How people find videos

At present very little is known about how people locate and view videos 'in the wild'. This study draws a rich picture of everyday video seeking strategies and video information needs, based on an ethnographic study of New Zealand university students. These insights into the participants' activities and motivations suggest potentially useful facilities for a video digital library

Finding video on the web

At present very little is known about how people locate and view videos. This study draws a rich picture of everyday video seeking strategies and video information needs, based on an ethnographic study of New Zealand university students. These insights into the participants’ activities and motivations suggest potentially useful facilities for a video digital library

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

Citation chain aggregation: An interaction model to support citation cycling

This is the postprint version of the conference paper.Citation chaining is a powerful means of exploring the academic literature. Starting from just one or two known relevant items, a naïve researcher can cycle backwards and forwards through the citation graph to generate a rich overview of key works, authors and journals relating to their topic. Whilst online citation indexes greatly facilitate this process, the size and complexity of the search space can rapidly escalate. In this paper, we propose a novel interaction model called citation chain aggregation (CCA). CCA employs a simple three-list view which highlights the overlaps that occur between the first-generation relations of known relevant items. As more relevant articles are identified, differences in the frequencies of citations made by or to unseen articles provide strong relevance feedback cues. The benefits of this technique are illustrated using a simple case study

On Birthing Dancing Stars: The Need for Bounded Chaos in Information Interaction

While computers causing chaos is acommon social trope, nearly the entirety of the history of computing is dedicated to generating order. Typical interactive information retrieval tasks ask computers to support the traversal and exploration of large, complex information spaces. The implicit assumption is that they are to support users in simplifying the complexity (i.e. in creating order from chaos). But for some types of task, particularly those that involve the creative application or synthesis of knowledge or the creation of new knowledge, this assumption may be incorrect. It is increasingly evident that perfect order—and the systems we create with it—support highly-structured information tasks well, but provide poor support for less-structured tasks.We need digital information environments that help create a little more chaos from order to spark creative thinking and knowledge creation. This paper argues for the need for information systems that offerwhat we term ‘bounded chaos’, and offers research directions that may support the creation of such interface

EGO: a personalised multimedia management tool

The problems of Content-Based Image Retrieval (CBIR) sys- tems can be attributed to the semantic gap between the low-level data representation and the high-level concepts the user associates with images, on the one hand, and the time-varying and often vague nature of the underlying information need, on the other. These problems can be addressed by improving the interaction between the user and the system. In this paper, we sketch the development of CBIR interfaces, and introduce our view on how to solve some of the problems of the studied interfaces. To address the semantic gap and long-term multifaceted information needs, we propose a "retrieval in context" system. EGO is a tool for the management of image collections, supporting the user through personalisation and adaptation. We will describe how it learns from the user's personal organisation, allowing it to recommend relevant images to the user. The recommendation algorithm is detailed, which is based on relevance feedback techniques

Book selection behavior in the physical library: implications for ebook collections

Little is known about how readers select books, whether they be print books or ebooks. In this paper we present a study of how people select physical books from academic library shelves. We use the insights gained into book selection behavior to make suggestions for the design of ebook-based digital libraries in order to better facilitate book selection behavior

Visualizing Research Digital Libraries with Open Standards

Large-scale research Digital Libraries (DLs) contain a large array of potentially useful metadata. Yet, many popular DLs do not provide a convenient way to navigate the metadata or to visualize classification schema in the user session. For example, in the broad world of Management Information Systems (MIS) research, a high-level overview of MIS topics and their inter-relationships would be useful to navigate a MIS DL before zooming in on a specific article. To address this obstacle, this paper describes a prototype, the Technical Report Visualizer System (TRV), which uses a wide variety of open standards to show DL classification metadata in the navigation interface. The system captures MIS article metadata from the Open Archives Initiative (OAI) compliant arXiv e-Print archive at Cornell University. The OAI Protocol for Metadata Harvesting (OAI-PMH) is used to collect the topic metadata; the articles\u27 Association for Computing Machinery\u27s (ACM) Computing Classification System codes. We display the topic metadata in a Java hyperbolic tree and make use of XML conceptual product and implementation product standards and specifications, such as the Dublin Core and BiblioML bibliographic metadata sets, XML Topic Maps, Xalan and Xerces, to link user navigation activity to the abstracts and full text contents of the articles. We discuss the flexibility and convenience of XML standards and link this effort to related digital library visualization approaches. Keywords

MEDQUAL: Improving Medical Web Search over Time with Dynamic Credibility Heuristics

Performing a search on the World Wide Web (WWW) and traversing the resulting links is an adventure in which one encounters both credible and incredible web pages. Search engines, such as Google, rely on macroscopic Web topology patterns and even highly ranked 'authoritative' web sites may be a mixture of informed and uninformed opinions. Without credibility heuristics to guide the user in a maze of facts, assertions, and inferences, the Web remains an ineffective knowledge delivery platform. This report presents the design and implementation of a modular extension to the popular Google search engine, MEDQUAL, which provisions both URL and content-based heuristic credibility rules to reorder raw Google rankings in the medical domain. MEDQUAL, a software system written in Java, starts with a bootstrap configuration file which loads in basic heuristics in XML format. It then provides a subscription mechanism so users can join birds of feather specialty groups, for example Pediatrics, in order to load specialized heuristics as well. The platform features a coordination mechanism whereby information seekers can effectively become secondary authors, contributing by consensus vote additional credibility heuristics. MEDQUAL uses standard XML namespace conventions to divide opinion groups so that competing groups can be supported simultaneously. The net effect is a merger of basic and supplied heuristics so that the system continues to adapt and improve itself over time to changing web content, changing opinions, and new opinion groups. The key goal of leveraging the intelligence of a large-scale and diffuse WWW user community is met and we conclude by discussing our plans to develop MEDQUAL further and evaluate it