Online digital library searchers who find themselves engaged in multiple concurrent complex search tasks may encounter potentially serendipitous information for one task while pursuing another. This can propel them in unexpected and exciting directions that enhance their knowledge. However, existing search interfaces provide limited support for searchers to handle such serendipitous information encounters, forcing them into an often disruptive choice between continuing their current search or pursuing the new discovery. To address this issue, we introduce Revelio: an academic digital library search interface based on a ‘save now, organize later’ workflow. Revelio provides a low-effort mechanism for deferring potentially serendipitous information encounters, and a semantic similarity approach for subsequently reviewing and saving such search results within a multi-workspace structure. We evaluated Revelio in a between-subjects controlled study with 28 participants using a novel experimental design that creates the opportunity for serendipitous information encounters within a concurrent complex academic search task context. Compared to those who used a baseline search interface, participants who used Revelio were able to effectively defer and subsequently review encountered information, resulting in positive opinions about the interface, increased performance in both prescribed search tasks, and greater perceived knowledge gain. These findings demonstrate the value of search interfaces that explicitly support the deferral and subsequent review of potentially serendipitous information.

The rapid development of artificial intelligence (AI) is reshaping how people seek, access, and use information, with significant implications for researchers, educators, and students. Increasingly, academic search engines, bibliographic databases, and digital libraries are integrating AI features, including generated and synthesized content, conversational interfaces, and intelligent recommendation. These tools promise to support discovery, synthesis, and learning, yet they also raise critical questions about search integrity, fairness, accountability, transparency, and ethics (FATE). In academic contexts, where reliability and credibility are paramount, the design and use of AI-mediated search systems require novel ideas and approaches. Building on previous work in interactive information retrieval (IIR), search as learning, and search user interface design, this workshop invites the CHIIR community to examine opportunities and challenges in developing and using AI-powered academic search systems for research and higher education.

When undertaking complex search tasks that cannot be completed in a single session, resuming the search task can be challenging. When the search is conducted over multiple platforms, this challenge increases. While aggregated search interfaces support the synthesis of search results from multiple sources, cross-session support in such settings remains underexplored. In this research, we study a set of novel workspace approaches to this problem, within a digital humanities search context. We introduce an interactive cluster refinement (ICR) workspace that automatically organizes saved resources using thematic clustering, preserves their provenance, and provides an interactive method for refining the cluster to match the searcher’s mental model. Building on this foundation, we investigate two augmentations to facilitate reacquaintance with previous search activities: interactive passage highlighting (ICR+IPH), which lets searchers mark salient passages as a reminder of why resources were saved; and AI-generated summarization (ICR+AIS), which produces concise overviews of saved resources with inline citations. We combine these together into a fourth interface (ICR+IPH+AIS), where the AI-generated summarization is instructed to make use of the passage highlighting. We conducted a cross-session laboratory study with n = 36 participants to compare these interface alternatives with respect to measures of utility, perceived value, metacognition, exploratory search behaviour, and cross-session support. Both ICR+IPH and ICR+AIS improved outcomes relative to ICR. The combined ICR+IPH+AIS interface was most effective in enabling cross-session searching, yielding faster task resumption, higher resource precision, greater perceived value and knowledge gain, and stronger support for metacognitive planning and evaluation as well as exploratory search outcomes.

Students often face complex academic search tasks, which cannot be resolved with a single query and selecting among the top few search results, or a single answer provided by a generative AI interface. Exploratory search process have been proposed as a useful framework for enabling searchers to undertake complex search tasks. In recent years, a variety of interfaces have been developed to support such searching. While such approaches generally focus on enabling searchers to make sense of what has been found and supporting them in managing their search activities, an underlying assumption is that searchers have good reading skills, working memory, and attention. However, these assumptions do not hold for all users; there can be a wide range of neurodiversity among students with respect to these important cognitive functions. Some searchers, such as those with dyslexia, need more support in some or all of these aspects than academic search interfaces offer. Taking inspiration from prior research on multi-workspace search environments, visually representing histories of past search activities, tag-based approaches to saving search results, interactive mechanisms for filtering what has been saved, and accessibility, we have developed a novel approach we call SearchPath. Herein we explain the key features of SearchPath, highlighting how they have been chosen and fine-tuned to serve as interactive memory aids that can help students with dyslexia to maintain orientation during their search journey.

