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2020 | Book

Introduction Read chapter Read first chapter

Understanding and Improving Information Search

A Cognitive Approach

Editors: Wai Tat Fu, Herre van Oostendorp

Publisher: Springer International Publishing

Book Series : Human–Computer Interaction Series

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik"

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About this book

This edited book adopts a cognitive perspective to provide breadth and depth to state-of-the-art research related to understanding, analyzing, predicting and improving one of the most prominent and important classes of behavior of modern humans, information search. It is timely as the broader research area of cognitive computing and cognitive technology have recently attracted much attention, and there has been a surge in interest to develop systems and technology that are more compatible with human cognitive abilities.

Divided into three interlocking sections, the first introduces the foundational concepts of information search from a cognitive computing perspective to highlight the research questions and approaches that are shared among the contributing authors. Relevant concepts from psychology, information and computing sciences are addressed. The second section discusses methods and tools that are used to understand and predict information search behavior and how the cognitive perspective can provide unique insights into the complexities of the behavior in various contexts. The final part highlights a number of areas of applications of which education and training, collaboration and conversational search interfaces are important ones.

Understanding and Improving Information Search - A Cognitive Approach includes contributions from cognitive psychologists, information and computing scientists around the globe, including researchers from Europe (France, Netherlands, Germany), the US, and Asia (India, Japan), providing their unique but coherent perspectives to the core issues and questions most relevant to our current understanding of information search behavior and improving information search.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
This book adopts a cognitive perspective to provide breadth and depth to state-of-the-art research related to understanding, analyzing, predicting, and improving one of the most prominent and important classes of behavior of modern humans: information search. This book is timely as the broader research area of cognitive computing and cognitive technology has recently attracted much attention, and there has been a surge in interest to develop systems that are more compatible with human cognitive abilities. The goal of this book is to introduce a coherent set of theories, methods, computational models, and empirical results that highlight how cognitively compatible systems can and should be developed to improve information search by humans. This edited book includes contributions from cognitive, social, information, and computer scientists around the globe, including researchers from Europe (France, Netherlands, Germany), the USA, and Asia (India, Japan), providing their unique but coherent perspectives to the set of core issues and questions most relevant to our current understanding of information search behavior. We expect this book will be of interest to information scientists, psychologists, and computer scientists.
Wai Tat Fu, Herre van Oostendorp

Foundation and Background

Frontmatter
Chapter 2. Challenges for a Computational Cognitive Psychology for the New Digital Ecosystem
Abstract
Advances in computational cognitive psychology have played an important role in understanding and engineering human–information interaction systems. These computational models include several addressing the cognition involved in the human sensemaking process, user models that capture the knowledge that humans acquire from interaction, and how people judge the credibility of online Twitter users who influence decision-making. The models presented in this chapter build on earlier information foraging models in which it is important to model individual-level knowledge and experience because these clearly influence human–information interaction processes. This chapter concludes with a discussion of challenges to computational cognitive models as digital information interaction becomes increasingly pervasive and complex.
Peter Pirolli
Chapter 3. How Cognitive Computational Models Can Improve Information Search
Abstract
This chapter discusses why and how a computational cognitive model that captures the broader set of processes of information search is important and useful. The first reason why this can be useful is when information search is only one component of a broader task. A better understanding of the broader process of information search can lead to better metrics of relevance that are specific to the broader task in which the user is engaged. The second reason is that it helps to develop better personalized tools that are more compatible with the individual users as they search information for different purposes. Two examples of such computational cognitive models are presented. The first model, SNIF-ACT, demonstrates the value of adopting a theory-based mechanism, called the Bayesian satisficing mechanism (BSM), that selects information search strategies based on ongoing assessment of the information scent cues encountered by a user as he or she navigates across Web pages. The second model, ESL, tracks both learning of knowledge structures and search behavior in a social tagging system over a period of eight weeks as they continuously search for Web documents. These computational cognitive models generate explicit predictions on what users will do when they interact with different information retrieval systems for different tasks in different contexts. Computational cognitive models therefore complement existing computational techniques that aim to improve information or document retrieval. At the same time, they allow researchers to develop and test unified theories of information search by integrating the vast literature on information search behavior in different contexts.
Wai Tat Fu
Chapter 4. Cognitive Modeling of Age and Domain Knowledge Differences in Information Search
Abstract
Several cognitive processes are involved in the process of information search on the Internet: memory, attention, comprehension, problem solving, executive control and decision making. Several cognitive factors such as aging-related cognitive abilities and domain knowledge in turn influence either positively or negatively these cognitive processes. Traditional click models from information retrieval community that predict user clicks do not fully consider the effect of the above cognitive factors. We demonstrate how the capabilities of computational cognitive models to simulate the effects of various cognitive factors can be used to improve our understanding of information search behavior. In this direction, we present some outcomes of modeling and predicting individual differences in information search due to age and domain knowledge using a computational cognitive model called CoLiDeS+. We also present some thoughts on how to model the influence of cognitive factors such as spatial ability and need for cognition in CoLiDeS+.
Saraschandra Karanam, Herre van Oostendorp

