1,720,969 research outputs found
Visualising the structure of document search results: A comparison of graph theoretic approaches
No full textThis is the post-print of the article - Copyright @ 2010 Sage PublicationsPrevious work has shown that distance-similarity visualisation or ‘spatialisation’ can provide a potentially useful context in which to browse the results of a query search, enabling the user to adopt a simple local foraging or ‘cluster growing’ strategy to navigate through the retrieved document set. However, faithfully mapping feature-space models to visual space can be problematic owing to their inherent high dimensionality and non-linearity. Conventional linear approaches to dimension reduction tend to fail at this kind of task, sacrificing local structural in order to preserve a globally optimal mapping. In this paper the clustering performance of a recently proposed algorithm called isometric feature mapping (Isomap), which deals with non-linearity by transforming dissimilarities into geodesic distances, is compared to that of non-metric multidimensional scaling (MDS). Various graph pruning methods, for geodesic distance estimation, are also compared. Results show that Isomap is significantly better at preserving local structural detail than MDS, suggesting it is better suited to cluster growing and other semantic navigation tasks. Moreover, it is shown that applying a minimum-cost graph pruning criterion can provide a parameter-free alternative to the traditional K-neighbour method, resulting in spatial clustering that is equivalent to or better than that achieved using an optimal-K criterion
Exploring cognitive issues in visual information retrieval
No full textA study was conducted that compared user performance across a range of search tasks supported by both a textual and a visual information retrieval interface (VIRI). Test scores representing seven distinct cognitive abilities were examined in relation to user performance. Results indicate that, when using VIRIs, visual-perceptual abilities account for significant amounts of within-subjects variance, particularly when the relevance criteria were highly specific. Visualisation ability also seemed to be a critical factor when users were
required to change topical perspective within the visualisation. Suggestions are made for navigational cues that may help to reduce the effects of these individual differences
Visualising and animating visual information foraging in context
No full textOptimal information foraging provides a potentially useful framework for modelling, analysing, and interpreting search strategies of users through a spatial-semantic interface. Improving the understanding of behavioural patterns of users in such environments has implications for the design and refinement of a range of user interfaces. In this article, we outline the role of optimal information foraging in the study of visual information retrieval and how one may use visualisation and animation techniques to put behavioural patterns in context. Behavioural patterns of information
foraging in an information space are visualised and animated to aid further in-depth analysis of search strategies
A study of navigation strategies in spatial-semantic visualizations
No full textVisualisations of abstract data are believed to assist the searcher by providing an overview of the semantic structure of a document collection whereby semantically similar items tend to cluster in space. Cribbin and Chen (2001) found that similarity data represented using minimum spanning tree (MST) graphs provided greater levels of support to users when conducting a range of information seeking tasks, in comparison to simple scatter graphs. MST graphs emphasise the most salient relationships between nodes by means of connecting links. This paper is based on the premise that it is the provision of these links that facilitated search performance. Using a combination of visual observations and existing theory, hypotheses predicting navigational strategies afforded by the MST link structure are presented and tested. The utility, in terms of navigational efficiency and retrieval success, of these and other observed strategies is then examined
Advanced modelling and visualisation of liquid-liquid separations of complex sample components, with variable phase distribution and mode of operation
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research is about liquid-liquid chromatography modelling. While the main focus was on liquid-liquid chromatography, where the stationary and mobile phases are both liquid, theory of different types of chromatography, including the currently most used techniques, were considered as well. The main goal of this research was to develop a versatile liquid-liquid separation model, able to model all potential operating scenarios and modes of operation. A second goal was to create effective and usable interfaces to such a model, implying primarily information visualisation, and secondarily educative visualisation. The first model developed was a model based on Counter-Current Distribution. Next a new more elemental model was developed, the probabilistic model, which better models continuous liquid-liquid chromatography
techniques. Finally, a more traditional model was developed using transport theory. These models were used and compared to experimental data taken from literature. The models were demonstrated to model all main liquid-liquid chromatography techniques, incorporated the different modes of operation, and were able to accurately model many sample components and complex sample injections. A model interface was developed, permitting functional and effective model configuration, exploration and analysis using visualisation and interactivity. Different versions of the interface were then evaluated using questionnaires, group interviews and Insight Evaluation. The visualisation and interactivity enhancements have proven to contribute understanding and insight of the underlying chromatography process. This also proved the value of the Insight Evaluation method, providing valuable qualitative evaluation results desired for this model interface evaluation. A prototype of a new graphical user interface developed, and showed great potential for combining model parameter input and exploring the liquid-liquid chromatography processes. Additionally, a new visualisation method was developed that can accurately visualise different modes of operation. This was used to create animations, which were also evaluated. The results of this evaluation show the new visualisation helps understanding of the liquid-liquid chromatography process amongst CCC novices. The model software will be a valuable tool for industry for predicting, evaluating and validating experimental
separations and production processes. While effective models already existed, the use of
interactive visualisation permits users to explore the relationship between parameters and performances in a simpler yet more powerful way. It will also be a valuable tool for academia for teaching & training, both staff and students, on how to use the technology. Prior to this work no such tool existed or existing tools were limited in their accessibility and educational value.This study was supported by Brunel University and the Royal Academy of Engineering
Citation chain aggregation: An interaction model to support citation cycling
No full textThis 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
Discovering latent topical structure by second-order similarity analysis
No full textThis is the post-print of the Article - Copyright @ 2011 ASIS&TDocument similarity models are typically derived from a term-document vector space representation by comparing all vector-pairs using some similarity measure. Computing similarity directly from a ‘bag of words’ model can be problematic because term independence causes the relationships between synonymous and related terms and the contextual influences that determine the ‘sense’ of polysemous terms to be ignored. This paper compares two methods that potentially address these problems by modelling the higher-order relationships that lie latent within the original vector space. The first is latent semantic analysis (LSA), a dimension reduction method which is a well known means of addressing the vocabulary mismatch problem in information retrieval systems. The second is the lesser known, yet conceptually simple approach of second-order similarity (SOS) analysis, where similarity is measured in terms of profiles of first-order similarities as computed directly from the term-document space. Nearest neighbour tests show that SOS analysis produces similarity models that are consistently better than both first-order and LSA derived models at resolving both coarse and fine level semantic clusters. SOS analysis has been criticised for its cubic complexity. A second contribution is the novel application of vector truncation to reduce the run-time by a constant factor. Speed-ups of four to ten times are found to be easily achievable without losing the structural benefits associated with SOS analysis
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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