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Scalable Set Visualizations (Dagstuhl Seminar 17332)

Yifan Hu, Luana Micallef, Martin Nöllenburg, Peter Rodgers, Marc Herbstritt
2018 Dagstuhl Reports  
During the seminar we had five invited overview talks on different aspects of set visualizations as well as a few ad-hoc presentations of ongoing work.  ...  The second part of this report contains summaries of the groups' findings.  ...  Acknowledgments Schloss Dagstuhl was the perfect place for hosting a seminar like this.  ... 
doi:10.4230/dagrep.7.8.1 dblp:journals/dagstuhl-reports/HuMNR17 fatcat:mqpltfdoqzaqfekr6yzxtprxsy

Visual Analytics for Sets over Time and Space (Dagstuhl Seminar 19192)

Sara Irina Fabrikant, Silvia Miksch, Alexander Wolff, Michael Wagner
2019 Dagstuhl Reports  
Abstracts of the talks and a report from each working group are included in this report.  ...  The goal of the seminar was to identify specific theoretical and practical problems that need to be solved in order to create dynamic and interactive set visualizations that take into account time and  ...  In particular, it was great to have the opportunity to use a separate room for each working group.  ... 
doi:10.4230/dagrep.9.5.31 dblp:journals/dagstuhl-reports/FabrikantM019 fatcat:ng3ajyjdbrhdhmb7xiiigohsde

Hypernetwork Representation Learning with the Set Constraint

Yu Zhu, Haixing Zhao
2022 Applied Sciences  
Therefore, in order to overcome the challenge of the hypernetwork structure faced by network representation learning, this paper proposes a hypernetwork representation learning method with the set constraint  ...  Experimental results demonstrate that HRSC outperforms other best baseline methods by about 1% on the MovieLens and wordnet datasets in terms of node classification, and outperforms the other best baseline  ...  Data Availability Statement: Data is contained in the article. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12052650 fatcat:pi3bboas2vgq5iwkvbibt4iepy

Radial Sets: Interactive Visual Analysis of Large Overlapping Sets

Bilal Alsallakh, Wolfgang Aigner, Silvia Miksch, Helwig Hauser
2013 IEEE Transactions on Visualization and Computer Graphics  
With a growing number of entities, the resulting element-set membership matrix becomes very rich of information about how these sets overlap.  ...  Abstract-In many applications, data tables contain multi-valued attributes that often store the memberships of the table entities to multiple sets such as which languages a person masters, which skills  ...  The computed order not only alleviates clutter, but also reveals clusters of sets having high overlap with each other.  ... 
doi:10.1109/tvcg.2013.184 pmid:24051816 fatcat:pze3ggsjubarbgzmksx7azivee

On the Readability of Abstract Set Visualizations [article]

Markus Wallinger, Ben Jacobsen, Stephen Kobourov, Martin Nöllenburg
2021 arXiv   pre-print
With this in mind, we consider three different systems for medium-sized set data, LineSets, EulerView, and MetroSets, and report the results of a controlled human-subjects experiment comparing their effectiveness  ...  Specifically, we evaluate the performance, in terms of time and error, on tasks that cover the spectrum of static set-based tasks.  ...  ACKNOWLEDGMENTS The authors would like to thank all of the participants in our experiment, and especially the experts of our pilot study (Daniel Archambault, Helen Purchase, Silvia Miksch).  ... 
arXiv:2101.08155v1 fatcat:65bxarlv4ngsbctnbcdlgdp6ce

Towards Privacy Preserving Publishing of Set-Valued Data on Hybrid Cloud

Hongli Zhang, Zhigang Zhou, Lin Ye, Xiaojiang Du
2018 IEEE Transactions on Cloud Computing  
In this work, we study the issue of privacy-preserving set-valued data publishing.  ...  Motivated by this observation, we present a suite of new techniques that make privacy-aware set-valued data publishing feasible on hybrid cloud.  ...  Set-valued data in the form of high dimensional sparse data is commonly ranging from market basket data to web search query logs, in which a set of values are oftentimes associated with private information  ... 
doi:10.1109/tcc.2015.2430316 fatcat:vskmge3uprcx7pb3lkpq2f7lga

The minimal hitting set generation problem: algorithms and computation [article]

Andrew Gainer-Dewar, Paola Vera-Licona
2016 arXiv   pre-print
Finding inclusion-minimal "hitting sets" for a given collection of sets is a fundamental combinatorial problem with applications in domains as diverse as Boolean algebra, computational biology, and data  ...  Much of the algorithmic literature focuses on the problem of *recognizing* the collection of minimal hitting sets; however, in many of the applications, it is more important to *generate* these hitting  ...  Results We present below the results of the benchmarking experiments on the data sets described in Section 5.2.  ... 
arXiv:1601.02939v1 fatcat:5ssbw6z54ramjjkuwf4rkilsvi

Privacy-preserving Constrained Spectral Clustering Algorithm for Large-scale Data Sets