Exploratory search has been proposed as a model of search behaviour that is well suited to complex search scenarios.However, the simple interfaces that are commonplace across many search contexts limit the ability for searchers to undertake exploratory searches.Little support is provided for the discovery, learning, and investigation necessary for exploratory browsing, or the query (re)formulation, result examination, and information extraction required for focused searching.While the design and study of search interfaces that accommodate and support searchers in undertaking exploratory searches has increased in recent years, much of this work has been ad hoc in nature.In this perspective paper, five search interface design principles are presented that are specifically tuned to support exploratory search.An extension of the classical heuristic evaluation method is provided to support the inspection of prototype search interfaces with respect to the design principles.Recent research in the field is categorized according to these design principles.Patterns and gaps in the literature are identified, highlighting opportunities for further research on exploratory search interfaces.These principles provide a framework to guide the design and inspection of future search interfaces to support exploratory search, as well as a mechanism for comparing and contrasting the interactive information retrieval literature as it relates to supporting exploratory search through novel interface design.

Interactive Information Retrieval (IIR) interfaces are typically evaluated using questionnaires that gather post-task subjective measures such as ease of use, usefulness, satisfaction, and user engagement, along with in-task objective measures derived from log analysis.However, a comprehensive evaluation requires a deeper understanding of user behaviour beyond such traditional measures.Integrating eye tracking data with logged feature use and emotional valence provides a multimodal approach to evaluating a search interface at the feature level.To validate this approach, we examined three search interfaces in a controlled laboratory study focused on exploratory search within the context of digital humanities archives.A key benefit of this multimodal approach is that it allows us to evaluate both traditional interaction with the search interface (looking at a feature, using it, and experiencing an emotional response) as well as passive interaction with the search interface (looking at a feature, choosing not to use it but possibly getting information from it, and experiencing an emotional response).Using this approach, we were able to identify specific features of the interfaces that generated positive and negative emotional valence responses when used, as well as features that generated such emotional valence responses when viewed but not used.Such feature-level assessments would be difficult to capture using other means, providing insight into the nature of the searchers' experiences using the search interfaces.

Interactive information retrieval (IIR) interfaces are commonly evaluated using questionnaires that collect post-task subjective measures such as satisfaction, ease of use, usefulness, and user engagement. Although the importance of measuring emotional responses during the search process has been recognized, incorporating this aspect into IIR user studies has been challenging. We have developed a novel method to capture real-time emotional responses based on advances in facial emotion classification approaches. We utilize consumer-grade front-facing cameras to collect emotional responses, which synchronize with the user’s interactions with the search interface. In a controlled laboratory study, the relevance of search results was manipulated to validate the approach’s effectiveness and explore how search results’ relevance impacts users’ emotional responses, post-task evaluations of the search interface, and interactions with search interface features. This enabled us to examine whether we could detect emotional responses, whether recency effects were observed in post-task evaluations, and whether feature use correlated with emotional responses. The study was conducted in the context of exploratory search within an academic digital library. The results of this study demonstrate that both positive and negative emotional responses can be reliably detected during the search process. There is evidence of recency effects in post-task measures, and the study identifies specific interactive features used during the experience of positive and negative emotional responses. This serves as a foundation for the use of emotional responses to supplement post-task survey data when evaluating search interfaces. • Real-time emotion detection in IIR interfaces. • Recency effects observed in post-task subjective measures. • Correlation between emotional responses and post-task evaluations. • Emotional responses variation across search interface features. • Emotions in exploratory search within academic digital libraries.

