space Word Representations Using Multilingual Correlation
The distributional hypothesis of Harris (1954), according to which the meaning of words is evidenced by the contexts they occur in, has motivated several effective techniques for obtaining vector space semantic representations of words using unannotated text corpora. This paper argues that lexico-semantic content should additionally be invariant across languages and proposes a simple technique ...
متن کاملSentential Representations in Distributional Semantics
This thesis is about the problem of representing sentential meaning in distributional semantics. Distributional semantics obtains the meanings of words through their usage, based on the hypothesis that words occurring in similar contexts will have similar meanings. In this framework, words are modeled as distributions over contexts and are represented as vectors in high dimensional space. Compo...
متن کاملTowards a semantics for distributional representations
Distributional representations have recently been proposed as a general-purpose representation of natural language meaning, to replace logical form. There is, however, one important difference between logical and distributional representations: Logical languages have a clear semantics, while distributional representations do not. In this paper, we propose a semantics for distributional represen...
متن کامل