BibSonomy publications for /user/brusilovsky/information-visualizationWed Jul 01 11:12:30 CEST 2009Essex, UKTheor. Comput. Sci.January2547--571Integrating information visualization and retrieval for WWW information discovery2922003adaptive-search information-visualization Wed Jul 01 11:12:30 CEST 2009Workshop on Social Navigation and Community-Based Adaptation Technologies at AH'2006A Two-Level Adaptive Visualization for Information Access to Open-Corpus Educational Resource2006e-learning implicit-feedback information-visualization snc\_bat2006 social-navigation The labyrinthine abundance of educational resources on the Web has greatly expanded the challenge of helping students find, organize, and use resources that will best match their individual goals, interests, and current knowledge. Map-based navigation, using technologies such as the Self-Organizing Maps (SOM), is one solution to this growing challenge. However, as the number of documents organized by SOM increases, the number of documents within each cell becomes too large for the user to make meaningful choices, overwhelming his ability to make accurate decisions. Combining interactivity with the ability to organize a large number of documents, we have developed two-level heterogeneous maps that are augmented with social navigation support. We implemented our idea within the Knowledge Sea II system and ran a pilot study using this system in an Information Retrieval course.Wed Jul 01 11:12:30 CEST 2009New York, NY, USACHI '01: Proceedings of the SIGCHI conference on Human factors in computing systems277--284Optimizing search by showing results in context2001information-retrieval information-visualization Wed Jul 01 11:12:30 CEST 2009New York, NY, USACHI '05: Proceedings of the SIGCHI conference on Human factors in computing systems131--140Findex: search result categories help users when document ranking fails2005information-retrieval information-visualization Wed Jul 01 11:12:30 CEST 2009New York, NY, USAAVI '06: Proceedings of the working conference on Advanced visual interfaces396--403Improving list revisitation with ListMaps2006information-visualization navigation-support social-navigation Wed Jul 01 11:12:30 CEST 2009New York, NY, USACHI '99: Proceedings of the SIGCHI conference on Human factors in computing systems481--488The reader's helper: a personalized document reading environment1999annotation information-retrieval information-visualization personalization Wed Jul 01 11:12:30 CEST 2009Washington, DC, USAIV '04: Proceedings of the Information Visualisation, Eighth International Conference on (IV'04)465--470Using Information Visualization for Accessing Learning Object Repositories2004digital-library information-retrieval information-visualization Wed Jul 01 11:12:30 CEST 2009dg.o2005: Proceedings of the 2005 national conference on Digital government research179--188Evaluation and evolution of a browse and search interface: relation browser2005information-retrieval information-visualization Wed Jul 01 11:12:30 CEST 2009: On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops1050--1061Ontological Distance Measures for Information Visualisation on Conceptual Maps2006concept-map information-visualization Wed Jul 01 11:12:30 CEST 2009Visualization and Computer Graphics, IEEE Transactions on5981--988A Novel Visualization Model for Web Search Results122006information-retrieval information-visualization This paper presents an interactive visualization system, named WebSearchViz, for visualizing the Web search results and facilitating users' navigation and exploration. The metaphor in our model is the solar system with its planets and asteroids revolving around the sun. Location, color, movement, and spatial distance of objects in the visual space are used to represent the semantic relationships between a query and relevant Web pages. Especially, the movement of objects and their speeds add a new dimension to the visual space, illustrating the degree of relevance among a query and Web search results in the context of users' subjects of interest. By interacting with the visual space, users are able to observe the semantic relevance between a query and a resulting Web page with respect to their subjects of interest, context information, or concern. Users' subjects of interest can be dynamically changed, redefined, added, or deleted from the visual spaceWed Jul 01 11:12:30 CEST 2009Proceedings of the IJCAI'03 Workshop on Artificial Intelligence, Information Access, and Mobile ComputingAugust59--64Website Navigation and Profiling Based on Self-organising Maps2003information-visualization som Wed Jul 01 11:12:30 CEST 2009Thousand Oaks, CA, USAJ. Inf. Sci.February163--77A connectionist and multivariate approach to science maps: the SOM, clustering and MDS applied to library and information science research322006information-map information-visualization som Wed Jul 01 11:12:30 CEST 2009New York, NY, USADL '98: Proceedings of the third ACM conference on Digital libraries303--304Information forage through adaptive visualization1998information-exploration information-visualization neural-network self-organized som Wed Jul 01 11:12:30 CEST 2009SOFSEM 2008: Theory and Practice of Computer Science672--683Visual Exploration of RDF Data2008information-visualization ontology We have developed and implemented [1,2] infrastructure and RDF storage for the Semantic Web. When we filled it with data the need for some tool that could explore the data became evident. Unfortunately, none of existing solutions fulfills requirements imposed by the data and users expectations. This paper presents our RDF visualizer that was designed specifically to handle large