Automatic Generation of Semi-structured Documents

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.

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Marking Up is Not Enough

Methods of Information in Medicine ◽

10.1055/s-0038-1634939 ◽

1993 ◽

Vol 32 (04) ◽

pp. 272-273 ◽

Cited By ~ 3

Author(s):

A. L. Rector

Keyword(s):

Health Care ◽

Intelligent Processing ◽

Structured Documents ◽

Electronic Health ◽

Health Care Records

Response to: Essin DJ. Intelligent processing of loosely structured documents as a strategy for organizing electronic health care records. Meth Inform Med 1993; 32: 265.

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Intelligent Processing of Loosely Structured Documents as a Strategy for Organizing Electronic Health Care Records

Methods of Information in Medicine ◽

10.1055/s-0038-1634938 ◽

1993 ◽

Vol 32 (04) ◽

pp. 265-268 ◽

Cited By ~ 11

Author(s):

D. J. Essin

Keyword(s):

Health Care ◽

Health Care Organization ◽

Database Systems ◽

Relevant Information ◽

Full Potential ◽

Care Organization ◽

Intelligent Processing ◽

Data Interchange ◽

Structured Documents ◽

Health Care Records

AbstractLoosely structured documents can capture more relevant information about medical events than is possible using today’s popular databases. In order to realize the full potential of this increased information content, techniques will be required that go beyond the static mapping of stored data into a single, rigid data model. Through intelligent processing, loosely structured documents can become a rich source of detailed data about actual events that can support the wide variety of applications needed to run a health-care organization, document medical care or conduct research. Abstraction and indirection are the means by which dynamic data models and intelligent processing are introduced into database systems. A system designed around loosely structured documents can evolve gracefully while preserving the integrity of the stored data. The ability to identify and locate the information contained within documents offers new opportunities to exchange data that can replace more rigid standards of data interchange.

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