Publication
HCI International
Conference
Location
Los Angeles, California
Abstract
A method is presented for generating informative and natural-sounding infotips for the graphical elements of a user interface. A domain-specific corpus is prepared using natural language processing techniques and a term-frequency/inverse-document-frequency transform is used for vectorization of features. A k-means clustering algorithm is used to group the corpus by semantic similarity and perform an automatic selection of infotips corresponding to inputted interface labels.