Experimental solutions for searching in an architectural and urban planning-specific database

  • Authors:
  • Daniel Rude;Lucio Campanelli;Xiangming Mu

  • Affiliations:
  • University of Wisconsin-Milwaukee, Milwaukee, WI;University of Wisconsin-Milwaukee, Milwaukee, WI;University of Wisconsin-Milwaukee, Milwaukee, WI

  • Venue:
  • Proceedings of the 2011 iConference
  • Year:
  • 2011

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Abstract

This paper studies the search behavior of an image search retrieval system using the model of an architectural and urban planning database. In this mixed-method study, interviews and surveys were conducted to identify unique search behaviors employed by student-workers at Community Design Solutions, a non-profit architectural and urban planning organization at the School of Architecture and Urban Planning (SARUP) located at the University of Wisconsin-Milwaukee. The study looked for users to indicate the problems with the search strategies they formulated to navigate the current database, the problems they encountered and any suggestions they had for improving the system. Based off of the findings, we found that a lack of metadata and associated text, users had a very difficult time locating related images. From this, we propose a proximity retrieval system.