Max L. Wilson

mSpace: improving information access to multimedia domains with multimodal exploratory search

Overview of mSpace interaction approach for presenting exploratory search particularly in the audio domain by using slices, preview cues, and user-determined organization of information from high-dimensional spaces

The evolving mSpace platform: leveraging the semantic web on the trail of the memex

Vannevar Bush proposed the memex as a means to support building knowledge in the way he says the human brain works: by association. Achieving this vision has been a core motivation for hypertext research. In this paper, we suggest first that Bushs memex reflects an interaction paradigm rather than system design. Second, we propose that Semantic Web promises to provide the mechanisms to enable these interaction requirements. Third, we propose the mSpace framework and architecture as a platform to deploy lightweight Semantic Web applications which foreground associative interaction. We propose this lightweight approach as a means to evaluate both interaction needs and the cost/benefits of using Semantic Web technologies to support them.

From Keyword Search to Exploration: Designing Future Search Interfaces for the Web

This monograph is directed at researchers and developers who are designing the next generation of web search user interfaces, by focusing on the techniques and visualizations that allow users to interact with and have control over their findings. Search is one of the keys to the Webs success. The elegant way in which search results are returned has been well researched and is usually remarkably effective. However, the body of work produced by decades of research into information retrieval continues to grow rapidly and so it has become hard to synthesize the current state-of-the-art to produce a search interface that is both highly functional, but not cluttered and distracting. Further, recent work has shown that there is substantial room for improving the support provided to users who are exhibiting more exploratory forms of search, including when users may need to learn, discover, and understand novel or complex topics. Overall, there is a recognized need for search systems to provide effective user experiences that do more than simply return results. With the aim of producing more effective search interfaces, human computer interaction researchers and web designers have been developing novel interactions and features that enable users to conveniently visualize, parse, manipulate, and organize their Web search results. For instance, while a simple set of results may produce specific information (e.g., the capital of Peru), other methods may let users see and explore the contexts of their requests for information (more about the country, city, and nearby attractions), or the properties that associate groups of information assets (grouping hotels, restaurants, and attractions by their type, district, or price). Other techniques support information-seeking processes that may last weeks or months or may even require collaboration between multiple searchers. The choice of relevant result visualization strategies in new search systems should reflect the searchers and the higher-level information needs that motivate their searches. These examples provide further motivation for supporting designers, who are challenged to synthesize and understand the breadth of advances in search, so that they can determine the benefits of varied strategies and apply them appropriately to build better systems. To support researchers and designers in synthesizing and understanding the advances in search, this monograph offers a structured means to think about web search result visualization, based on an inclusive model of search that integrates information retrieval, information seeking and a higher-level context of tasks and goals. We examine each of these levels of search in a survey of advances in browsers and related tools by defining search-related cognitive processes and analyzing innovative design approaches. We then discuss evaluations at each of these levels of search, presenting significant results and identifying both the traditional and novel means used to produce them. Based on this examination, we propose a taxonomy of search result visualization techniques that can be used to identify gaps for future research and as a reference for designers of next generation web search systems.

RepliCHI: the workshop

The replication of, or perhaps the replicability of, research is often considered to be a cornerstone of scientific progress. Yet unlike many other disciplines, like medicine, physics, or mathematics, we have almost no drive and barely any reason to consider replicating the work of other HCI researchers. Our community is driven to publish novel results in novel spaces using novel designs, and to keep up with evolving technology. The aim of this workshop is to trial a new venue that embodies the plans made in previous SIGs and panels, such that we can begin to give people an outlet to publish experiences of attempting to replicate HCI research, and challenge or confirm its findings.

Search User Interface Design

Search User Interfaces (SUIs) represent the gateway between people who have a task to complete, and the repositories of information and data stored around the world. Not surprisingly, therefore, there are many communities who have a vested interest in the way SUIs are designed. There are people who study how humans search for information, and people who study how humans use computers. There are people who study good user interface design, and people who design aesthetically pleasing user interfaces. There are also people who curate and manage valuable information resources, and people who design effective algorithms to retrieve results from them. While it would be easy for one community to reject another for their limited ability to design a good SUI, the truth is that they all can, and they all have made valuable contributions. Fundamentally, therefore, we must accept that designing a great SUI means leveraging the knowledge and skills from all of these communities. The aim of this book is to at least acknowledge, if not integrate, all of these perspectives to bring the reader into a multidisciplinary mindset for how we should think about SUI design. Further, this book aims to provide the reader with a framework for thinking about how different innovations each contribute to the overall design of a SUI. With this framework and a multidisciplinary perspective in hand, the book then continues by reviewing: early, successful, established, and experimental concepts for SUI design. The book then concludes by discussing how we can analyse and evaluate the on-going developments in SUI design, as this multidisciplinary area of research moves forwards. Finally, in reviewing these many SUIs and SUI features, the book finishes by extracting a series of 20 SUI design recommendations that are listed in the conclusions. Table of Contents: Introduction / Searcher-Computer Interaction / Early Search User Interfaces / Modern Search User Interfaces / Experimental Search User Interfaces / Evaluating Search User Interfaces / Conclusions

