The growth of mobile applications that run on cell phones and other handheld devices has introduced a broad range of usability challenges that were not faced by the web and standalone PC environments. The current usability models for mobile applications are mostly based on the experience of the usability experts and users that were collected through surveys and field studies. Many usability researchers and practitioners have developed conceptual usability frameworks that utilize either different or overlapping usability attributes. Moreover, the usability frameworks in existence they are limited in scope and do not consider all the usability dimensions. There is no consensus among usability researchers and standard organizations regarding what constitutes a usability model or framework. This research attempts to utilize a novel, computational, linguistic approach in order to identify the semantic relatedness between different usability attributes. We use text-mining and information-extraction techniques to mine for usability attributes in a large collection of published literature about mobile usability. A hierarchical clustering analysis is performed to cluster semantically related usability attributes. The results are utilized to develop a usability taxonomy and a unified usability construct for mobile applications.