Abstract

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—fact‐finding, 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.

Highlights

  • Search activities are commonly divided into two broad categories: lookup and exploratory (Marchionini, 2006)

  • There has been a lot of research on understanding exploratory search, there are many open questions when it comes to the design of information retrieval (IR) systems that provide tailored and adaptive support

  • To make an informed decision, we review information search behaviors identified in the literature and select a set of behaviors that are both expected to be informative as well as easy to measure by an IR system

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Summary

Introduction

Search activities are commonly divided into two broad categories: lookup and exploratory (Marchionini, 2006). 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. There are marked differences between web searching and searching with IR systems (Jansen & Pooch, 2001) To this end, a thorough empirical analysis of exploratory and lookup activities within an IR environment is necessary. Our objective is to provide a systemic and rigorous analysis of exploratory and lookup information search behaviors across several search activities. We follow the framework of Marchionini (2006) This framework assigns the lower level search activities, such as, fact-finding, knowledge acquisition, into high-level categories—exploratory and lookup.

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