Structured distributional semantic models aim to improve upon simple vector space models of semantics by hypothesizing that the meaning of a word is captured more effectively through its relational — rather than its raw distributional — signature. In accordance, they extend the vector space paradigm by structuring elements with relational information that decompose distributional signatures ove...

The ability to mimic human notions of semantic distance has widespread applications. Some measures rely only on raw text (distributional measures) and some rely on knowledge sources such as WordNet. Although extensive studies have been performed to compare WordNet-based measures with human judgment, the use of distributional measures as proxies to estimate semantic distance has received little ...

In order to incorporate distributional concerns into cost-effectiveness analysis, it would be useful to elicit distributional weights that express people's valuation of marginal health gains at various levels of health. Distributional preferences are commonly elicited either through a person trade off (PTO) or a gain trade off (GTO) technique. An inherent problem of the GTO is that it is based ...

Distributional information has recently been implicated as playing an important role in several aspects of language ability. Learning the meaning of a word is thought to be dependent, at least in part, on exposure to the word in its linguistic contexts of use. In two experiments, we manipulated subjects’ contextual experience with marginally familiar and nonce words. Results showed that similar...

The analysis of federal regulations focuses on the analysis of economic efficiency through standard benefit-cost analysis in which reductions in risk tend to represent benefits and variability may be investigated through sensitivity or simulation methods. Such analyses typically ignore distributional consequences that can affect decisions. Although analytical guidance from the Office of Managem...

Several phonological and prosodic properties of words have been shown to relate to differences between grammatical categories. Distributional information about grammatical categories is also a rich source in the child's language environment. In this paper we hypothesise that such cues operate in tandem for developing the child's knowledge about grammatical categories. We term this the Phonologi...

The distributional form of the Maxwell-Vlasov equations are formulated. Submanifold distributions are analysed and the general submanifold distributional solutions to the Vlasov equations are given. The properties required so that these solutions can be a distributional source to Maxwell’s equations are analysed and it is shown that a sufficient condition is that spacetime be globally hyperboli...

The effects of orthographic neighborhood density and word frequency in visual word recognition were investigated using distributional analyses of response latencies in visual lexical decision. Main effects of density and frequency were observed in mean latencies. Distributional analyses additionally revealed a density × frequency interaction: for low-frequency words, density effects were mediat...

Computational work has suggested that one could, in principle, learn aspects of word meaning simply from patterns of co-occurrence between words. The extent to which humans can do this distributional learning is an open question – artificial language learning experiments have yielded mixed results, prompting suggestions that distributional cues must be correlated with other cues, such as phonol...

What makes some words easy for infants to recognize, and other words difficult? We addressed this issue in the context of prior results suggesting that infants have difficulty recognizing verbs relative to nouns. In this work, we highlight the role played by the distributional contexts in which nouns and verbs occur. Distributional statistics predict that English nouns should generally be easie...