[1]
Rank As You Go: User-Driven Exploration of Search Results
Intelligent Visualizations
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di Sciascio, Cecilia
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Sabol, Vedran
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Veas, Eduardo E.
Proceedings of the 2016 International Conference on Intelligent User
Interfaces
2016-03-07
v.1
p.118-129
© Copyright 2016 ACM
Summary: Whenever users engage in gathering and organizing new information, searching
and browsing activities emerge at the core of the exploration process. As the
process unfolds and new knowledge is acquired, interest drifts occur inevitably
and need to be accounted for. Despite the advances in retrieval and recommender
algorithms, real-world interfaces have remained largely unchanged: results are
delivered in a relevance-ranked list. However, it quickly becomes cumbersome to
reorganize resources along new interests, as any new search brings new results.
We introduce uRank and investigate interactive methods for understanding,
refining and reorganizing documents on-the-fly as information needs evolve.
uRank includes views summarizing the contents of a recommendation set and
interactive methods conveying the role of users' interests through a
recommendation ranking. A formal evaluation showed that gathering items
relevant to a particular topic of interest with uRank incurs in lower cognitive
load compared to a traditional ranked list. A second study consisting in an
ecological validation reports on usage patterns and usability of the various
interaction techniques within a free, more natural setting.
[2]
Reading Through Graphics: Interactive Landscapes to Explore Dynamic Topic
Spaces
Information Visualisation
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Ulbrich, Eva
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Veas, Eduardo
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Singh, Santokh
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Sabol, Vedran
HIMI 2015: 17th International Conference on Human Interface and the
Management of Information, Symposium on Human Interface, Part I: Information
and Knowledge Design
2015-08-02
v.1
p.127-137
Keywords: Text visualisation; Dynamic information landscape; Interaction design; User
study
© Copyright 2015 Springer International Publishing Switzerland
Summary: An information landscape is commonly used to represent relatedness in large,
high-dimensional datasets, such as text document collections. In this paper we
present interactive metaphors, inspired in map reading and visual transitions,
that enhance the landscape representation for the analysis of topical changes
in dynamic text repositories. The goal of interactive visualizations is to
elicit insight, to allow users to visually formulate hypotheses about the
underlying data and to prove them. We present a user study that investigates
how users can elicit information about topics in a large document set. Our
study concentrated on building and testing hypotheses using the map reading
metaphors. The results show that people indeed relate topics in the document
set from spatial relationships shown in the landscape, and capture the changes
to topics aided by map reading metaphors.
[3]
Towards a Recommender Engine for Personalized Visualizations
Long Presentations
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Mutlu, Belgin
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Veas, Eduardo
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Trattner, Christoph
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Sabol, Vedran
Proceedings of the 2015 Conference on User Modeling, Adaptation and
Personalization
2015-06-29
p.169-182
Keywords: Personalized visualizations; Visualization recommender; Recommender systems;
Collaborative filtering; Crowd-sourcing
© Copyright 2015 Springer International Publishing Switzerland
Summary: Visualizations have a distinctive advantage when dealing with the
information overload problem: since they are grounded in basic visual
cognition, many people understand them. However, creating them requires
specific expertise of the domain and underlying data to determine the right
representation. Although there are rules that help generate them, the results
are too broad to account for varying user preferences. To tackle this issue, we
propose a novel recommender system that suggests visualizations based on (i) a
set of visual cognition rules and (ii) user preferences collected in
Amazon-Mechanical Turk. The main contribution of this paper is the introduction
and the evaluation of a novel approach called VizRec that can suggest an
optimal list of top-n visualizations for heterogeneous data sources in a
personalized manner.
[4]
VizRec: A Two-Stage Recommender System for Personalized Visualizations
Poster & Demo Session
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Mutlu, Belgin
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Veas, Eduardo
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Trattner, Christoph
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Sabol, Vedran
Companion Proceedings of the 2015 International Conference on Intelligent
User Interfaces
2015-03-29
v.2
p.49-52
© Copyright 2015 ACM
Summary: Identifying and using the information from distributed and heterogeneous
information sources is a challenging task in many application fields. Even with
services that offer well-defined structured content, such as digital libraries,
it becomes increasingly difficult for a user to find the desired information.