RDF data by means of incremental navigation. A detailed description of the algorithm is given as well as actual results produced by the visualizer.Wed Jul 01 11:12:30 CEST 2009Washington, DC, USAINFOVIS '04: Proceedings of the IEEE Symposium on Information Visualization9--16User Experiments with Tree Visualization Systems2004hierarchy information-visualization This paper describes a comparative experiment with five well-known tree visualization systems, and Windows Explorer as a baseline system. Subjects performed tasks relating to the structure of a directory hierarchy, and to attributes of files and directories. Task completion times, correctness and user satisfaction were measured, and video recordings of subjects\'{y} interaction with the systems were made. Significant system and task type effects and an interaction between system and task type were found. Qualitative analyses of the video recordings were thereupon conducted to determine reasons for the observed differences, resulting in several findings and design recommendations as well as implications for future experiments with tree visualization systems.Wed Jul 01 11:12:30 CEST 2009New York, NY, USACHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems1085--1088PeerChooser: visual interactive recommendation2008dlpaws en information-exploration information-visualization recommender Collaborative filtering (CF) has been successfully deployed over the years to compute predictions on items based on a user's correlation with a set of peers. The black-box nature of most CF applications leave the user wondering how the system arrived at its recommendation. This note introduces PeerChooser, a collaborative recommender system with an interactive graphical explanation interface. Users are provided with a visual explanation of the CF process and opportunity to manipulate their neighborhood at varying levels of granularity to reflect aspects of their current requirements. In this manner we overcome the problem of redundant profile information in CF systems, in addition to providing an explanation interface. Our layout algorithm produces an exact, noiseless graph representation of the underlying correlations between users. PeerChooser's prediction component uses this graph directly to yield the same results as the benchmark. User's then improve on these predictions by tweaking the graph to their current requirements. We present a user-survey in which PeerChooser compares favorably against a benchmark CF algorithm.Wed Jul 01 11:12:30 CEST 2009New York, NY, USACHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems1217--1226An exploratory study of visual information analysis2008empirical-study information-analysis information-visualization To design information visualization tools for collaborative use, we need to understand how teams engage with visualizations during their information analysis process. We report on an exploratory study of individuals, pairs, and triples engaged in information analysis tasks using paper-based visualizations. From our study results, we derive a framework that captures the analysis activities of co-located teams and individuals. Comparing this framework with existing models of the information analysis process suggests that information visualization tools may benefit from providing a flexible temporal flow of analysis actions.Wed Jul 01 11:12:30 CEST 2009New York, NY, USACHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems1237--1246Supporting the analytical reasoning process in information visualization2008en information-analysis information-visualization japaws This paper presents a new information visualization framework that supports the analytical reasoning process. It consists of three views - a data view, a knowledge view and a navigation view. The data view offers interactive information visualization tools. The knowledge view enables the analyst to record analysis artifacts such as findings, hypotheses and so on. The navigation view provides an overview of the exploration process by capturing the visualization states automatically. An analysis artifact recorded in the knowledge view can be linked to a visualization state in the navigation view. The analyst can revisit a visualization state from both the navigation and knowledge views to review the analysis and reuse it to look for alternate views. The whole analysis process can be saved along with the synthesized information. We present a user study and discuss the perceived usefulness of a prototype based on this framework that we have developed.Wed Jul 01 11:12:30 CEST 2009New York, NY, USACHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems1493--1496Metrics for measuring human interaction with interactive visualizations for information analysis2008en evaluation information-analysis information-visualization There is a lack of widely-accepted metrics for evaluating analysts' experiences with interactive visualizations (IV) for information analysis. We report an approach for developing analyst-centered IV metrics that is built upon understanding the workplace needs and experiences of information analysts with respect to IVs. We derive metrics from human-computer interaction heuristics, specializing the metrics to address the characteristics of IVs and analysts. When there are no existing heuristics, analysts' needs and experiences inform new heuristics.Wed Jul 01 11:12:30 CEST 2009New York, NY, USACIKM '93: Proceedings of the second international conference on Information and knowledge management11--20InfoCrystal: a visual tool for information retrieval \& management1993information-visualization Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.