A comparison of techniques for measuring sensemaking and learning within participant-generated summaries

While it is easy to identify whether someone has found a piece of information during a search task, it is much harder to measure how much someone has learned during the search process. Searchers who are learning often exhibit exploratory behaviors, and so current research is often focused on improving support for exploratory search. Consequently, we need effective measures of learning to demonstrate better support for exploratory search. Some approaches, such as quizzes, measure recall when learning from a fixed source of information. This research, however, focuses on techniques for measuring open-ended learning, which often involve analyzing handwritten summaries produced by participants after a task. There are two common techniques for analyzing such summaries: a counting facts and statements and b judging topic coverage. Both of these techniques, however, can be easily confounded by simple variables such as summary length. This article presents a new technique that measures depth of learning within written summaries based on Blooms taxonomy B.S. Bloom &M.D. Engelhart, 1956. This technique was generated using grounded theory and is designed to be less susceptible to such confounding variables. Together, these three categories of measure were compared by applying them to a large collection of written summaries produced in a task-based study, and our results provide insights into each of their strengths and weaknesses. Both fact-to-statement ratio and our own measure of depth of learning were effective while being less affected by confounding variables. Recommendations and clear areas of future work are provided to help continued research into supporting sensemaking and learning.

Backward highlighting: enhancing faceted search

Directional faceted browsers, such as the popular column browser iTunes, let a person pick an instance from any column-facet to start their search for music. The expected effect is that any columns to the right are filtered. In keeping with this directional filtering from left to right, however, the unexpected effect is that the columns to the left of the click provide no information about the possible associations to the selected item. In iTunes, this means that any selection in the Album column on the right returns no information about either the Artists (immediate left) or Genres (leftmost) associated with the chosen album. Backward Highlighting (BH) is our solution to this problem, which allows users to see and utilize, during search, associations in columns to the left of a selection in a directional column browser like iTunes. Unlike other possible solutions, this technique allows such browsers to keep direction in their filtering, and so provides users with the best of both directional and non-directional styles. As well as describing BH in detail, this paper presents the results of a formative user study, showing benefits for both information discovery and subsequent retention in memory.

A longitudinal study of exploratory and keyword search

Digital libraries are concerned with improving the access to collections to make their service more effective and valuable to users. In this paper, we present the results of a four-week longitudinal study investigating the use of both exploratory and keyword forms of search within an online video archive, where both forms of search were available concurrently in a single user interface. While we expected early use to be more exploratory and subsequent use to be directed, over the whole period there was a balance of exploratory and keyword searches and they were often used together. Further, to support the notion that facets support exploration, there were more than five times as many facet clicks than more complex forms of keyword search (boolean and advanced). From these results, we can conclude that there is real value in investing in exploratory search support, which was shown to be both popular and useful for extended use of the system.

Pico-ing into the future of mobile projector phones

Ten years ago we were on the verge of having cameras built into our mobile phones, but knew very little about what to expect or how they would be used. Now we are faced with the same unknowns with mobile projector phones. This research-in-progress seeks to explore how people will want to use such technology, how they will feel when using it, and what social effects we can expect to see. This paper describes our two-phase field investigation, with results and design recommendations from its first, experience-sampling phase.

Measuring the effect of think aloud protocols on workload using fNIRS

The Think Aloud Protocol (TAP) is a verbalisation technique widely employed in HCI user studies to give insight into user experience, yet little work has explored the impact that TAPs have on participants during user studies. This paper utilises a brain sensing technique, fNIRS, to observe the effect that TAPs have on participants. Functional Near-Infrared Spectroscopy (fNIRS) is a brain sensing technology that offers the potential to provide continuous, detailed insight into brain activity, enabling an objective view of cognitive processes during complex tasks. Participants were asked to perform a mathematical task under 4 conditions: nonsense verbalisations, passive concurrent think aloud protocol, invasive concurrent think aloud protocol, and a baseline of silence. Subjective ratings and performance measures were collected during the study. Our results provide a novel view into the effect that different forms of verbalisation have on workload during tasks. Further, the results provide a means for estimating the effect of spoken artefacts when measuring workload, which is another step towards our goal of proactively involving fNIRS analysis in ecologically valid user studies.