Data Mining Practical Machine Learning Tools and Techniques

We present VOSviewer, a freely available computer program that we have developed for constructing and viewing bibliometric maps. Unlike most computer programs that are used for bibliometric mapping, VOSviewer pays special attention to the graphical representation of bibliometric maps. The functionality of VOSviewer is especially useful for displaying large bibliometric maps in an easy-to-interpret way. The paper consists of three parts. In the first part, an overview of VOSviewer’s functionality for displaying bibliometric maps is provided. In the second part, the technical implementation of specific parts of the program is discussed. Finally, in the third part, VOSviewer’s ability to handle large maps is demonstrated by using the program to construct and display a co-citation map of 5,000 major scientific journals.

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Software survey: VOSviewer, a computer program for bibliometric mapping.

In this article we present a standardized set of 260 pictures for use in experiments investigating differences and similarities in the processing of pictures and words. The pictures are black-and-white line drawings executed according to a set of rules that provide consistency of pictorial representation. The pictures have been standardized on four variables of central relevance to memory and cognitive processing: name agreement, image agreement, familiarity, and visual complexity. The intercorrelations among the four measures were low, suggesting that they are indices of different attributes of the pictures. The concepts were selected to provide exemplars from several widely studied semantic categories. Sources of naming variance, and mean familiarity and complexity of the exemplars, differed significantly across the set of categories investigated. The potential significance of each of the normative variables to a number of semantic and episodic memory tasks is discussed.

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A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity.

Fast and frugal heuristics - simple rules for making decisions with realistic mental resources - are presented here. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? What heuristics are in the mind's adaptive toolbox, and what building blocks compose them? Can judgments based simply on a single reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? This book explores these questions by developing computational models of heuristics and testing them through experiments and analysis. It shows how fast and frugal heuristics can yield adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop-out rates, and playing the stock market.

Simple Heuristics That Make Us Smart

The purpose of this article is to review basic empirical results from the psychological literature in a way that provides a useful foundation for research on consumer knowledge. A conceptual organization for this diverse literature is provided by two fundamental distinctions. First, consumer expertise is distinguished from product-related experience. Second, five distinct aspects, or dimensions, of expertise are identified: cognitive effort, cognitive structure, analysis, elaboration, and memory. Improvements in the first two dimensions are shown to have general beneficial effects on the latter three. Analysis, elaboration, and memory are shown to have more specific interrelationships. The empirical findings related to each dimension are reviewed and, on the basis of those findings, specific research hypotheses about the effects of expertise on consumer behavior are suggested.

Dimensions of Consumer Expertise

Partial table of contents: OVERVIEWS Applying Cognitive Psychology: Bridging the Gulf Between Basic Research and Cognitive Artifacts (D Gillan & R Schvaneveldt) Applications of Attention Research (W Rogers, et al) Knowledge and Expertise (N Charness & R Schultetus) Applications of Social Cognition: Attitudes as Cognitive Structures (L Fabrigar, et al) BUSINESS AND INDUSTRY The Cognitive Psychology and Cognitive Engineering of Industrial Systems (N Moray) Applied Cognition in Consumer Research (J Alba & J Hutchinson) COMPUTERS AND TECHNOLOGY Devices that Remind (D Herrmann, et al) Knowledge Elicitation (N Cooke) INFORMATION AND INSTRUCTION Statistical Graphs and Maps (S Lewandowsky & J Behrens) Instructional Technology (R Mayer) Cognitive Psychology Applied to Testing (S Embretson) HEALTH AND LAW Medical Cognition (V Patel, et al) Designing Healthcare Advice for the Public (P Wright) Perspectives on Jury Decision-Making: Cases with Pretrial Publicity and Cases Based on Eyewitness Identifications (J Devenport, et al) Indexes

Handbook of applied cognition

Publisher Summary This chapter discusses network representations and their relationship to proximity data. Proximity data are commonplace in the social and behavioral sciences. Networks have several properties that should be of value in representing the structure in proximity data. Networks reduce a large number of pairwise proximities to a smaller set of links. Compared to spatial scaling methods, networks focus on the closely related entities. Graph theory is the mathematical study of structures consisting of nodes with links connecting some pairs of nodes. In applications of networks, the nodes usually represent entities and the links represent pairwise relations among the entities. Because a set of nodes can be connected by links in many possible ways, a wide variety of structures can be represented by graphs. The methods used to obtain the proximity data used in the Pathfinder analyses are straightforward and analogous to methods employed to obtain data for cluster analysis

Network Structures in Proximity Data

Air traffic control instructors controlled simulated traffic while a variety of techniques for determining situation awareness (SA) were implemented. SA was assessed using a self-report measure (th...

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Situation awareness as a predictor of performance in en route air traffic controllers

This report reviews work on defining and measuring conceptual structures of expert and novice fighter pilots. Individuals with widely varying expertise were tested. Cognitive structures were derived using multidimensional scaling (MDS) and link-weighted networks (Pathfinder). Experience differences among pilots were reflected in the conceptual structures. Detailed analyses of individual differences point to factors that distinguish experts and novices. Analysis of individual concepts identified areas of agreement and disagreement in the knowledge structures of experts and novices. Applications in selection, training and knowledge engineering are discussed.

Francis T. Durso

Papers

Handbook of applied cognition

Network Structures in Proximity Data

Situation awareness as a predictor of performance in en route air traffic controllers

Measuring the structure of expertise

Facilitation in naming and categorizing repeated pictures and words.