Abstract Searching across diverse information platforms, such as digital humanities archives, academic digital libraries, and encyclopedias, poses challenges in managing the queries issued to each platform and synthesizing the resources discovered. While search result aggregation interfaces address this problem, how best to present the search results from different platforms in the search engine results page remains an open question. In this research, we implemented three common approaches and developed a new technique for aggregating search results across three platforms: Europeana, our University's academic library, and Wikipedia. The three common approaches (1) use tabs to switch between the platforms, (2) interleave results from each platform producing a single list, and (3) use a bento box approach to group results from each platform. The new technique organizes the search results into thematic clusters irrespective of their source platform. We designed a controlled laboratory study using a within‐subjects design and exploratory search tasks conducted in the context of digital humanities searching. We collected data from 32 student participants, focusing on utility, perceived value, and diversity of saved resources. This study provides evidence that thematic clustering can be a beneficial aggregation approach, opening opportunities for studying different ways of representing and visualizing aggregated search results.

Abstract When undertaking complex search scenarios, the underlying information need cannot be satisfied by finding a single optimal resource; instead, searchers need to engage in exploratory search processes to find multiple resources by iteratively revising and reformulation their queries. This process of query refinement is particularly challenging when using a mobile device, where typing is difficult. Furthermore, in mobile search contexts interruptions can lead to searchers losing track of what they were doing. To address these challenges, we designed a public digital library search interface for mobile devices that includes two novel features: drag‐and‐drop query refinement and query history visualization. To assess the value of this interface compared to a typical baseline, we conducted a controlled laboratory study with 32 participants that included pursuing complex search scenarios, being interrupted in the midst of the search, and resuming the search after the interruption. While participants took more time, they generated longer queries and reported positive subjective opinions about the usability of the exploratory search and task resumption features, along with a greater increase in certainty. These findings show the value of leveraging new touch‐based interaction mechanisms within mobile search contexts, and the benefits that visualization can bring to supporting search task resumption.

In academic digital libraries, searchers commonly engage in exploratory search when faced with complex search tasks. An important part of exploratory search is exploratory browsing, where the focus is on search activities associated with discovery, learning, and investigation. However, these critical aspects of exploratory browsing are often not adequately supported by existing digital library search systems. In particular, they are hindered by the inability for searchers to add further information to inform their exploratory browsing style of searching. We address this issue by providing two new features: dynamic tagging of search results and an interactive workspace that allows the searcher to highlight and filter the search results using these tags. We have evaluated this approach compared to a baseline search system in a 32-participant user study. Increases in typical subjective measures were found, along with increases in perceived motivation and ability. Further, the documents saved as part of the exploratory browsing process were of higher precision when using this approach. These results show the value of providing searchers with interactive features that enable an exploratory browsing style of searching, beyond simply entering a query and selecting/saving search results.

Keywords contain important contextual information about search results within academic digital library search interfaces. However, such information tends to be underutilized within modern search interface designs. In prior work, methods for visually linking keywords between search results have been proposed and studied. In this research, we analyze the design space and propose a new approach that aggregates the keywords over all items on the search engine results page (SERP), visually linking them back to their source search result. We have created interactive and static versions of both interfaces, and conducted a controlled laboratory study to assess the impact of the interfaces on measures of utility (efficiency, effectiveness, feature use) and perceived value (usefulness, ease of use, satisfaction, user engagement, knowledge gain, and interest gain). The findings from this research show the merit of using keywords to provide summaries of documents and search result sets, the value of making keywords interactive, and the benefit of using visualization to interactively link information within a search engine results page. The differences between providing the keywords along side each document or aggregated over the entire SERP were minimal, suggesting that it does not matter how the keywords are represented as long as they can be used to interactively reveal relationships among the search results.

Conducting exploratory searches within digital libraries requires that searchers revise, refine, and reformulate their queries multiple times. Challenges that searchers of digital public libraries face include choosing how to refine their queries and making spelling or typographical errors. These are compounded when using mobile devices, where typing is time-consuming and error-prone. Conducting searches in a mobile context adds yet another challenge: the possibility of being interrupted and losing track of what was being done. In this paper we demonstrate a novel digital public library search interface tuned for mobile device use, which was designed to address these challenges through two key features: drag-and-drop query refinement and query history visualization. This work represents an example of how thoughtful search interface design and the judicious use of visualization techniques can be used to enhance exploratory search processes within digital public libraries.

