[PDF] Top 20 Distributional Semantics in Use

... Distributional semantics has revolutionised com- putational semantics by representing the meaning of linguistic expressions as vectors that capture their co-occurrence patterns in large corpora (Tur- ... See full document

... In order to determine the usefulness of the wordspace package for realistically sized data sets, a benchmark was carried out using the W × W projection of the Distributional Memory tensor (Baroni and Lenci, 2010), ... See full document

... to use corpus-extracted example vectors of both the input (typically, words) and output elements (typically, phrases) in order to op- timize the composition operation ... See full document

... Distributional semantics (Turney and Pantel, 2010) builds on the assumption that the semantic similar- ity of words is strongly correlated to the overlap between their linguistic ... See full document

... In this work, we propose a vector-space model which provides a formal foundation for a distri- butional semantics of entailment. We developed a mean-field approximation to probabilistic entail- ment between ... See full document

... models use large text cor- pora to derive estimates of semantic similarities be- tween ...whether distributional semantic models are also reflecting human cogni- tive processes (Griffiths et ... See full document

... on distributional semantics and compositionality as well as for those interested in extracting non-compositional phrases from large corpora by applying distributional methods that assign a graded ... See full document

... they use Wikipedia as a training corpus and a more sophisticated version of the NLM presented here, that takes into account global context and performs word sense discrimi- ... See full document

... a distributional semantic model on the enriched text (corresponding to (2) in the example above) and for comparison also on the original raw text (corre- sponding to ...we use the Skip-gram model from the ... See full document

... of distributional semantics methods, we decided to use the same corpora as used in pre- vious work for the inspected compound splitters (Ziering and Van der Plas, ...(i.e., distributional ... See full document

... the distributional hypothesis which states that words with similar meanings tend to occur in similar context (Harris, ...a distributional semantic model (Pad´o and Lapata, 2003; Turney and Pantel, ... See full document

... 2005) use wordnet similarity to classify a set of 2169 com- pounds into 20 semantic categories, achieving 53% ...2010) use a dataset of 17509 compounds and a maximum en- tropy classifier to achieve ... See full document

... We present an approach to track how words change their dominant meaning depending on the partic- ular text register in which they are used. A typical example is the English word ‘cup’ denoting mostly mugs in the fiction ... See full document

... to use the cues we proposed as features to train a classifier to predict the preferred order of adjectives, to be tested also in cases where neither order is found in the corpus, so direct corpus evidence cannot ... 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

... basing semantics on sampling language use—a position embraced by distributional ...a semantics driven by the ...a semantics based on the DH suffers from shortcomings with respect to ... See full document

... to distributional semantics, especially with respect to particular categories of phrase ...that distributional se- mantic representations might play in the production of a model of a ...on ... See full document

... Even when controlling for speaker identity there are still superficial features of the speech signal which make it easy for the model to ignore the se- mantic content. Some of these may be due to arti- facts in datasets ... See full document

... full use of the tensor product space; only tensor products are used, not sums of tensor products, giving us the equivalent of the product states of quantum ... See full document

... to use a compound classification algorithm on the ...a distributional model of AB semantic transparency, the vector for A should be given more weighting than the vector for ... See full document