Interactive Visualization and Navigation of Web Search Results Revealing Community Structures and Bridges

International audienceWith the information overload on the Internet, organization and visualization of web search results so as to facilitate faster access to information is a necessity. The classical methods present search results as an ordered list of web pages ranked in terms of relevance to the searched topic. Users thus have to scan text snippets or navigate through various pages before finding the required information. In this paper we present an interactive visualization system for content analysis of web search results. The system combines a number of algorithms to present a novel layout methodology which helps users to analyze and navigate through a collection of web pages. We have tested this system with a number of data sets and have found it very useful for the exploration of data. Different case studies are presented based on searching different topics on Wikipedia through Exalead's search engine

Revealing Hidden Community Structures and Identifying Bridges in Complex Networks: An Application to Analyzing Contents of Web Pages for Browsing

International audienceThe emergence of scale free and small world properties in real world complex networks has stimulated lots of activity in the field of network analysis. An example of such a network comes from the field of Content Analysis (CA) and Text Mining where the goal is to analyze the contents of a set of web pages. The Network can be represented by the words appearing in the web pages as nodes and the edges representing a relation between two words if they appear in a document together. In this paper we present a CA system that helps users analyze these networks representing the textual contents of a set of web pages visually. Major contributions include a methodology to cluster complex networks based on duplication of nodes and identification of bridges i.e. words that might be of user interest but have a low frequency in the document corpus. We have tested this system with a number of data sets and users have found it very useful for the exploration of data. One of the case studies is presented in detail which is based on browsing a collection of web pages on Wikipedia (http://en.wikipedia.org/wiki/Main_Page)

A visual analytics approach for understanding biclustering results from microarray data

Abstract Background Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from microarrays. Although biclustering can be used in any kind of classification problem, nowadays it is mostly used for microarray data classification. A large number of biclustering algorithms have been developed over the years, however little effort has been devoted to the representation of the results. Results We present an interactive framework that helps to infer differences or similarities between biclustering results, to unravel trends and to highlight robust groupings of genes and conditions. These linked representations of biclusters can complement biological analysis and reduce the time spent by specialists on interpreting the results. Within the framework, besides other standard representations, a visualization technique is presented which is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions. This microarray analysis framework (BicOverlapper), is available at http://vis.usal.es/bicoverlapper Conclusion The main visualization technique, tested with different biclustering results on a real dataset, allows researchers to extract interesting features of the biclustering results, especially the highlighting of overlapping zones that usually represent robust groups of genes and/or conditions. The visual analytics methodology will permit biology experts to study biclustering results without inspecting an overwhelming number of biclusters individually.</p

Developing an interoperable cloud-based visualization workflow for 3D archaeological heritage data. The Palenque 3D Archaeological Atlas

In archaeology, 3D data has become ubiquitous, as researchers routinely capture high resolution photogrammetry and LiDAR models and engage in laborious 3D analysis and reconstruction projects at every scale: artifacts, buildings, and entire sites. The raw data and processed 3D models are rarely shared as their computational dependencies leave them unusable by other scholars. In this paper we outline a novel approach for cloud-based collaboration, visualization, analysis, contextualization, and archiving of multi-modal giga-resolution archaeological heritage 3D data. The Palenque 3D Archaeological Atlas builds on an open source WebGL systems that efficiently interlink, merge, present, and contextualize the Big Data collected at the ancient Maya city of Palenque, Mexico, allowing researchers and stakeholders to visualize, access, share, measure, compare, annotate, and repurpose massive complex archaeological datasets from their web-browsers

Understanding the bi-directional relationship between analytical processes and interactive visualization systems

Interactive visualizations leverage the human visual and reasoning systems to increase the scale of information with which we can effectively work, therefore improving our ability to explore and analyze large amounts of data. Interactive visualizations are often designed with target domains in mind, such as analyzing unstructured textual information, which is a main thrust in this dissertation. Since each domain has its own existing procedures of analyzing data, a good start to a well-designed interactive visualization system is to understand the domain experts' workflow and analysis processes. This dissertation recasts the importance of understanding domain users' analysis processes and incorporating such understanding into the design of interactive visualization systems. To meet this aim, I first introduce considerations guiding the gathering of general and domain-specific analysis processes in text analytics. Two interactive visualization systems are designed by following the considerations. The first system is Parallel-Topics, a visual analytics system supporting analysis of large collections of documents by extracting semantically meaningful topics. Based on lessons learned from Parallel-Topics, this dissertation further presents a general visual text analysis framework, I-Si, to present meaningful topical summaries and temporal patterns, with the capability to handle large-scale textual information. Both systems have been evaluated by expert users and deemed successful in addressing domain analysis needs. The second contribution lies in preserving domain users' analysis process while using interactive visualizations. Our research suggests the preservation could serve multiple purposes. On the one hand, it could further improve the current system. On the other hand, users often need help in recalling and revisiting their complex and sometimes iterative analysis process with an interactive visualization system. This dissertation introduces multiple types of evidences available for capturing a user's analysis process within an interactive visualization and analyzes cost/benefit ratios of the capturing methods. It concludes that tracking interaction sequences is the most un-intrusive and feasible way to capture part of a user's analysis process. To validate this claim, a user study is presented to theoretically analyze the relationship between interactions and problem-solving processes. The results indicate that constraining the way a user interacts with a mathematical puzzle does have an effect on the problemsolving process. As later evidenced in an evaluative study, a fair amount of high-level analysis can be recovered through merely analyzing interaction logs