Methods and Tools

Frontmatter
Chapter 5. An Evolving Perspective to Capture Individual Differences Related to Fluid and Crystallized Abilities in Information Searching with a Search Engine
Abstract
Interacting with a search engine to search for information is an essential component in our information society. Yet, information search can be a complex task as users can face challenges when processing a staggering amount of information. Research in cognitive psychology and ergonomics has shown important individual differences in search strategies and performance. In this chapter, we describe how fluid and crystallized abilities may influence search behavior all along the task and how they can account for users’ difficulties. Our purpose is to provide a theoretical and methodological foundation to better understand the role of these abilities. To this point, we first review recent insights on the behavioral data collected in studies. Next, we present a new framework to analyze such data and discuss how fluid and crystallized abilities can impact information processing when searching for information. Illustrations of how this work can contribute to the development of useful information search support tools are discussed.
Mylène Sanchiz, Franck Amadieu, Aline Chevalier
Chapter 6. Semantic Relevance Feedback on Queries and Search Results for Younger and Older Adults
Abstract
In this chapter, we describe research in which the influence of providing feedback on the semantic relevance of queries and search results is examined with younger and older adults when they reformulate their search queries. Providing feedback on the semantic relevance of search queries and search results increased the semantic relevance of future search queries as they reformulated both for younger and older adults. This applies especially to more difficult search problems. For younger adults, in addition to the semantic relevance of search queries, also an improvement in their search performance (in terms of the amount of time and the number of clicks needed to solve the task) was observed. No such difference in search performance was found for older adults. A possible explanation could be that, older adults need more time to adjust to the new search interface in order to find effects not only in the semantic relevance of queries but also in their search performance.
Herre van Oostendorp, Saraschandra Karanam
Chapter 7. Designing Multistage Search Systems to Support the Information Seeking Process
Abstract
Due to the advances in information retrieval in the past decades, search engines have become extremely efficient at acquiring useful sources in response to a user’s query. However, for more prolonged and complex information seeking tasks, these search engines are not as well suited. During complex information seeking tasks, various stages may occur, which imply varying support needs for users. However, the implications of theoretical information seeking models for concrete search user interfaces (SUI) design are unclear, both at the level of the individual features and of the whole interface. Guidelines and design patterns for concrete SUIs, on the other hand, provide recommendations for feature design, but these are separated from their role in the information seeking process. This chapter addresses the question of how to design SUIs with enhanced support for the macro-level process, first by reviewing previous research. Subsequently, we outline a framework for complex task support, which explicitly connects the temporal development of complex tasks with different levels of support by SUI features. This is followed by a discussion of concrete system examples which include elements of the three dimensions of our framework in an exploratory search and sensemaking context. Moreover, we discuss the connection of navigation with the search-oriented framework. In our final discussion and conclusion, we provide recommendations for designing more holistic SUIs which potentially evolve along with a user’s information seeking process.
Hugo C. Huurdeman, Jaap Kamps
Chapter 8. Search Support Tools
Abstract
This chapter presents in-depth reviews of search tools for supporting information search. With the brief introduction of cutting-edge search support tools, we describe the key ideas behind the tools and implications for design. We also discuss the limitations of conventional search interfaces to explore directions for future research on search support tools.
Kazutoshi Umemoto, Takehiro Yamamoto, Katsumi Tanaka
Chapter 9. Eye-Tracking as a Method for Enhancing Research on Information Search
Abstract
The human eye plays an essential role in information acquisition from external world, and much of our contemporary information technology relies on visual processing. The eye-mind hypothesis suggests that human attention is connected to where our eyes are looking (Just and Carpenter 1980). Taken together with the continual movement of our eyes and the limited area of high-acuity human vision, eye-tracking methods are considered to offer theoretically reliable measures of visual attention and search task activities. We first briefly review cognitive factors of interest to information search and the “traditional” methods of their measurement. We then present examples of eye tracking tools and how they capture data before examining how eye-tracking data has been used to assess select cognitive factors in information search.
Jacek Gwizdka, Andrew Dillon

