SketchBrain: An Interactive Information Seeking Interface for Exploratory Search Hogun Park, Sung Hyon Myaeng, Gwan Jang, Jong-wook Choi, Sooran Jo, Hyung-chul Roh School of Engineering, Information & Communications University (ICU) 119, Munjiro, Yuseong-gu, Daejeon, 305-732, Korea +42-866-6210, 82 {gsgphg, myaeng, ilys23, pudidic, ddangly-, nuunmir }@icu.ac.kr ABSTRACT As the Web has become a commodity, it is used for a variety of purposes and tasks that may require a great deal of cognitive efforts. However, most search engines developed for the Web provide users with only searching and browsing capabilities, leaving all the burdens of manipulating information objects to the users. In this paper, we focus on an exploratory search task and propose an underlying framework for human-Web interactions. Based on the framework, we designed and implemented a new information seeking interface that helps users to relieve cognitive burden. The new human-Web interface provides a personal workspace that can be created and manipulated cooperatively with the system, which helps the user conceptualize his information seeking tasks and record their trails for future uses. This interaction tool has been tested for its efficacy as an aid for exploratory search. Categories and Subject Descriptors H.3.7 [Information Storage and Retrieval]: Information seeking Interface General Terms Documentation, Design, Experimentation. Keywords Information Seeking Interface, Exploratory Search 1. INTRODUCTION For a traditional Web search engine, the process of querying and viewing the results is usually regarded as a single, isolated session that ends in itself. As the Web has become a commodity, however, it is used for a variety of tasks in many different ways, encouraging new paradigms in information seeking (e.g. berrypicking [1], information foraging [2], and sense-making [3]). However, most popular commercial search engines have taken a conservative position and adhered to the traditional model, leaving all the rest of the information seeking and related tasks to the user. More specifically, the user has all the burdens of manipulating the information objects that have come to his attention in a series of search activities. An area in which this type of cognitive burden affects significantly is exploratory search. An exploratory search task [4][5] is to investigate on the background information of a topic or gather information sufficient to make an informed decision. For example, assume that a user is considering purchasing a DMB (digital multimedia broadcasting) receiver. The user would want to learn more about the DMB technology and the manufacturers of various products related to it, so that he can select the provider and the products that best suit the needs. We believe that most existing search engines and their interfaces are not satisfactory for exploratory tasks, because of the following. First, compared to the task of searching for specific or known items, an exploratory search task usually requires users to send a series of queries during a search session, visit more new domains, and revisit previously visited sites (especially branch pages) [5]. These activities together mean a significant amount of information and workload that traditional search engines have rarely attempted to reduce. The workload is associated with representing information needs [14], determining informativeness [15], and memorizing previously explored information [16]. Without explicit support from a search engine, the difficulties resulting from the workload are left as a cognitive burden to the user. Second, there are narrow interaction channels for incorporating user interests. In an exploratory search, a user needs to build up background information on a topic gradually until she feels that a sufficient amount of information has been gathered for the given task. As such, it is important to incorporate the users’ interest and the information that has been found as the system processes the current query. However, current search systems rarely support the notion of “session” and interactions explicitly. While the one-time query/result model is simple and natural with HTTP, it ignores what has been done by the user in her attempt to change her anomalous state of knowledge [17]. Although there have been some attempts to infer user interest explicitly [7][8][9], implicitly [18], or both [19], the problem remains challenging, especially within the context of user-system interactions. Given the limitations of traditional search engines for an open- ended, exploratory search task, we propose a new interaction tool that can provide an interface between a user and a search engine, called sketchBrain. Our aim is to provide an effective interaction Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. HCIR’08, Oct 23, 2008, Redmond, WA. Copyright 2008 ACM 1-58113-000-0/00/0004…$5.00. 53