[PDF] Top 20 Representing Meaning with a Combination of Logical and Distributional Models
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Representing Meaning with a Combination of Logical and Distributional Models
... only on individual word pairs, this technique would use distributional similarity to learn the meaning of unknown terms, given that many other terms are already known. This article has focused on the RTE ... See full document
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MoL 2014 22: Categorical Foundations for Extended Compositional Distributional Models of Meaning
... associate logical derivations with terms of the lambda calculus, hence the slogan ‘proofs as ...the meaning of a complex expression is to be computed out of the meaning of its constituent ...semantic ... See full document
139
There Is No Logical Negation Here, But There Are Alternatives: Modeling Conversational Negation with Distributional Semantics
... DS models based on narrower contexts, which are known to produce similarity estimates that are more ontologically tight, and less broadly topic-based (Sahlgren ...corpus-based distributional model is ... See full document
24
Modeling covert event retrieval in logical metonymy: probabilistic and distributional accounts
... We evaluate the probabilistic models (Sec. 2) and the similarity-based models (Sec. 3) on a dataset con- structed from two German psycholinguistic studies on logical metonymy. One study used ... See full document
10
MoL 2017 16: Not logical: A distributional semantic account of negated adjectives
... word meaning and its negated version not to share any feature, and hence model the latter as the orthogonal vector to the ...matrix representing not as a mapping between the vectors of two antonyms, and to ... See full document
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Experimental Support for a Categorical Compositional Distributional Model of Meaning
... into logical formulae, then use computer-aided automation tools to reason about them (Alshawi, ...the meaning of a sentence, and says nothing about the closeness in meaning or topic of expressions ... See full document
11
Cognitively Motivated Distributional Representations of Meaning
... for representing the semantics of two-word phrases divided in three cat- egories, namely, noun-noun (NN), adjective-noun (AN), and verb-object ...distinct models are built, namely, domain and function ... See full document
7
The Meaning of UML Models
... a logical model of the ...nodes representing system states and edges representing ...UML models by deriving a structure from the prescriptive parts (StateMachines, Activities), and formulae ... See full document
205
Towards a Matrix based Distributional Model of Meaning
... vector-based models, we suggest a novel distributional paradigm for representing text in that we introduce a further dimension into a “standard” two-dimensional word space ... See full document
6
Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning
... Domains and Functions. In recent work, Turney (2012) suggests modeling word repre- sentations not as a single semantic vector, but as a pair of vectors: one containing the information of the word relative to its domain ... See full document
48
Combined Distributional and Logical Semantics
... of distributional and formal logical semantics. Distributional models have been successful in modelling the meanings of content words, but logical se- mantics is necessary to adequately ... See full document
14
Concrete Sentence Spaces for Compositional Distributional Models of Meaning
... compositional distributional model of meaning, based on the intuition that syntactic analysis guides the semantic vector ...a meaning vector in the space corresponding to its type. The meaning ... See full document
10
Squibs: When the Whole Is Not Greater Than the Combination of Its Parts: A “Decompositional” Look at Compositional Distributional Semantics
... compositional distributional semantic models (CDSMs) estimate degrees of seman- tic similarity (or, more generally, relatedness) between two phrases: A good CDSM might tell us that green bird is closer to ... See full document
10
Quantifiers: Experimenting with Higher Order Meaning in Distributional Semantic Space
... Integral to the discussion here, as well as the “tripartite representation” of meaning in Her- mann et al. (2013), is the concept of a dual- space representation similar to those of Tur- ney (2012). A dual-space ... See full document
5
Logical openness in Cognitive Models
... with logical openness and able, by means of intrinsic emergence processes, to produce new codes which lead the system in building world representations centered on its ... See full document
15
Short Term Meaning Shift: A Distributional Exploration
... a distributional model to capture these phenomena, which is what we do in this paper for short-term meaning ...consider meaning shift in short time periods on Twitter data, but without providing an ... See full document
7
Deep Neural Models of Semantic Shift
... Although this evaluation provides useful infor- mation on the quality of an diachronic distribu- tional model, it has some weaknesses. The first is that it is a synthetic task that operates on synthetic words. Thus, we ... See full document
11
Sound based distributional models
... or combination of features in the future (see Breebaart & McKinney 2004 for a ...Mixture Models and Fisher encoding (also used successfully by Bruni et ... See full document
6
Inference with Distributional Semantic Models
... We use count models to produce our distributional vectors because their determinis- tic training procedure makes it easier to train compositional models. We extract co- occurrence information from a ... See full document
73
Extracting Logical Formulae that Capture the Functionality of SystemC Designs
... Inferred logical properties representing a sound abstraction of the system behavior are still general enough to be translated into an ad-hoc representation for a wide range of tools in order to verify ... See full document
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