Areas of Applications

Frontmatter
Chapter 10. Children’s Acquisition of Text Search Strategies: The Role of Task Models and Relevance Processes
Abstract
Searching texts both online and in print has become an essential skill for twenty-first-century students. Although most children can read fluently and comprehend short texts by the age of 10, research suggests that older students and even adults experience difficulties when searching for information inside texts. This chapter synthesizes various theoretical models of the processes involved in information search, drawing from information science as well as cognitive psychology. We identify three key processes that may represent specific challenges for young students: constructing a task model, selectively scanning and assessing the relevance of information. We review the evidence regarding children’s ability to search for information, and we stress the importance of the task model on subsequent search processes. In the last part of the paper, we review attempts to foster children’s information search skills and we highlight some preconditions for skill acquisition. Finally, we discuss the implications of research on children’s search skills for future research in this domain.
Jean-François Rouet, Julie Ayroles, Mônica Macedo-Rouet, Anna Potocki
Chapter 11. Trainings and Tools to Foster Source Credibility Evaluation During Web Search
Abstract
On the Web, anyone can publish information without review by professional gatekeepers. Thus, in order to avoid obtaining incomplete or inaccurate information, Web searchers need to critically evaluate the credibility of online information or its source, respectively. However, previous research has indicated that Web users of all ages infrequently engage in credibility evaluation spontaneously during Web search. Therefore, in recent years, various interventions have been developed and tested that aim at fostering individuals’ credibility evaluation during Web search. The present chapter provides an overview of these interventions. Specifically, the chapter distinguishes between three different types of interventions or support tools, respectively. These are comprehensive long-term training programs that teach students the whole process of conducting Web searches (of which credibility evaluation is only one aspect among many), short-term trainings that focus explicitly on aspects of credibility evaluation during Web search, and last but not least computer-based applications or search results interfaces that provide prompts or cues that help evaluate the credibility of online information during Web search. The different types of approaches will be compared and critically discussed in terms of both their effectiveness and limitations.
Yvonne Kammerer, Saskia Brand-Gruwel
Chapter 12. Computer-Supported Collaborative Information Search for Geopolitical Forecasting
Abstract
Geopolitical forecasting is the process of generating judgments of probability for a wide variety of future geopolitical events, such as political elections, international conflict, disease outbreaks, and macro-economic indicators. Governmental policy-makers, private organizations, and individuals use forecasting to aid their strategic decision-making. For example, a government agency may forecast the likelihood of a disease outbreak; business leaders may forecast how the market will respond if they launch a new product; individuals may employ forecasting to aid their decisions about what career to choose or how to invest for retirement. Recent research in geopolitical forecasting showed that instruction, practice, and peer interaction made a big difference in forecasting accuracy. In this chapter, we review relevant literature from the areas of decision-making, psychology, and human–machine interaction and suggest how findings from these areas could contribute to improvements in forecasters’ performance. We also present data and insights gained from our experience as competitors in a government-funded forecasting tournament.
Ion Juvina, Othalia Larue, Colin Widmer, Subhashini Ganapathy, Srikanth Nadella, Brandon Minnery, Lance Ramshaw, Emile Servan-Schreiber, Maurice Balick, Ralph Weischedel
Chapter 13. Conversational Interfaces for Information Search
Abstract
Recent progress in machine learning has given rise to a plethora of tools and applications that rely on conversational interactions, from chatbots, speech-controlled devices to robots and virtual agents. Conversational interfaces are becoming widely accepted for utility tools, where a common function is to serve users’ information needs. Albeit with much excitement, we are only starting to understand how users’ information-seeking behaviors and design opportunities may transform moving from traditional graphical user interfaces to conversational user interfaces. In this chapter, we start by reviewing recent work in the emerging area of conversational interfaces and lay out their opportunities for supporting information search tasks. We then present insights from our experience deploying a chatbot supporting information search in a large enterprise, demonstrating how a conversational interface impacts user behaviors and offers new opportunities for improving search experience, in particular for user modeling.
Q. Vera Liao, Werner Geyer, Michael Muller, Yasaman Khazaen
Metadata
Title
Understanding and Improving Information Search
Editors
Wai Tat Fu
Herre van Oostendorp
Copyright Year
2020
Electronic ISBN
978-3-030-38825-6
Print ISBN
978-3-030-38824-9
DOI
https://doi.org/10.1007/978-3-030-38825-6