FOR THE WEB
The World Wide Web presents both new challenges and opportunities for conducting Human Factors work. Browse hierarchies used to classify web content present an interesting case in point. On the one hand, the size of the domain to be classified and its general-purpose intent (i.e., it is intended for all users and retrieval of all types of information) make traditional techniques such as card sorts too unwieldy. On the other hand, the nature of the Web makes efficient data collection from a relatively large number of people a possibility. The purpose of this initial, small-scale study was to begin to investigate usability methods that have the potential to scale to the range of users and tasks and at the same time take advantage of the data collection possibilities that exist for the web (e.g., server log data.)
A coherent, learnable category structure is a central goal for browse hierarchies such as those on Yahoo, Excite, msn.com and other Internet portals. Such a structure will allow users to efficiently find the information they need and to become more and more proficient in using the hierarchy over time. We know from cognitive psychology ( Rosch 1975) that coherent, learnable category structures have high within-category similarity and high between category discriminability. For abstract categories, such as those found in browse hierarchies for the web, we also know that linguistic cues that highlight relevant features of the categories can be important ( Horton and Markman 1980). Categories whose members go together in a loose way, have high overlap with other categories, or are represented with general labels that do not highlight reasons for category membership should be difficult for people to use.
Beyond the difficulties of size and the general-purpose nature of browse hierarchies in the creation of usable browse hierarchies, the fact that once a browse hierarchy is released to the Web content continues to be added makes maintaining a good user experience challenging. Changes to the makeup and