Information seeking in an academic digital library is complex in nature, often spanning multiple search sessions. Resuming academic search tasks requires significant cognitive effort as searchers must re-acquaint themselves with previous search session activities and previously discovered documents before resuming their search. Further, some academic searchers may find it convenient to initiate such searches on their mobile devices during short gaps in time (e.g., between classes), and resume them later in a desktop environment when they can use the extra screen space and more convenient document storage capabilities of their computers. To support such searching, we have developed an academic digital library search interface that assists searchers in managing cross-session search tasks even when moving between mobile and desktop environments. Using a controlled laboratory study we compared our approach (Dilex) to a standard academic digital library search interface. We found increased user engagement in both the initial (mobile) and resumed (desktop) search activities, and that participants spent more time on the search results pages and had an increased degree of interaction with information and personalization features during the resumed tasks. These results provide evidence that the participants were able to make effective use of the visualization features in Dilex, which enabled them to readily resume their search tasks and stay engaged in the search activities. This work represents an example of how semi-automatic search task/session management and visualization features can support cross-session search, and how designing for both mobile and desktop use can support cross-device search.

Abstract While it is clear that using a mobile device can interrupt real‐world activities such as walking or driving, the effects of interruptions on mobile device use have been under‐studied. We are particularly interested in how the ambient distraction of walking while using a mobile device, combined with the occurrence of simulated interruptions of different levels of cognitive complexity, affect web search activities. We have established an experimental design to study how the degree of cognitive complexity of simulated interruptions influences both objective and subjective search task performance. In a controlled laboratory study (n = 27), quantitative and qualitative data were collected on mobile search performance, perceptions of the interruptions, and how participants reacted to the interruptions, using a custom mobile eye‐tracking app, a questionnaire, and observations. As expected, more cognitively complex interruptions resulted in increased overall task completion times and higher perceived impacts. Interestingly, the effect on the resumption lag or the actual search performance was not significant, showing the resiliency of people to resume their tasks after an interruption. Implications from this study enhance our understanding of how interruptions objectively and subjectively affect search task performance, motivating the need for providing explicit mobile search support to enable recovery from interruptions.

Abstract While the search interfaces used by common academic digital libraries provide easy access to a wealth of peer‐reviewed literature, their interfaces provide little support for exploratory browsing. When faced with a complex search task (such as one that requires knowledge discovery), exploratory browsing is an important first step in an exploratory search process. To more effectively support exploratory browsing, we have designed and implemented a novel academic digital library search interface (KLink Search) with two new features: visually linked keywords and an interactive workspace. To study the potential value of these features, we have conducted a controlled laboratory study with 32 participants, comparing KLink Search to a baseline digital library search interface modeled after that used by IEEE Xplore. Based on subjective opinions, objective performance, and behavioral data, we show the value of adding lightweight visual and interactive features to academic digital library search interfaces to support exploratory browsing.

Academic search tasks that are complex may require that a searcher undertake the task over the course of multiple search sessions, and possibly using multiple devices. One of the key challenges in cross-session search is resuming the previously started search task. If task resumption can be supported well in a mobile environment, we may be able to encourage academic searchers to make use of the small down-times they encounter while away from their computers (e.g., while in line at the market). If it is supported well in a desktop/laptop environment, the work that was done on a mobile device can easily be accessed and used. In this paper, we demonstrate an academic digital library search interface that supports cross-session cross-device search, using visualization approaches to support browsing and selection of past search topics, and faceted navigation features to support investigation and examination of previously saved documents.

Academic digital library searchers often employ exploratory search strategies when faced with the complex search task of finding academic literature on a topic that is new to them. Unfortunately, the interfaces employed by academic digital libraries provide little support for exploratory browsing, which is a critical first step in exploratory search. To address this shortcoming, we have designed and implemented a novel academic digital library interface (KLink Search) with two new features: visually linked keywords and an interactive workspace. Here, we present preliminary analysis of data collected in a controlled laboratory study (n=32) comparing KLink Search to a baseline interface. Participants reported higher degrees of usefulness, ease-of-use, satisfaction, and knowledge gain after using KLink Search. Participants spent more time on the search tasks, and were able to collect sets of documents that were highly relevant to the tasks. Results from this research illustrate the value of adding lightweight visual and interactive features to academic digital library search interfaces to support exploratory browsing.

