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...

Distributional semantic models (DSMs) are semantic models which are based on the statistical analysis of co-occurrences of words in large corpora. DSMs can be used in a wide spectrum of semantic applications including semantic search, question answering, paraphrase detection, word sense disambiguation, among others. The ability to automatically harvest meaning from unstructured heterogeneous da...

Opportunities for associationist learning of word meaning, where a word is heard or read contemperaneously with information being available on its meaning, are considered too infrequent to account for the rate of language acquisition in children. It has been suggested that additional learning could occur in a distributional mode, where information is gleaned from the distributional statistics (...

nowadays, organizations are required to continually find new ways to grow in response to constantly changing challenges. in today’s dynamic work place, successful organizations need employees who do more than their role requirements. employees who perceive unfairness might lessen their extra-role behavior, while on the other hand employees who perceive fairness would want to contribute more to ...

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...