[PDF] Top 20 A Regression Model of Adjective Noun Compositionality in Distributional Semantics

... We use a general-purpose vector space extracted from the British National Corpus. We used the Infomap software to collect co-occurrence statis- tics for lemmas within a rectangular 5L–5R win- dow. The corpus was ... See full document

... to semantics (sometimes called distribu- tional semantics ) naturally captures collocations, scales well to large lexicons and does not require words to be manually disambiguated (Sch¨ utze, ...of ... See full document

... graded compositionality for phrases per se that occur in three types of grammatical relations: adjective-noun pairs, subject-verb and verb-object pairs in English and ... See full document

... Prior proposals have rarely analysed content word errors from a semantic perspective. K&B have focused on ED for AN phrases and shown that approaches aimed at detecting semantic deviance can also identify errors in ... See full document

... this model by proposing to represent each node in a parse tree by a vector capturing the meaning and a matrix capturing the compositional ...to model subject-verb-object triples based on tensor ... See full document

... from adjective-noun ...vs. distributional count models) as well as a learned compositionality function based on a full additive model capitalizing on weight matrices for balancing the ... See full document

... I model the semantic composition of adjacent Adjective-Noun pairs expressing attributive modification of a nominal ...also model the syntactic relation between adjacent Verb-Noun ... See full document

... Distributional semantics. We observe two re- cent trends in distributional semantics research: (i) The use of VSM tends to shift from mea- suring unfocused semantic similarity to captur- ing ... See full document

... Ridge Regression is only one of of many estimation techniques that could be tried to come up with better matrix and tensor ...the model is clearly motivated as an instantiation of the vector-space “dual” of ... See full document

... years, distributional models have been extended to handle the semantic composition of words into phrases and longer constituents (Baroni and Zamparelli 2010; Mitchell and Lapata 2010; Socher et ...Formal ... See full document

... The following example, which uses actual corpus data, illustrates how the approach works. Say we want to compute the distributionally similar words to the noun de- vice in the context of example expressions ... See full document

... A native speaker of English and linguist evaluated the quality of the nearest neighbors of frequent versus (relatively) rare phrases, comparing the lexical function model and the observed data. As frequent ... See full document

... In this paper we present a study cover- ing the creation of compositional distri- butional representations for English noun compounds (e.g. computer science) using two compositional models proposed in the ... See full document

... certainty, CLF classifier, COLL collective, DR ‘derivational’, DES desiderative, ENDEAR endearment (term), EMPH emphatic, E oblique core argument, EVENT event (nominalisation), F feminine, G general, GR group, GEN ... See full document

... Each compound phrase in the selected list is an- notated by two experts according to the following schema: (0) the phrase is non-compositional; (1) the phrase is compositional; (2) the phrase is am- biguous, which means ... See full document

... The refined corpus is one of the largest available datasets for sounds and the only dataset with adjective-noun and verb-noun labels. The ANPs and VNPs are weak labels based on the collaborative ... See full document

... structured distributional context) with values weighted by their scaled similarities to words (or effectively word-dimensions) that actu- ally occur in the syntactic ... See full document

... the distributional semantic models framework, fol- lowing the assumption that tokens that occur in similar context tend to be semantically related (Harris, ... See full document

... In this paper, we categorically propose an un- supervised framework for metaphor detection wi- thout using any hand-coded knowledge, making it robust to scale and adaptive to language change. Using the ... See full document

... the semantics associated with the statistical analysis of spatial ...of regression models and, therefore, the meaning of predicted y, are shown to vary due to (1) choices about data: the specification of x ... See full document