Exploratory search is an increasingly important activity yet challenging for users. Although there exists an ample amount of research into understanding exploration, most of the major information retrieval (IR) systems do not provide tailored and adaptive support for such tasks. One reason is the lack of empirical knowledge on how to distinguish exploratory and lookup search behaviors in IR systems. The goal of this article is to investigate how to separate the 2 types of tasks in an IR system using easily measurable behaviors. In this article, we first review characteristics of exploratory search behavior. We then report on a controlled study of 6 search tasks with 3 exploratory-comparison, knowledge acquisition, planning-and 3 lookup tasks-factfinding, navigational, question answering. The results are encouraging, showing that IR systems can distinguish the 2 search categories in the course of a search session. The most distinctive indicators that characterize exploratory search behaviors are query length, maximum scroll depth, and task completion time. However, 2 tasks are borderline and exhibit mixed characteristics. We assess the applicability of this finding by reporting on several classification experiments. Our results have valuable implications for designing tailored and adaptive IR systems. IntroductionSearch activities are commonly divided into two broad categories: lookup and exploratory (Marchionini, 2006). Lookup search is by far the better understood and assumed to have precise search goals. The predominant design goal in information retrieval (IR) systems has been fast and accurate completion of lookup searches. Exploratory search is presently thought to center around the acquisition of new knowledge and considered to be challenging for the user (White & Roth, 2009). Although there has been a lot of research on understanding exploratory search, there are many open questions when it comes to the design of IR systems that provide tailored and adaptive support. One of the key problems is how we can make an IR system automatically distinguish the two categories of search in the course of a search session (Belkin, 2008). In this article, we look into if, and how well, we can tell apart lookup and exploratory search activities from properties that IR systems can easily observe.It is difficult to separate exploratory and lookup search in IR systems. This is because currently there is a gap between our knowledge in exploratory search behaviors and requirements of IR system design. First, many studies compared the exploratory and lookup searches by cognitive strategies only (J. Kim, 2009;Thatcher, 2008 activity: learning or knowledge acquisition. However, it is held that exploratory search involves many subcategories of search activities (Marchionini, 2006;White & Roth, 2009). Third, many studies that attempt to distinguish between different task types only consider web search behaviors but not behaviors specific to IR system use (Liu et al., 2010b). There are marked differences between web searching and...
Since the recent emergence of electronic literature resources, researchers have begun to adopt new informationseeking practices. The purpose of this research is to investigate the information needs and searching behaviors of researchers, and their implications for electronic literature search tools. We conducted mixed-method case studies involving interviews, diary logs, and observations of computer scientists followed by a web-based survey to validate our findings. The results show that computer science researchers have the following main purposes for seeking information: keeping up to date, exploring new topics, reviewing literature, collaborating, preparing lectures, and recommending material for students. We found that keeping up to date with research is the most frequent purpose and exploring unfamiliar research areas is the most difficult. Furthermore, we found that literature searching is a collaborative process and, depending on the search purpose, different information sources and navigation strategies are used. On the basis of these findings we discuss six design challenges for literature search tools, which are: providing support for keeping up to date with research, exploring unfamiliar topics, browsing user history, collaborating and sharing, performing a federated search that goes beyond scholarly research, and sorting and navigating the results.
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