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High-dimensional distributed semantic spaces for utterances ...
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Abstract:
High-dimensional distributed semantic spaces have proven useful and effective for aggregating and processing visual, auditory, and lexical information for many tasks related to human-generated data. Human language makes use of a large and varying number of features, lexical and constructional items as well as contextual and discourse-specific data of various types, which all interact to represent various aspects of communicative information. Some of these features are mostly local and useful for the organisation of e.g. argument structure of a predication; others are persistent over the course of a discourse and necessary for achieving a reasonable level of understanding of the content. This paper describes a model for high-dimensional representation for utterance and text level data including features such as constructions or contextual data, based on a mathematically principled and behaviourally plausible approach to representing linguistic information. The implementation of the representation is a ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2104.00424 https://dx.doi.org/10.48550/arxiv.2104.00424
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How Lexical Gold Standards Have Effects On The Usefulness Of Text Analysis Tools For Digital Scholarship ...
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Text Mining for Processing Interview Data in Computational Social Science ...
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A proposal to use distributional models to analyse dolphin vocalization
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Semantic Space Models for Profiling Reputation of Corporate Entities
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CLEF 2012: Information Access meets Multilinguality, Multimodality, and Visual Analytics
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Report on the Fourth Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 11)
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Features for modelling characteristics of conversations : Notebook for PAN at CLEF 2012
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Profiling Reputation of Corporate Entities in Semantic Space : Notebook for RepLab at CLEF 2012
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Report on the Third Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR), Toronto, Canada
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