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111.
112.
This paper presents a new procedure called TREEFAM for estimating ultrametric tree structures from proximity data confounded by differential stimulus familiarity. The objective of the proposed TREEFAM procedure is to quantitatively filter out the effects of stimulus unfamiliarity in the estimation of an ultrametric tree. A conditional, alternating maximum likelihood procedure is formulated to simultaneously estimate an ultrametric tree, under the unobserved condition of complete stimulus familiarity, and subject-specific parameters capturing the adjustments due to differential unfamiliarity. We demonstrate the performance of the TREEFAM procedure under a variety of alternative conditions via a modest Monte Carlo experimental study. An empirical application provides evidence that the TREEFAM outperforms traditional models that ignore the effects of unfamiliarity in terms of superior tree recovery and overall goodness-of-fit. 相似文献
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114.
优、差生组织策略水平的比较研究 总被引:2,自引:0,他引:2
本文比较了初一年级优、差生在词表记忆中的组织策略水平的差异,结果表明:1、初一年级优、差生都还没能自发地运用组织策略,优生只在非典型项目的记忆中群集水平明显优于差生,优、差生的群集水平和记忆成绩之间不存在一一对应的关系。2、在典型或非典型项目的记忆中,记忆成绩和知识背景都有着非常显著的正相关。 相似文献
115.
Debra L. Franko 《Group》1997,21(1):39-45
Although group therapy is often recommended for the treatment of bulimia nervosa, relatively little is known about predictors
of short-term outcome. This pilot study examined whether a standardized measure of readiness for change might be related to
changes in binge frequency. Sixteen bulimic patients participated in short-term cognitive behavioral group therapy for twelve
weeks. Each patient completed the Change Assessment Scale prior to treatment, along with a battery of symptom measures which
were readministered at the conclusion of therapy. Bulimic patients with positive outcome in binge frequency were at a higher
stage of readiness for change at pretreatment than were patients with negative outcome. Results indicated that there may be
methods of determining who would be most likely to benefit from cognitive behavioral group therapy, and tentatively suggest
that interventions may be more successful when readiness for change is taken into consideration. 相似文献
116.
Cluster differences scaling with a within-clusters loss component and a fuzzy successive approximation strategy to avoid local minima 总被引:2,自引:0,他引:2
Cluster differences scaling is a method for partitioning a set of objects into classes and simultaneously finding a low-dimensional spatial representation ofK cluster points, to model a given square table of dissimilarities amongn stimuli or objects. The least squares loss function of cluster differences scaling, originally defined only on the residuals of pairs of objects that are allocated to different clusters, is extended with a loss component for pairs that are allocated to the same cluster. It is shown that this extension makes the method equivalent to multidimensional scaling with cluster constraints on the coordinates. A decomposition of the sum of squared dissimilarities into contributions from several sources of variation is described, including the appropriate degrees of freedom for each source. After developing a convergent algorithm for fitting the cluster differences model, it is argued that the individual objects and the cluster locations can be jointly displayed in a configuration obtained as a by-product of the optimization. Finally, the paper introduces a fuzzy version of the loss function, which can be used in a successive approximation strategy for avoiding local minima. A simulation study demonstrates that this strategy significantly outperforms two other well-known initialization strategies, and that it has a success rate of 92 out of 100 in attaining the global minimum. 相似文献
117.
118.
Spatial versus tree representations of proximity data 总被引:2,自引:0,他引:2
In this paper we investigated two of the most common representations of proximities, two-dimensional euclidean planes and additive trees. Our purpose was to develop guidelines for comparing these representations, and to discover properties that could help diagnose which representation is more appropriate for a given set of data. In a simulation study, artificial data generated either by a plane or by a tree were scaled using procedures for fitting either a plane (KYST) or a tree (ADDTREE). As expected, the appropriate model fit the data better than the inappropriate model for all noise levels. Furthermore, the two models were roughly comparable: for all noise levels, KYST accounted for plane data about as well as ADDTREE accounted for tree data. Two properties of the data proved useful in distinguishing between the models: the skewness of the distribution of distances, and the proportion of elongated triangles, which measures departures from the ultrametric inequality, Applications of KYST and ADDTREE to some twenty sets of real data, collected by other investigators, showed that most of these data could be classified clearly as favoring either a tree or a two-dimensional representation.A portable PASCAL program implementing the Sattath and Tversky [1977] ADDTREE algorithm is available from J. Corter, Department of Psychology, Stanford University, Stanford, California 94305. 相似文献
119.
Note on ultrametric hierarchical clustering algorithms 总被引:3,自引:0,他引:3
Vladimir Batagelj 《Psychometrika》1981,46(3):351-352
Milligan presented the conditions that are required for a hierarchical clustering strategy to be monotonic, based on a formula by Lance and Williams. In the present paper, the statement of the conditions is improved and shown to provide necessary and sufficient conditions.This work was supported in part by the Boris Kidri Fund, Yugoslavia. 相似文献
120.
关于短时记忆中范畴群集的定位实验 总被引:1,自引:0,他引:1
本研究通过对短时记忆的编码或提取阶段进行注意分散来探讨范畴群集的定位问题。以大学生为被试,应用双作业进行分散注意条件下的记忆实验,并与集中注意条件下的记忆实验进行比较。识记材料均为双范畴词表。结果表现无论在编码还是提取阶段分散注意,都导致范畴群集程度的降低。实验结果不支持认为范畴群集的组织过程仅仅发生在记忆信息加工的某一个阶段的看法,而有利于双重定位观点,即认为范畴群集既与编码阶段有关,也与提取阶段有关。 相似文献