@techreport{12297,
author       = {Hildebrand, M. and van Ossenbruggen, J. R. and Amin, A. K. and Aroyo, L. and Wielemaker, J. and Hardman, L.},
title        = {The {Design} {Space} {Of} {A} {Configurable} {Autocompletion} {Component}},
series       = {Information Systems [INS]},
year         = {2007},
number       = {INS-E0708},
publisher    = {CWI},
issn         = {1386-3681},
class        = { H.5.2; H.3.3},
keywords     = {Semantic autocompletion, configurable interface component, sorting, clustering, presentation, RDF"},
group        = {INS2},
language     = {en},
abstract     = {Autocompletion is a commonly used interface feature in diverse applications. Semantic Web data has, on the
 one hand, the potential to provide new functionality by exploiting the semantics in the data used for generating autocompletion
 suggestions. Semantic Web applications, on the other hand, typically pose extra requirements on the semantic properties
 of the suggestions given. When the number of syntactic matches becomes too large, some means of selecting a semantically
 meaningful subset of suggestions to be presented to the user is needed. In this paper we identify a number of key design
 dimensions of autocompletion interface components. Our hypothesis is that a one-size-fits-all solution to autocompletion
 interface components does not exist, because different tasks and different data sets require interfaces corresponding to
 different points in our design space. We present a fully configurable architecture, which can be used to configure autocompletion
 components to the desired point in this design space. The architecture has been implemented as an open source software component
 that can be plugged into a variety of applications. We report on the results of a user evaluation that confirms this hypothesis,
 and describe the need to evaluate semantic autocompletion in a task and application-specific context.
},
url          = {http://oai.cwi.nl/oai/asset/12297/12297D.pdf},
}

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