146 resultados para Semantic Compatibility Index


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Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meaning in terms of undifferentiated bags of words or topical dimensions. This has led some to question their psychological plausibility (Murphy, 2002; Schunn, 1999). We present here a fully automatic method for extracting a structured and comprehensive set of concept descriptions directly from an English part-of-speech-tagged corpus. Concepts are characterized by weighted properties, enriched with concept-property types that approximate classical relations such as hypernymy and function. Our model outperforms comparable algorithms in cognitive tasks pertaining not only to concept-internal structures (discovering properties of concepts, grouping properties by property type) but also to inter-concept relations (clustering into superordinates), suggesting the empirical validity of the property-based approach. Copyright © 2009 Cognitive Science Society, Inc. All rights reserved.

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Achieving a clearer picture of categorial distinctions in the brain is essential for our understanding of the conceptual lexicon, but much more fine-grained investigations are required in order for this evidence to contribute to lexical research. Here we present a collection of advanced data-mining techniques that allows the category of individual concepts to be decoded from single trials of EEG data. Neural activity was recorded while participants silently named images of mammals and tools, and category could be detected in single trials with an accuracy well above chance, both when considering data from single participants, and when group-training across participants. By aggregating across all trials, single concepts could be correctly assigned to their category with an accuracy of 98%. The pattern of classifications made by the algorithm confirmed that the neural patterns identified are due to conceptual category, and not any of a series of processing-related confounds. The time intervals, frequency bands and scalp locations that proved most informative for prediction permit physiological interpretation: the widespread activation shortly after appearance of the stimulus (from 100. ms) is consistent both with accounts of multi-pass processing, and distributed representations of categories. These methods provide an alternative to fMRI for fine-grained, large-scale investigations of the conceptual lexicon. © 2010 Elsevier Inc.

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Many studies suggest a large capacity memory for briefly presented pictures of whole scenes. At the same time, visual working memory (WM) of scene elements is limited to only a few items. We examined the role of retroactive interference in limiting memory for visual details. Participants viewed a scene for 5?s and then, after a short delay containing either a blank screen or 10 distracter scenes, answered questions about the location, color, and identity of objects in the scene. We found that the influence of the distracters depended on whether they were from a similar semantic domain, such as "kitchen" or "airport." Increasing the number of similar scenes reduced, and eventually eliminated, memory for scene details. Although scene memory was firmly established over the initial study period, this memory was fragile and susceptible to interference. This may help to explain the discrepancy in the literature between studies showing limited visual WM and those showing a large capacity memory for scenes.

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In most previous research on distributional semantics, Vector Space Models (VSMs) of words are built either from topical information (e.g., documents in which a word is present), or from syntactic/semantic types of words (e.g., dependency parse links of a word in sentences), but not both. In this paper, we explore the utility of combining these two representations to build VSM for the task of semantic composition of adjective-noun phrases. Through extensive experiments on benchmark datasets, we find that even though a type-based VSM is effective for semantic composition, it is often outperformed by a VSM built using a combination of topic- and type-based statistics. We also introduce a new evaluation task wherein we predict the composed vector representation of a phrase from the brain activity of a human subject reading that phrase. We exploit a large syntactically parsed corpus of 16 billion tokens to build our VSMs, with vectors for both phrases and words, and make them publicly available.

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Endometrial cancer risk has been directly associated with glycemic load. However, few studies have investigated this link, and the etiological role of specific dietary carbohydrate components remains unclear. Our aim was to investigate associations of carbohydrate intake, glycemic index, and glycemic load with endometrial cancer risk in the US Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Recruitment took place in 1993-2001. Over a median of 9.0 years of follow-up through 2009, 386 women developed endometrial cancer among 36,115 considered in the analysis. Dietary intakes were assessed using a 124-item diet history questionnaire. Cox proportional hazards models were applied to calculate hazard ratios and 95% confidence intervals. Significant inverse associations were detected between endometrial cancer risk and total available carbohydrate intake (hazard ratio (HR) = 0.66, 95% confidence interval (CI): 0.49, 0.90), total sugars intake (HR = 0.71, 95% CI: 0.52, 0.96), and glycemic load (HR = 0.63, 95% CI: 0.46, 0.84) when women in the highest quartile of intake were compared with those in the lowest. These inverse associations were strongest among overweight and obese women. No associations with endometrial cancer risk were observed for glycemic index or dietary fiber. Our findings contrast with previous evidence and suggest that high carbohydrate intakes and glycemic loads are protective against endometrial cancer development. Further clarification of these associations is warranted.

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Obesity has consistently been linked to an increased risk of colorectal cancer, particularly among men. Whether body mass index (BMI) differentially influences the risk across the stages of colorectal cancer development remains unclear. We evaluated the associations of BMI with colorectal adenoma incidence, adenoma recurrence, and cancer in the context of a large screening trial, in which cases and controls had an equal chance for disease detection.

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Abstract Objective To determine if high umbilical artery Doppler (UAD) pulsatility index (PI) is associated with cardio-vascular (CV) risk-factors in children at age 12 years. Methods We studied 195 children at age 12 years who had had in-utero UAD studies performed at 28 weeks gestation. The children were grouped according to whether their umbilical Doppler PI was high (indicating poor feto-placental circulation) or normal. At age 12 years we assessed CV risk factors, including anthropometric measures, blood pressure, pulse wave velocity (a measure of arterial compliance), cardio-respiratory fitness and homocysteine and cholesterol serum levels. Results Compared with children with a normal UAD PI (N=88), the children (N=107) with high UAD PI had higher resting pulse rate (p=0.04), higher pulse wave velocity (p=0.046), higher serum homocysteine levels (p=0.032) and reduced arterial compliance (7.58 v 8.50 m/sec, p=0.029) using univariate analysis. These differences were not present when adjusting for cofounders was modelled. Conclusion High PI on UAD testing in-utero may be associated with increased likelihood of some cardio-vascular risk factors at age 12-years but confounding variables may be as important. Our study raises possible long-term benefits of in-utero UAD measurements.

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Intraspecific variation in gamete compatibility among male/female pairs causes variation in the concentration of sperm required to achieve equivalent fertilization levels. Gamete compatibility is therefore potentially an important factor controlling mating success. Many broadcast-spawning marine invertebrates, however, also live in a dynamic environment where hydrodynamic conditions can affect the concentration of sperm reaching eggs during spawning. Thus flow conditions may moderate the effects of gamete compatibility on fertilization. Using the green sea urchin Strongylocentrotus droebachiensis as a model system, we assessed the relative effects of gamete compatibility (the concentration of sperm required to fertilize 50% of the eggs in specific male/female pairs; F50) and the root-mean-square of total velocity (urms; 0.01-0.11 m s(-1)) on fertilization in four locations near a spawning female (water column, wake eddy, substratum, and aboral surface) in both unidirectional and oscillatory flows. Percent fertilization decreased significantly with increasing urms at all locations and both flow regimes. However, although gamete compatibility varied by almost 1.5 orders of magnitude, it was not a significant predictor of fertilization for most combinations of position and flow. The notable exception was a significant effect of gamete compatibility on fertilization on the aboral surface under unidirectional flow. Our results suggest that selection on variation in gamete compatibility may be strongest in eggs fertilized on the aboral surface of sea urchins and that hydrodynamic conditions may add environmental noise to selection outcomes.