Clustering-Based Visual Interfaces for Presentation of Web Search Results: An Empirical Investigation

Abstract

The result of a typical web search is often overwhelming. It is very difficult to explore the textual listing of the resulting documents, which may be in the thousands. In order to improve the utility of the search experience, we explore presenting search results through clustering and a zoomable two-dimensional map (zoomable treemap). Furthermore, we apply the fisheye view technique to this map of web search clusters to provide details in context. In this study, we report on our evaluation of these presentation features. The particular interfaces evaluated were:(1) a textual list, (2) a zoomable two-dimensional map of the clustered results, and (3) a fisheye version of the zoomable twodimensional map where the results were clustered. We found that subjects completed search tasks faster with the visual interfaces than with the textual interface, and faster with the fisheye interface than just the zoomable interface. Based on the findings, we conclude that there is promise in the use of clustering and visualization with a fisheye zooming capability in the exploration of web search results.

A survey of Web clustering engines

“…A recent comparison of textual and zoomable interfaces to search results clustering has shown that even if the raw retrieval performance of the tested systems was comparable, users subjectively preferred Vivísimo's textual interface [Rivadeneira and Bederson 2003]. In another experiment [Turetken and Sharda 2005], a TreeMap visualization of clustered results was found to be more effective than a ranked list presentation. Unfortunately, in this latter experiment the effect of clustering was not decoupled from that of the visual interface.…”

“…Although in this section, we have focused on automatic evaluation methods, it must be noted that conducting user studies is a viable alternative or complementary approach [Chen and Dumais 2000;Turetken and Sharda 2005;Ferragina and Gulli 2005;Käki 2005;and Carpineto et al 2006]. The user performs some kind of informationseeking task with the systems being compared, the user session is recorded, and the retrieval performance is typically evaluated measuring the accuracy with which the task has been performed, and its completion time.…”

Untitled

“…Individuals can use this user-generated content to make wiser decisions (Huang, Tu, Fu, & Amanzadeh, 2013). However, users often find the vastness of this content hard to digest, which gives rise to the challenge of information overload (Turetken & Sharda, 2005).…”

The impact of context-aware fisheye models on understanding business processes: An empirical study of data flow diagrams

“…Such integration is not easy and may cause disorientation with viewers feeling lost. System analysts are therefore faced with a dilemma: one option is the creation of a single comprehensive model, while the other is the creation of separate models representing different parts of the overall system, possibly causing confusion when switching between diagrams at www.elsevier.com/locate/im Information & Management 44 (2007) [40][41][42][43][44][45][46][47][48][49][50][51][52] different levels of detail. According to Kim et al, this effect complicates the cognitive processes in integrating these diagrams to understand the system as a whole.…”

“…The fisheye view concept introduced by Furnas [10] seemed particularly promising. It has been applied to graphical presentations of hierarchies for groupware [16], hypertext [9], and search on the World Wide Web [41]. Turetken et al [40] and Turetken and Schuff [39] proposed the use of fisheye views with systems analysis and design diagrams.…”