Vector-based models of word meaning have become increasingly popular in cognitive science. The appeal of these models lies in their ability to represent meaning simply by using distributional information under the assumption that words occurring within similar contexts are semantically similar. Despite their widespread use, vector-based models are typically directed at representing words in isolation, and methods for constructing representations for phrases or sentences have received little attention in the literature. This is in marked contrast to experimental evidence (e.g., in (...) sentential priming) suggesting that semantic similarity is more complex than simply a relation between isolated words. This article proposes a framework for representing the meaning of word combinations in vector space. Central to our approach is vector composition, which we operationalize in terms of additive and multiplicative functions. Under this framework, we introduce a wide range of composition models that we evaluate empirically on a phrase similarity task. (shrink)

I have two goals in this paper. First, I want to show by example that inferences about theoretical entities are relatively contingent affairs. Previously accepted conceptual metaphors in science set both the general form of new theories and our acceptance of the theories as plausible. In addition, they determine how we define the relevant parameters in investigating phenomena in the first place. These items then determine how we conceptualize things in the world. Second, and maybe more importantly, I want to (...) solve a puzzle that falls out of our current explication of attention, namely why we have it. Given the now widely accepted view that our brains are massively parallel, it is difficult to see why we should have evolved attentional mechanisms at all. Why gate when we can already process what we transduce in parallel? Here I answer that puzzle and suggest a perspective on attention that makes it a bit easier to understand, although this perspective also entails that we have to revise how we individuate experimental protocols and relevant data. (shrink)

Reingold, Reichle, Glaholt, and Sheridan reported a gaze-contingent eye-movement experiment in which survival-curve analyses were used to examine the effects of word frequency, the availability of parafoveal preview, and initial fixation location on the time course of lexical processing. The key results of these analyses suggest that lexical processing begins very rapidly and is supported by substantial parafoveal processing. Because it is not immediately obvious that these results are congruent with the theoretical assumption that words are processed and identified in (...) a strictly serial manner, we attempted to simulate the experiment using the E-Z Reader model of eye-movement control. These simulations were largely consistent with the empirical results, suggesting that parafoveal processing does play an important functional role by allowing lexical processing to occur rapidly enough to mediate direct control over when the eyes move during reading. (shrink)