Data‐driven approaches to information access

This paper summarizes three lines of research that are motivated by the practical problem of helping users find information from external data sources, most notably computers. The application areas include information retrieval, text categorization, and question answering. A common theme in these applications is that practical information access problems can be solved by analyzing the statistical properties of words in large volumes of real world texts. The same statistical properties constrain human performance, thus we believe that solutions to practical information access problems can shed light on human knowledge representation and reasoning.     

Rare Constructions Are More Often Sentence‐Initial

Main clause phenomena (MCPs) are syntactic constructions that occur predominantly or exclusively in main clauses. I propose a processing explanation for MCPs. Sentence processing is easiest at the beginning of the sentence (requiring less search); this follows naturally from widely held assumptions about sentence processing. Because of this, a wider variety of constructions can be allowed at the beginning of the sentence without overwhelming the sentence‐processing mechanism. Unlike pragmatic and grammatical accounts of MCPs, the processing account predicts avoidance of MCPs in non‐initial main clauses (non‐initial coordinate clauses and premodified clauses). A corpus study supports these predictions, but it is somewhat inconclusive. A further corpus study examines another type of syntactic construction, premodifying adjunct phrases (“openers”); the prediction here is that less common types of opener will be especially avoided in non‐initial contexts. The prediction is confirmed, supporting the processing view of rare constructions.     

“To hope was to expect”: The impact of perspective taking and forecast type on wishful thinking

When forecasting future outcomes, people tend to believe that the outcomes they want to happen are also likely to happen. Despite numerous attempts, few systematic factors have been identified that consistently and robustly reduce wishful thinking (WT) effects. Using elections and sporting event outcomes as contexts, three experiments examined whether taking the perspective of a political rival or opposing fan reduced WT effects. We also examined whether making deliberative (vs. intuitive-based) forecasts was associated with lower WT effects. Online adult samples of U.S. citizens from Mechanical Turk and U.S. college students provided their preferences and forecasts for the U.S. presidential election (Experiments 1 and 2) and a sports competition outcome (Experiment 3). Critically, some participants received perspective taking prompts immediately before providing forecasts. First, results revealed reductions in WT effects when participants engaged in perspective taking. Interestingly, this effect only emerged when intuitive-based forecasts were made first (Experiment 3). Second, intuitive-based forecasts revealed stronger evidence of WT effects. Finally, we found that perspective taking and forming forecasts deliberately promoted a shift in focus away from preferences and toward a consideration of the relative strengths and weaknesses of the entities (i.e., candidates and teams). Theoretical implications for understanding WT effects and applied implications for developing interventions are discussed.     

Functional measurement approach to self-estimation in multiattribute evaluation

Multiattribute analysis depends on measurement of values and weights. Unless these measures reflect the decision maker's true values and weights, the multiattribute formula may put a less-preferred alternative in first place. To avoid such disordinality requires stringent measurement conditions: First, the values and weights must be on linear (equal interval) or ratio (known zero) scales. Second, these scales must satisfy a condition of common unit across disparate attribute dimensions. Most methods of range adjustment beg both of these measurement questions. Functional measurement theory can solve both problems and so can be useful in multiattribute analysis. Past work has established the operation of a general cognitive algebra as an empirical reality. The averaging model, in particular, makes possible the definition and estimation of weights and values as distinct psychological parameters. It can also solve the problem of common unit. Cognitive algebra thus provides a grounded theoretical foundation on which to develop self-estimation methodology, in which decision makers provide direct estimates of their values and weights. The logic is straightforward. Functional measurement can analyze global judgments to obtain validated psychological scales. These scales may then be used as validational criteria for the self-estimates. Procedures to eliminate biases in the self-estimates can thus be tested and refined in well-learned multiattribute tasks, such as judgments of meals, in which global judgments are trustworthy. Once developed, such self-estimation procedures may be used with some confidence for general multiattribute analysis. A number of studies from 20-odd years of work on the theory of information integration are summarized to show good, although not unmixed promise for self-estimation.     

影响频度记忆的几个因素

本研究通过两个实验探讨了刺激呈现频度、刺激的形式及其性质、加工深度、操作难度、意向性诸因素对频度记忆的影响,结果表明频度编码并不是一个独立、自动的加工系统,对其它识记过程有影响的因素同时也能改变被试的频度估计水平;意向的作用主要体现在当识记任务有一定难度且又缺乏有效的回忆线索时,能够在有限的范围内提高频度估计的水平;记忆痕迹的深度和广度对于频度信息的提取来说是两个彼此关联的线索。此外,本文还就频度记忆领域几个主要理论观点作了简要评述。     

量词肯定句和否定句的理解

本研究试图探索人们对舍有“所有”、“每一个”、“有一些”等量词的肯定句、否定句和双重否定句的理解。要求成人被试尽快判断呈现在计算机屏幕上的句子和哪一幅图画的内容相符。结果表明,影响反应时的因素为(1)句子的表层结构和它的底层意义的一致程度;(2)句子的意义和从图画中得出的命题的一致程度;(3)句子中使用的量词。结果还表明,否定句的判断时间不一定全都比肯定句的长。     

Parallel distributed processing and neuropsychology: A neural network model of Wisconsin card sorting and verbal fluency

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.     

Incorporating prior theory in covariance structure analysis: A bayesian approach

A Bayesian approach to the testing of competing covariance structures is developed. The method provides approximate posterior probablities for each model under consideration without prior specification of individual parameter distributions. The method is based on ayesian updating using cross-validated pseudo-likelihoods. Given that the observed variables are the samefor all competing models, the approximate posterior probabilities may be obtained easily from the chi square values and other known constants, using only a hand calculator. The approach is illustrated using and example which illustrates how the prior probabilities can alter the results concerning which model specification is preferred.     

Assertiveness and cognitive processing in interpersonal situations

This study examined social skills components that precede the delivery of a skilled overt interpersonal response. Using a cognitive-behavioral systems approach to assertiveness, a task analysis of how women receive and process information in interpersonal situations requiring an assertive response to men was performed. Forty women were assigned to high- or low-assertive groups based on their Rathus Assertiveness Schedule scores. In small group sessions, each woman viewed four videotaped problem situations requiring an assertive response to both pleasant and angry males. After viewing each scene, each woman completed three questionnaires: (a) receiving information, (b) processing-generation of alternatives and decision making, and (c) processing-generation of consequences. High- and low-assertive participants were found to differ in their evaluation of consequences, for response options, particularly how a male would likely to behave to them. High-assertive participants were judged to evaluate more correctly than low-assertive participants the likely behavior of males if response options were implemented. All participants generated more complex alternatives and more assertive responses to situations involving an angry male as compared to a pleasant male. No differences were found between groups in their ability to receive information accurately. Correlational results were supportive of a cognitive-behavioral systems approach of assertion, that is, the emission of a skilled response depends on a chain of preceding responses.Thanks are due to Vida Dyson and Lenard Jason for their comments on an early draft of this paper.