@incollection{vdv07chi,
title = {Mapping semantic relevancy of information displays},
author = { Vladislav Daniel Veksler and Wayne D. Gray},
year = {2007},
date = {2007-01-01},
booktitle = {ACM CHI 2007 Conference on Human Factors in Computing Systems},
pages = {2729-2734},
publisher = {ACM Press},
address = {NY},
abstract = {Semantic Relevancy Maps are a visual analytic technique for representing the distribution of semantic relevancy across an information display. The maps highlight the text areas of the display corresponding to the relevance of that text to user goals, with stronger highlights indicating higher degrees of relevance. Semantic Relevancy Maps were developed as a tool for high-fidelity computational cognitive models that search complex information displays in the same manner as humans. However, they offer the potential to be a standalone tool for quickly evaluating the spatial layout of information for designers or, more simply, for identifying the spatial location of sought-for information by any computer user.},
keywords = {associative strength, semantic relevancy maps, Semantic similarity measures, visual analytics, visual saliency maps},
pubstate = {published},
tppubtype = {incollection}
}
Semantic Relevancy Maps are a visual analytic technique for representing the distribution of semantic relevancy across an information display. The maps highlight the text areas of the display corresponding to the relevance of that text to user goals, with stronger highlights indicating higher degrees of relevance. Semantic Relevancy Maps were developed as a tool for high-fidelity computational cognitive models that search complex information displays in the same manner as humans. However, they offer the potential to be a standalone tool for quickly evaluating the spatial layout of information for designers or, more simply, for identifying the spatial location of sought-for information by any computer user.
@techreport{vdv06techRpt,
title = {I see where you mean: Thinking spatially about meaning for HCI research and practice},
author = { Vladislav Daniel Veksler and Wayne D. Gray},
year = {2006},
date = {2006-09-01},
number = {CWL-TR060928},
institution = {Rensselaer Polytechnic Institute},
abstract = {Semantic Relevancy Maps are a visual analytic technique for representing the distribution of semantic relevancy across an information display. The maps highlight the text areas of the display corresponding to the relevance of that text to user goals, with stronger highlights indicating higher degrees of relevance. Semantic Relevancy Maps were developed as a tool for high-fidelity computational cognitive models that search complex information displays in the same manner as humans. However, they offer the potential to be a standalone tool for quickly evaluating the spatial layout of information for designers or, more simply, for identifying the spatial location of sought-for information by any computer user.},
keywords = {associative strength, semantic relevancy maps, Semantic similarity measures, visual analytics, visual saliency maps},
pubstate = {published},
tppubtype = {techreport}
}
Semantic Relevancy Maps are a visual analytic technique for representing the distribution of semantic relevancy across an information display. The maps highlight the text areas of the display corresponding to the relevance of that text to user goals, with stronger highlights indicating higher degrees of relevance. Semantic Relevancy Maps were developed as a tool for high-fidelity computational cognitive models that search complex information displays in the same manner as humans. However, they offer the potential to be a standalone tool for quickly evaluating the spatial layout of information for designers or, more simply, for identifying the spatial location of sought-for information by any computer user.