To cope with an overloaded information space, we propose a novel approach --
VizRec -- combining recommender systems (RS) and visualizations. VizRec
suggests personalized visual representations for recommended data. One
important aspect of our contribution and a prerequisite for VizRec are user
preferences that build a personalization model. We present a crowd based
evaluation and show how such a model of preferences can be elicited.
[5]
EDITED BOOK
Knowledge Visualization Currents: From Text to Art to Culture
/
Marchese, Francis T.
/
Banissi, Ebad
2013
n.11
p.220
Springer London
DOI: 10.1007/978-1-4471-4303-1
== Knowledge Visualization Background ==
What Is an Effective Knowledge Visualization? Insights from a Review of Seminal Concepts (3-12)
+ Eppler, Martin J.
What Is Knowledge Visualization? Eight Reflections on an Evolving Discipline (13-32)
+ Bertschi, Stefan
+ Bresciani, Sabrina
+ Crawford, Tom
+ Goebel, Randy
+ Kienreich, Wolfgang
+ Lindner, Martin
+ Sabol, Vedran
+ Moere, Andrew Vande
== Text ==
Tables and Early Information Visualization (35-61)
+ Marchese, Francis T.
Contract Clarity and Usability through Visualization (63-84)
+ Haapio, Helena
From Culture to Text to Interactive Visualization ofWine Reviews (85-110)
+ Kerren, Andreas
+ Kyusakova, Mimi
+ Paradis, Carita
== Art ==
Colorscore: Visualization and Condensation of Structure of Classical Music (113-128)
+ Hayashi, Aki
+ Itoh, Takayuki
+ Matsubara, Masaki
The Implications of David Hockney Thesis for 3D Computer Graphics (129-145)
+ Wyeld, Theodor
Practice of Using Virtual Reconstruction in the Restoration of Monumental Painting of the Church of the Transfiguration of Our Saviour on Nereditsa Hill (147-164)
+ Laska, Tatiana
+ Tsimbal, Irina
+ Golubkov, Sergey
+ Petrova, Yulia Anatolievna
== Culture ==
Mediation of Knowledge Construction of Historic Sites: Embodied Interaction + Space (167-177)
+ Deray, Kristine
+ Day, Michael
Memory, Difference, and Information: Generative Architectures Latent to Material and Perceptual Plasticity (179-197)
+ Lucia, Andrew P.
+ Sabin, Jenny E.
+ Jones, Peter Lloyd
Cultural Data Sculpting: Omnidirectional Visualization for Cultural Datasets (199-220)
+ Kenderdine, Sarah
+ Shaw, Jeffrey
+ Gremmler, Tobias
[6]
Incremental computation of information landscapes for dynamic web interfaces
Artigos resumidos
/
Sabol, Vedran
/
Syed, Kamran Ali Ahmad
/
Scharl, Arno
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Muhr, Markus
/
Hubmann-Haidvogel, Alexander
Proceedings of the 2010 Brazilian Symposium on Human Factors in Computing
Systems
2010-10-05
p.205-208
© Copyright 2010 SBC
Summary: This paper presents a technique for the visual analysis of topical shifts in
dynamically changing textual archives. Our approach is based on the well-known
information landscape metaphor, whereby topical changes are represented by
changes in landscape topography. Incremental clustering and multi-dimensional
scaling algorithms are periodically applied to a changing document set for
generating a series of information landscapes. The resulting landscapes are
suitable for dynamic Web interfaces, enabling the user to explore topical
relationships and understand topical shifts and trends in changing document
repositories.
[7]
InfoSky: Visual Exploration of Large Hierarchical Document Repositories
Human-centred computing : cognitive, social and ergonomic aspects
/
Kappe, F.
/
Droschl, G.
/
Kienreich, W.
/
Sabol, V.
/
Becker, J.
/
Andrews, K.
/
Granitzer, M.
/
Tochtermann, K.
/
Auer, P.
Proceedings of the Tenth International Conference on Human-Computer
Interaction
2003-06-22
v.3
p.1268-1272
© Copyright 2003 Lawrence Erlbaum Associates