[PDF] Top 20 A Compositional and Interpretable Semantic Space
Has 10000 "A Compositional and Interpretable Semantic Space" found on our website. Below are the top 20 most common "A Compositional and Interpretable Semantic Space".
A Compositional and Interpretable Semantic Space
... like a black box - it is unclear what VSM dimen- sions represent (save for broad classes of corpus statistic types) and what the application of a com- position function to those dimensions entails. Neu- ral network (NN) ... See full document
10
Compositional Matrix Space Models of Language
... A great variety of linguistic models are sub- sumed by this general idea ranging from purely symbolic approaches (like type systems and cate- gorial grammars) to rather statistical models (like vector space and ... See full document
10
Compositional Semantic Parsing on Semi Structured Tables
... Two important aspects of semantic pars- ing for question answering are the breadth of the knowledge source and the depth of logical compositionality. While existing work trades off one aspect for another, this ... See full document
11
Compositional Matrix Space Models for Sentiment Analysis
... explicitly compositional in nature. Thus, we can model the compositional effects required for accu- rate assignment of phrase-level ...multiplicative semantic effects. Although the ... See full document
11
Literal and Metaphorical Senses in Compositional Distributional Semantic Models
... like space, time, and number operate over a shared, generalized magnitude system, yet oth- ers maintain that our mental representation of time and number is distinct from our mental represen- tation of ... See full document
11
Compositional Vector Space Models for Knowledge Base Completion
... Better generalization can be gained by operat- ing on embedded vector representations of rela- tions, in which vector similarity can be interpreted as semantic similarity. For example, Bordes et al. (2013) learn ... See full document
11
Interpretable Semantic Vectors from a Joint Model of Brain and Text Based Meaning
... For a given value of ` we solve the NNSE(Text) and JNNSE(Brain+Text) objective function as de- tailed in Equation 1 and 4 respectively. We com- pared JNNSE(Brain+Text) and NNSE(Text) mod- els by measuring the correlation ... See full document
11
Learning Compositional Semantics for Open Domain Semantic Parsing
... new semantic representation, λ-inverse is no longer a ...Indeed, semantic graphs provide us with maximal freedom in breaking ...a semantic lexicon becomes ...partial semantic graphs, the ... See full document
18
The Role of Syntax in Vector Space Models of Compositional Semantics
... Recently those searching for the right represen- tation for compositional semantics have drawn in- spiration from the success of distributional mod- els of lexical semantics. This approach represents single words ... See full document
11
Distributional semantic phrases vs. semantic distributional nonsense: Adjective Modification in Compositional Distributional Semantics
... Color terms. This dataset is populated with a randomly selected set of adjective- noun pairs from the space presented above. From the 11 colors in the basic set proposed by Berlin & Kay (1969), we cover 7 ... See full document
129
Capturing Anomalies in the Choice of Content Words in Compositional Distributional Semantic Space
... answered. Compositional mod- els can be assessed by their ability both to provide a solid theoretical basis for meaning composition and to represent composite meaning for relevant practical ...and semantic ... See full document
8
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
... Note that this semantic correspondence permits a wide range of logical forms for each syntactic category. Each logical form can have an arbitrary functional form, as long as it has the correct se- mantic type. ... See full document
10
Interpretable and Compositional Relation Learning by Joint Training with an Autoencoder
... parameter space, such as constrain- ing that relations are translations (Bordes et ...with compositional constraints, because it is difficult to know a priori which two relations compose to which third ... See full document
12
Learning Effective and Interpretable Semantic Models using Non Negative Sparse Embedding
... the semantic features for those concepts, β is the vector of weights we must learn for each of those (corpus-derived) features, and λ tunes the degree of ...each semantic dimension, building a picture of ... See full document
18
Quantitative morphometric methods in diatom research
... Expressing allometric variation with respect to the comparison of forms as a latent variable originates from the work of Thompson (1917, 1942), and this basis is used in modern morphometrics (e.g., Adams et al. 2004). ... See full document
26
A Generalisation of Lexical Functions for Composition in Distributional Semantics
... Many researchers have already studied and evalu- ated different composition models within a distri- butional approach. One of the first studies eval- uating compositional phenomena in a systematic way is Mitchell ... See full document
11
Compositional Semantic Parsing across Graphbanks
... single semantic parser that does very well across all of DM, PAS, PSD, EDS and AMR (2015 and ...the compositional neural AMR parser of Groschwitz et ...its compositional tree structure and learns to ... See full document
10
Towards Compositional Tree Kernels
... similar syntactic structure. For example in the MSRvid dataset, a sentence pair is given by The man are playing soccer and A man is riding a mo- torcycle, that are strictly syntactically correlated. As a side effect, PTK ... See full document
9
PP 2015 06: Those Who Must Do It: the Agency of Language
... time, space, and computation, and increasingly, the study of information-‐driven agency, recorded in my Norwegian-‐length trilogy Exploring Logical Dynamics, Logical Dynamics of Information and Interaction, and ... See full document
15
Learning a Compositional Semantic Parser using an Existing Syntactic Parser
... a generative model with discriminative reranking. Note that some of these approaches require ad- ditional human supervision, knowledge, or engi- neered features that are unavailable to the other systems; namely, S CISSOR ... See full document
9
Related subjects