User modeling for exploratory search on the Social Web. Exploiting social bookmarking systems for user model extraction, evaluation and integration

Exploratory search is an information seeking strategy that extends be- yond the query-and-response paradigm of traditional Information Retrieval models. Users browse through information to discover novel content and to learn more about the newly discovered things. Social bookmarking systems integrate well with exploratory search, because they allow one to search, browse, and filter social bookmarks. Our contribution is an exploratory tag search engine that merges social bookmarking with exploratory search. For this purpose, we have applied collaborative filtering to recommend tags to users. User models are an im- portant prerequisite for recommender systems. We have produced a method to algorithmically extract user models from folksonomies, and an evaluation method to measure the viability of these user models for exploratory search. According to our evaluation web-scale user modeling, which integrates user models from various services across the Social Web, can improve exploratory search. Within this thesis we also provide a method for user model integra- tion. Our exploratory tag search engine implements the findings of our user model extraction, evaluation, and integration methods. It facilitates ex- ploratory search on social bookmarks from Delicious and Connotea and pub- lishes extracted user models as Linked Data

Doctor of Philosophy

dissertationWith the ever-increasing amount of available computing resources and sensing devices, a wide variety of high-dimensional datasets are being produced in numerous fields. The complexity and increasing popularity of these data have led to new challenges and opportunities in visualization. Since most display devices are limited to communication through two-dimensional (2D) images, many visualization methods rely on 2D projections to express high-dimensional information. Such a reduction of dimension leads to an explosion in the number of 2D representations required to visualize high-dimensional spaces, each giving a glimpse of the high-dimensional information. As a result, one of the most important challenges in visualizing high-dimensional datasets is the automatic filtration and summarization of the large exploration space consisting of all 2D projections. In this dissertation, a new type of algorithm is introduced to reduce the exploration space that identifies a small set of projections that capture the intrinsic structure of high-dimensional data. In addition, a general framework for summarizing the structure of quality measures in the space of all linear 2D projections is presented. However, identifying the representative or informative projections is only part of the challenge. Due to the high-dimensional nature of these datasets, obtaining insights and arriving at conclusions based solely on 2D representations are limited and prone to error. How to interpret the inaccuracies and resolve the ambiguity in the 2D projections is the other half of the puzzle. This dissertation introduces projection distortion error measures and interactive manipulation schemes that allow the understanding of high-dimensional structures via data manipulation in 2D projections

Parametric BIM-based Design Review

This research addressed the need for a new design review technology and method to express the tangible and intangible qualities of architectural experience of parametric BIM-based design projects. The research produced an innovative presentation tool by which parametric design is presented systematically. Focus groups provided assessments of the tool to reveal the usefulness of a parametric BIM-based design review method. The way in which we visualize architecture affects the way we design and perceive architectural form and performance. Contemporary architectural forms and systems are very complex, yet most architects who use Building Information Modeling (BIM) and generative design methods still embrace the two-dimensional 15th-century Albertian representational methods to express and review design projects. However, architecture cannot be fully perceived through a set of drawings that mediate our perception and evaluation of the built environment. The systematic and conventional approach of traditional architectural representation, in paper-based and slide-based design reviews, is not able to visualize phenomenal experience nor the inherent variation and versioning of parametric models. Pre-recorded walk-throughs with high quality rendering and imaging have been in use for decades, but high verisimilitude interactive walk-throughs are not commonly used in architectural presentations. The new generations of parametric and BIM systems allow for the quick production of variations in design by varying design parameters and their relationships. However, there is a lack of tools capable of conducting design reviews that engage the advantages of parametric and BIM design projects. Given the multitude of possibilities of in-game interface design, game-engines provide an opportunity for the creation of an interactive, parametric, and performance-oriented experience of architectural projects with multi-design options. This research has produced a concept for a dynamic presentation and review tool and method intended to meet the needs of parametric design, performance-based evaluation, and optimization of multi-objective design options. The concept is illustrated and tested using a prototype (Parametric Design Review, or PDR) based upon an interactive gaming environment equipped with a novel user interface that simultaneously engages the parametric framework, object parameters, multi-objective optimized design options and their performances with diagrammatic, perspectival, and orthographic representations. The prototype was presented to representative users in multiple focus group sessions. Focus group discussion data reveal that the proposed PDR interface was perceived to be useful if used for design reviews in both academic and professional practice settings