Searching for images posted within social media services such as Twitter relies on matching textual queries to the contents of the posts that include the images. Unfortunately, social media posts may not always provide accurate or meaningful descriptions of the contents of the embedded images, making searching for images a challenging task. In this research, we augment the textual contents of the posts with new information extracted from the images using image processing and deep learning methods, and provide a visual interface to enable interactive image retrieval. A user study was conducted with 28 participants to collect evidence on how our approach was used in relation to Vakkari's three-stage model of information seeking. We also analyzed participants' perceptions of usefulness, ease of use, and satisfaction in comparison to a common grid-based image search interface. The results from this study highlight the value of providing visual and interactive features to enable searchers to discover images from social media sources.

An important contribution in the development of interactive information retrieval as a research discipline has been the specification of information seeking models. A variety of such models have been documented, some of which apply generally to a broad set of search settings, and others which are specific to settings such as academic search. Within the domain of academic search, it is unclear to what extent searchers employ the strategies specified in such models when faced with different types of information needs (ranging from fact verification to knowledge discovery). Using an online questionnaire that presented four different academic search scenarios, we collected data on the self-reported likelihood of researchers (professors, graduate students) to use specific strategies from each of five different information seeking models. Preliminary analysis of data from a pilot study (n=10) has revealed differences in which of the strategies are employed depending on the type of search scenario as well as the level of expertise of the searcher.

As search tasks move beyond targeted search and into the domain of complex search, a substantial cognitive burden is placed on the searcher to craft and refine their queries, evaluate and explore among the search results, and ultimately make use of what is found. In such cases, information visualization techniques may be leveraged to enable searchers to perceive, interpret, and make sense of the information available throughout the search process. This tutorial will establish the fundamental principles and theories of information visualization, explain how information visualization can support interactive information retrieval, and survey search interfaces from my own research that leverage information visualization techniques. The goal of this tutorial will be to encourage researchers to make informed design decisions for how to integrate information visualization into their own interactive information retrieval projects.

While Wikipedia is an excellent source of information about entities, discovering relationships among them is not well-supported by its search features. Lensing Wikipedia was designed as an alternate search and summarization interface, providing a set of filtering, visualization, and exploration tools that enable searching among the connections between people, organizations, and locations. In this paper, we present the results of a user study on how these features are used in each of Vakkari's stages of information seeking (pre-focus, focus formulation, and post-focus), and the participants perceptions of the utility of these features to their overall information-seeking goals. Participants primarily used input and control features during the pre-focus stage, informational and personalization features during the focus formulation stage, and personalization features during the post-focus stage. Findings from this study contribute to understanding how people use advanced search, summarization, and visualization tools to aid their information seeking tasks.

Popular user-generated content services like Twitter have made it easy for people to post and browse short messages while on the go. However, the ability to search is limited by the query box and search results list paradigm. In this paper, we propose TwIST (Twitter Information Search Tool), which has been designed to support interactive search and exploration within Twitter. TwIST is a mobile application that works in two modes: simple search and exploratory search. The searcher can easily change between these modes by rotating the device, making it easy to access the mode that will support the desired search activity. While the simple search mode is dominated by the common search results list format, the exploratory search mode uses topic modelling, visualization, and interactive filtering to support the searcher in finding the information they are seeking.

Geographic phenomena often have an intrinsic temporal component that can be an important part of answering many research questions. Geospatial applications are well developed in their ability to navigate the spatial dimension of data through zoom and pan tools, but are less developed in their temporal navigation abilities. Improved temporal navigation tools are important for achieving a simplified and more thorough analysis of spatio-temporal data. This paper presents new approaches for navigating the temporal dimension of spatio-temporal data in a multi-touch environment using temporal zoom and pan. Two approaches, Dynamic Radial Navigation and Multiple Linked Time Sliders, were implemented and tested with a user evaluation that compared them to two approaches based on more commonly available temporal navigation tools, Drop-Down List and Date/Time Spinners. Results from the user evaluation indicated that although all of the approaches were effective, there were variations in efficiency and perceptions of ease of use and usefulness. The results of the study favoured the Date/Time Spinners, even though these consumed the largest amount of display space. The participants did acknowledge the value of the visualization and interaction elements in the new approaches, but reported difficulty in using them due to their compact size. These findings illustrate the delicate balance between size, utility, and novelty, which must be carefully managed in the development of multi-touch data analysis tools.

