Assessing Visualization Techniques for the Search Process in Digital Libraries

In this paper we present an overview of several visualization techniques to support the search process in Digital Libraries (DLs). The search process typically can be separated into three major phases: query formulation and refinement, browsing through result lists and viewing and interacting with documents and their properties. We discuss a selection of popular visualization techniques that have been developed for the different phases to support the user during the search process. Along prototypes based on the different techniques we show how the approaches have been implemented. Although various visualizations have been developed in prototypical systems very few of these approaches have been adapted into today's DLs. We conclude that this is most likely due to the fact that most systems are not evaluated intensely in real-life scenarios with real information seekers and that results of the interesting visualization techniques are often not comparable. We can say that many of the assessed systems did not properly address the information need of cur-rent users.Comment: 23 pages, 14 figures, pre-print to appear in "Wissensorganisation mit digitalen Technologien" (deGruyter

Learning Visual Importance for Graphic Designs and Data Visualizations

Knowing where people look and click on visual designs can provide clues about how the designs are perceived, and where the most important or relevant content lies. The most important content of a visual design can be used for effective summarization or to facilitate retrieval from a database. We present automated models that predict the relative importance of different elements in data visualizations and graphic designs. Our models are neural networks trained on human clicks and importance annotations on hundreds of designs. We collected a new dataset of crowdsourced importance, and analyzed the predictions of our models with respect to ground truth importance and human eye movements. We demonstrate how such predictions of importance can be used for automatic design retargeting and thumbnailing. User studies with hundreds of MTurk participants validate that, with limited post-processing, our importance-driven applications are on par with, or outperform, current state-of-the-art methods, including natural image saliency. We also provide a demonstration of how our importance predictions can be built into interactive design tools to offer immediate feedback during the design process

Visual articulation of navigation and search systems for digital libraries

Journal and digital library portals are the information systems that researchers turn to most frequently for undertaking and disseminating their academic work. However, their interfaces have not been improved. We propose an articulation of the navigation and search systems in a single visual solution that would allow the simultaneous exploration and interrogation of the information system. Area is a low-cost visualization tool that is easy to implement, and which can be used with large collections of documents. Moreover, it has a short learning curve that enhances both user-experience and user-satisfaction with journal and digital library websites

How people recognize previously seen Web pages from titles, URLs and thumbnails

The selectable lists of pages offered by web browsers ’ history and bookmark facilities ostensibly make it easier for people to return to previously visited pages. These lists show the pages as abstractions, typically as truncated titles and URLs, and more rarely as small thumbnail images. Yet we have little knowledge of how recognizable these representations really are. Consequently, we carried out a study that compared the recognizability of thumbnails between various image sizes, and of titles and URLs between various string sizes. Our results quantify the tradeoff between the size of these representations and their recognizability. These findings directly contribute to how history and bookmark lists should be designed

This image smells good: Effects of image information scent in search engine results pages

Users are confronted with an overwhelming amount of web pages when they look for information on the Internet. Current search engines already aid the user in their information seeking tasks by providing textual results but adding images to results pages could further help the user in judging the relevance of a result. We investigated this problem from an Information Foraging perspective and we report on two empirical studies that focused on the information scent of images. Our results show that images have their own distinct "smell" which is not as strong as that of text. We also found that combining images and text cues leads to a stronger overall scent. Surprisingly, when images were added to search engine results pages, this did not lead our participants to behave significantly differently in terms of effectiveness or efficiency. Even when we added images that could confuse the participants' scent, this had no significantly detrimental impact on their behaviour. However, participants expressed a preference for results pages which included images. We discuss potential challenges and point to future research to ensure the success of adding images to textual results in search engine results pages. © 2011 ACM

From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Semi-Automatic, Inline and Collaborative Web Page Code Curations

Software developers spend about a quarter of their workday using the web to fulfill various information needs. Searching for relevant information online can be time-consuming, yet acquired information is rarely systematically persisted for later reference. In this work, we introduce SALI, an approach for semi-automated linking web pages to source code locations inline with the source code. SALI helps developers naturally capture high-quality, explicit links between web pages and specific source code locations by suggesting links for curation within the IDE. Through two laboratory studies, we examined the developer’s ability to both curate and consume links between web pages and specific source code locations while performing software development tasks. The studies were performed with 20 subjects working on realistic software change tasks from widely-used open-source projects. Results showed that developers continuously and concisely curate web pages at meaningful locations in the code with little effort. Additionally, we showed that other developers could use these curations while performing new and different change tasks to speed up relevant information gathering within unfamiliar codebases by a factor of 2.4

Visualization in information retrieval: Standards, trends and limitations

The evolution of the information retrieval discipline has not been sensitive to developing the display of results. In many cases, the results presentation is as important as the selection of the retrieved documents in satisfying the user’s information needs. However, it is possible to identify a number of standard models and certain trends in the visual presentation of results in a retrieval system. This study analyzed the patterns and trends and established a series of requirements (architectural and semantic) as a guide for improving the functionality of visualization tools in the retrieval processes