[PDF] Top 20 Sentential Representations in Distributional Semantics

... I extracted distributional semantic vectors using as source corpus the concatenation of ukWaC, Wikipedia (2009 dump) and BNC, 2.8 billion tokens in total. 4 I use a bag-of- words approach and I count ... See full document

... of Distributional Semantics and supervised Machine ...brief, distributional semantic spaces containing representations for complex constructions such as Adjective-Noun and Verb-Noun pairs, as ... See full document

... One might argue that the concerns about DSMs not being grounded or em- bodied are exaggerated, because they overlook the fact that the patterns of lin- guistic co-occurrence exploited by DSMs reflect semantic knowledge ... See full document

... years, distributional semantics models (DSMs) (Erk, 2012; Clark, 2012; Turney and Pantel, 2010) have received close attention from the linguistic ...excellent representations of lexical meaning, ... See full document

... tributed representations that encode fea- tures that are predictive with respect to id- iom token ...these representations have competitive performance compared with the state of the art in idiom token ... See full document

... a distributional semantics space to some heavily underspecified form of a “model-theoretic” space (Herbelot and Vecchi 2015); (c) a function from sentences in a discourse to other sentences in the same ... See full document

... image-based representations to favour (not surprisingly!) highly visual properties such as colours and shapes, ...develop distributional models that come with more well-rounded charac- terizations of the ... See full document

... where x, y, z ∈ A and α, β ∈ R . It is assumed that the multiplication is associative, but not commutative. The resulting structure is an associative algebra over a field — or simply an algebra when there is no ... See full document

... sparse representations have been shown to be beneficial in NLP, both for ap- plications and for interpretability of features (Mur- phy et ...sparse representations, we also assume that all link weights are ... See full document

... Distributional semantics creates vector- space representations that capture many forms of semantic similarity, but their re- lation to semantic entailment has been less ...a distributional ... See full document

... smaller, dense structures, for which sparse rep- resentations are not optimal. This is our motiva- tion for supporting both dense and sparse repre- sentations. The choice of dense vs. sparse is ini- tially determined by ... See full document

... After loading the package (line 1), we use a standard R function to extract data for the written part of the BNC (line 3). The dsm() function constructs a basic DSM object from co-occurrence data in various sparse matrix ... See full document

... Flickr8K Initial experiments with Flickr8K were similarly unsuccessful. Analysis of the learned SegMatch representations revealed that in spite of partitioning the data by speaker for train- ing, speaker identity ... See full document

... Standardly, distributional models are con- structed from large amounts of data in batch mode by aggregating information into a vector that syn- thesises the general distributional meaning of an ...recent ... See full document

... and Distributional Semantics Logic is necessary for implementing the functional aspects of meaning and organizing knowledge in a struc- tured and unambiguous ...butional semantics provides an elegant ... See full document

... producing representations of propositionally typed phrases, it is not a nec- essary condition for a semantic ...the representations of syntactically differ- ent phrases with the same ... See full document

... the representations of bilingual lexical and sentential semantics, we propose an approach to capture the mapping from the defini- tions to the corresponding foreign words by lever- aging bilingual ... See full document

... nificantly better than stem (p < .001). Lexfunc provides a flexible way to account for affixation, since it models it directly as a function mapping from and onto word vectors, without requiring a vector ... See full document

... between distributional representations and the semantics of logical ...using distributional representations as inten- sions of logical ...the distributional representation for ... See full document

... This intuition is backed by a manual analysis we conducted on 100 random errors not made by the baseline. When examining each of the system’s antecedent decisions and their weights, we found that 23% of the wrong links ... See full document