Abstract Although information retrieval techniques used by Web search engines have improved substantially over the years, the results of Web searches have continued to be represented in simple list‐based formats. Although the list‐based representation makes it easy to evaluate a single document for relevance, it does not support the users in the broader tasks of manipulating or exploring the search results as they attempt to find a collection of relevant documents. HotMap is a meta‐search system that provides a compact visual representation of Web search results at two levels of detail, and it supports interactive exploration via nested sorting of Web search results based on query term frequencies. An evaluation of the search results for a set of vague queries has shown that the re‐sorted search results can provide a higher portion of relevant documents among the top search results. User studies show an increase in speed and effectiveness and a reduction in missed documents when comparing HotMap to the list‐based representation used by Google. Subjective measures were positive, and users showed a preference for the HotMap interface. These results provide evidence for the utility of next‐generation Web search results interfaces that promote interactive search results exploration.

TheHotMap.com is an example of a next-generation Web search interface, wherein users are able to take an active role in the Web search process. Information that can assist searchers in their Web search tasks is presented in a visual manner. The system supports user interaction both during the query refinement process, as well as the search results exploration process. This paper describes the features of TheHotMap.com; usage log analysis illustrates the benefits of supporting flexible interaction within a single unified Web search interface.

In general, Web search engines perform well for users whose information needs are well-defined. When searchers can provide specific terms that adequately describe the information they are seeking, the top search results are commonly very relevant. However, when users wish to explore a topic, little assistance is provided by Web search engines to help users in finding the information they seek. In this paper, a system that supports exploratory search through the visual specification of utility functions is presented. Users are able to recognize potentially relevant terms using a term frequency histogram, and can indicate their preferences for these in a visual manner. The search results are re-sorted based on the corresponding utility function; colour coding allows users to easily locate the selected terms within the search results list.

Users of traditional Web search engines commonly find it difficult to evaluate the results of their Web searches. We suggest the use of information visualization and interactive visual manipulation as methods for improving the ability of users to evaluate the results of a Web search. In this paper, we present the results of a user study that compared the search results interface provided by Google to that of two systems we have developed: HotMap and Concept Highlighter. We found that users were able to perform their searches faster with HotMap, were able to find more relevant documents with Concept Highlighter, and generally ranked these interfaces higher than Google with respect to subjective measures. When given a choice between these interfaces, participants ranked HotMap the highest, followed by Google and Concept Highlighter. These results indicate that even though the list-based representation of search results are common among search engines, visual and interactive interfaces to Web search results can be more efficient, effective, and satisfying to the users

It is common for Web searchers to have difficulties crafting queries to fulfil their information needs. Even when they provide a good query, users often find it challenging to evaluate the results of their Web searches. Sources of these problems include the lack of support for query refinement, and the static nature of the list-based representations of Web search results. To address these issues, we have developed WordBars, an interactive tool for Web information retrieval. WordBars visually represents the frequencies of the terms found in the first 100 document surrogates returned from the initial query. This system allows the users to interactively re-sort the search results based on the frequencies of the selected terms within the document surrogates, as well as to add and remove terms from the query, generating a new set of search results. Examples illustrate how WordBars can provide valuable support for query refinement and search results exploration, both when specific and vague initial queries are provided

It has been well documented that Web searchers have difficulties crafting queries to fulfill their information needs. In this work, we use a concept knowledge base generated from the ACM computing classification system to generate a query space that represents the query terms in relation to the concepts they describe and the other terms that are related to these concepts. A visual representation of this query space allows the user to interpret the relationships between their query terms and the query space. Interactive query refinement within this visual representation takes advantage of the user's visual information processing abilities, and allows the user to choose terms that accurately represent their information need. A preview of the search results from Google provides the user with an indication of the current state of their query refinement process. This work allows the user to take an active role in the information retrieval process, supporting the fundamental shift from information retrieval systems to information retrieval support systems.