Keywords Information management, information retrieval, 3D, similarity, categorization, information visualization, classification introduction




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Visualizing Implicit Queries

For Information Management and Retrieval



Mary Czerwinski, Susan Dumais, George Robertson,

Susan Dziadosz, Scott Tiernan and Maarten van Dantzich

Microsoft Research
One Microsoft Way
Redmond, WA 98052 USA
+1 425-703-4882
marycz@microsoft.com






Figure 1. Data Mountain with Implicit Query results shown (highlighted pages to left of selected page).

Figure 1. Data Mountain with Implicit Query results shown (highlighted pages to left of selected page).





ABSTRACT


In this paper, we describe the use of similarity metrics in a novel visual environment for storing and retrieving favorite web pages. The similarity metrics, called Implicit Queries, are used to automatically highlight stored web pages that are related to the currently selected web page. Two experiments explored how users manage their personal web information space with and without the Implicit Query highlighting and later retrieve their stored web pages. When storing and organizing web pages, users with Implicit Query highlighting generated slightly more categories. Implicit Queries also led to faster web page retrieval time, although the results were not statistically significant.

Keywords


Information management, information retrieval, 3D, similarity, categorization, information visualization, classification

INTRODUCTION


The digital revolution has brought with it the problem of information overload. Even the simplest user query for information is accompanied by a results list that can be overwhelming. In addition, very little support is provided to help users in collecting, organizing and determining relevancy of retrieved items [, , ]. A careful examination of the graphical user interface and of similarity analysis methods is needed in order to address these sensemaking hurdles.

Usually query results are presented textually, as lists of e-mail, Internet documents or news reports. However, today nearly all web pages include some form of distinguishable graphics (e.g., a company logo) that users might associate in memory with that page. To take advantage of this, we present a visualization that allows users to manually create a spatial layout of the thumbnails of their documents in a 3D environment.

As an organizational aid to the user, we use document similarity metrics and visual highlighting cues to indicate that web pages are semantically related in this personal information space. This paper will compare two such metrics, one user-driven and one content-driven, used to determine web page similarity relations during sensemaking tasks.


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Current web browsers try to alleviate the sensemaking problems raised above through the use of bookmarks or favorites mechanisms, wherein users store the URLs of interesting web pages in order to build a personalized information space. Despite these user interface mechanisms, a 1998 survey of over 10,000 web users revealed that one of the most common problems users have with the web is organizing the information that they gather there []. In related research, Abrams, et al. [] studied the bookmark archives and personal Web habits of users and made recommendations for improving the design of existing favorites management systems. Abrams surveyed 322 Web users, and analyzed the bookmarks of 50 Web users in detail. He found that bookmarks were used to reduce the cognitive load of managing URL addresses (by aiding memory and keeping history), to facilitate access, and to create information spaces for personal and group use. Bookmarks were often added sporadically—perhaps not surprisingly when too many favorite pages were piling up in a user’s list. Almost 40% of those studied used no organization and simply left web pages in the order they were added to the favorites list; 50% used a hierarchy of one (30%) or more (20%) levels. Most users organized at the time they created a bookmark and cleaned up only occasionally. The initial use of folders began after a user had about 35 bookmarks. Abrams also found that 50% of the bookmarks had been visited in the last 3 months; 67% in the last 6 months; and 97% in the last year. Some ease of use recommendations provided by Abrams included providing aids in the browser for semi-automatic filing, time- or usage-based orderings, and much better tools for helping users in their organizing task. These findings provided the primary motivation for the research described in this paper.

We describe a new interaction that helps users quickly recognize and use the categorical structure they need to organize their favorite web pages. The interaction technique includes the Data Mountain [], a novel visual environment for laying out personal web pages in a 3D space (described below), and an Implicit Query technique which shows the user which items are related to their current interest. Our Implicit Query algorithms determine similarities among web pages, and present the results in a visual format that has been observed to be useful and usable. This approach allows users to focus on relevant items instead of searching through large numbers of pages in the space. We have initially applied this idea to interaction with documents on the Web, although the interaction technique could be applied to any electronic document management task.
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