Brent Kievit-Kylar

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Here we describe the Semantic Pictionary Project—a set of online games and tools designed to collect large amounts of structured data about the object characteristics and perceptual properties of word referents. The project hinges on the use of encoding-decoding games and a set of creation tools to capture data using online crowdsourcing. We describe the(More)
Semantic models play an important role in cognitive science. These models use statistical learning to model word meanings from co-occurrences in text corpora. A wide variety of semantic models have been proposed, and the literature has typically emphasized situations in which one model outperforms another. However, because these models often vary with(More)
We describe a model designed to learn word-concept pairings using a combination of semantic space models. We compare various semantic space models to each other as well as to extant word-learning models in the literature and find that not only do semantic space models require fewer underlying assumptions, they perform at least on par with existing(More)
The registration, transfer, clearing and settlement of equities represents a significant part of economic activity currently underserved by modern technological innovation. In addition, recent events have revealed problems of transparency, inviting public criticism and scrutiny from regulatory authorities. A peer-to-peer platform facilitating the creation(More)
In this paper we explore the application of a novel data collection scheme for multi-sensory information to the question of whether different sensory domains tend to show similar relations between objects (along with some unique variance). Our analyses—hierarchical clustering, MDS mapping, and other comparisons between sensory domains— support the existence(More)
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