Wenfen Liu, Ji Li, Jianghong Wei, Mao Ye, Xuexian Hu
2019 IET Information Security  
Spectral clustering is one of the most widely used clustering algorithm for exploratory data analysis and usually has to deal with sensitive data sets.  ...  With the increasing concern on the preservation of personal privacy, privacy-preserving data mining has become a hot topic in recent years.  ...  Acknowledgments This work is supported in part by the National Nature Science  ... 
doi:10.1049/iet-ifs.2019.0255 fatcat:qpk72f4shzb45k6aomtbrxcbwm

Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges [article]

Bilal Alsallakh, Luana Micallef, Wolfgang Aigner, Helwig Hauser, Silvia Miksch, Peter Rodgers
2014 Eurographics Conference on Visualization  
A variety of data analysis problems can be modelled by defining multiple sets over a collection of elements and analyzing the relations between these sets.  ...  We provide a systematic overview of state-of-theart techniques for visualizing different kinds of set relations.  ...  depict clustering results of a social network in Vizster [HB05] .  ... 
doi:10.2312/eurovisstar.20141170 dblp:conf/vissym/AlsallakhMAHMR14 fatcat:kdpd63ly55fire6ykyrdz2shwi

A Cluster Ensemble Framework for Large Data sets

Prodip Hore, Lawrence Hall, Dmitry Goldgof
2006 2006 IEEE International Conference on Systems, Man and Cybernetics  
Merging multiple clustering solutions in a scalable framework requires both cluster ensemble creation and merging to be efficient in terms of time and memory complexity.  ...  Combining multiple clustering solutions within a scalable and robust framework for large data sets is addressed here.  ...  In [12] , weak clusters of a data set are formed by using random hyper planes and multiple views of a sample of the data.  ... 
doi:10.1109/icsmc.2006.384634 dblp:conf/smc/HoreHG06 fatcat:r7764bjqszgejmw5pc3f2innsi

UpSet: Visualization of Intersecting Sets

Alexander Lex, Nils Gehlenborg, Hendrik Strobelt, Romain Vuillemot, Hanspeter Pfister
2014 IEEE Transactions on Visualization and Computer Graphics  
The element view shows filtered elements and a scatterplot comparing two sets of filtered elements.  ...  UpSet showing relationships of movie genres. The set view visualizes intersections and their aggregates, the number of elements, and attribute statistics.  ...  This work was supported in part by the Austrian Science Fund (J 3437-N15), the Air Force Research Laboratory and DARPA grant FA8750-12-C-0300 and the United States National Institutes of Health (K99 HG007583  ... 
doi:10.1109/tvcg.2014.2346248 pmid:26356912 pmcid:PMC4720993 fatcat:4bua3km565fwzjoxtvpzqsjlsy

A Hypergraph-Based Approach to Feature Selection [chapter]

Zhihong Zhang, Edwin R. Hancock
2011 Lecture Notes in Computer Science  
In many data analysis tasks, one is often confronted with the problem of selecting features from very high dimensional data.  ...  Experimental results demonstrate the effectiveness of our feature selection method on a number of standard data-sets.  ...  Introduction High-dimensional data pose a significant challenge for pattern recognition. The most popular methods for reducing dimensionality are variance based subspace methods such as PCA.  ... 
doi:10.1007/978-3-642-23672-3_28 fatcat:5da24equjvhqpk2i4ks7vuctne

Transductive Multilabel Learning via Label Set Propagation

Xiangnan Kong, Michael K. Ng, Zhi-Hua Zhou
2013 IEEE Transactions on Knowledge and Data Engineering  
The problem of multilabel classification has attracted great interest in the last decade, where each instance can be assigned with a set of multiple class labels simultaneously.  ...  In this paper, we study the problem of transductive multilabel learning and propose a novel solution, called TRAsductive Multilabel Classification (TRAM), to effectively assign a set of multiple labels  ...  TABLE 1 Summary of Experimental Data Sets on all those criteria.  ... 
doi:10.1109/tkde.2011.141 fatcat:csa2dtwitvczfcqcwcge33fn4a

Constrained Dominant sets and Its applications in computer vision [article]

Alemu Leulseged Tesfaye
2020 arXiv   pre-print
In the last decades clustering methods have played a vital role in computer vision applications; herein, we focus on the extension, reformulation, and integration of a well-known graph and game theoretic  ...  clustering method known as Dominant Sets.  ...  In other words, a dominant set is a maximally coherent data set.  ... 
arXiv:2002.06028v1 fatcat:rxf5idn2fjcvzj24iu4kggbaoq

Hypergraph Spectra for Unsupervised Feature Selection [chapter]

Zhihong Zhang, Edwin R. Hancock
2012 Lecture Notes in Computer Science  
Most existing feature selection methods focus on ranking individual features based on a utility criterion, and select the optimal feature set in a greedy manner.  ...  relationships within a set of samples.  ...  order similarity measure, we establish a hypergraph framework for characterizing a set of high dimensional samples.  ... 
doi:10.1007/978-3-642-34166-3_68 fatcat:vozzhoeklvblzlit7ydjq5bwsm
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