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GUDIE: a flexible, user-defined method to extract subgraphs of interest from large graphs [article]

Maria Inês Silva, David Aparício, Beatriz Malveiro, João Tiago Ascensão, Pedro Bizarro
2021 arXiv   pre-print
Large, dense, small-world networks often emerge from social phenomena, including financial networks, social media, or epidemiology.  ...  We design GUDIE for rich, labeled graphs, and expansions consider node and edge attributes. Preliminary results indicate that GUDIE expands to insightful areas while avoiding unimportant connections.  ...  Conclusion We propose GUDIE to extract node context from large, highly connected networks.  ... 
arXiv:2108.09200v1 fatcat:5cqsfgbbxrh5jpdnwbxb46un3y

Graph Exploration

Davide Mottin, Emmanuel Müller
2017 Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17  
The increasing interest in social networks, knowledge graphs, protein-interaction, and many other types of networks has raised the question how users can explore such large and complex graph structures  ...  In many cases graph methods try to scale to the size and complexity of a real network.  ...  We abstracted user-driven graph exploration properties from techniques proposed in the literature and defined such a unified taxonomy.  ... 
doi:10.1145/3035918.3054778 dblp:conf/sigmod/MottinM17 fatcat:wvq2efawrng3ro7nkht5l4occy

Line graph explorer

Robert Kincaid, Heidi Lam
2006 Proceedings of the working conference on Advanced visual interfaces - AVI '06  
To address these issues, we have developed Line Graph Explorer (LGE).  ...  Sequential sorting by associated line graph metadata is also supported. We illustrate the features and use of LGE with examples from meteorology and biology.  ...  Such methods, when coupled with user-variable magnification, would allow the user to drill to an arbitrary level of graph detail in either dimension.  ... 
doi:10.1145/1133265.1133348 dblp:conf/avi/KincaidL06 fatcat:njuil76fc5fqdnlpfoz6f6re3i

Graph-based exploration of non-graph datasets

Udayan Khurana, Srinivasan Parthasarathy, Deepak Turaga
2016 Proceedings of the VLDB Endowment  
While the system automates the computationally intensive aspects of the process, it is engineered to leverage human domain expertise and instincts to fine tune the data exploration process.  ...  The effort and skill required in identifying and extracting the relevant graph representation from data is often the prohibitive and limits a wider adoption of graph-based analysis of nongraph data.  ...  Large-scale Graph Analytics in Aster 6: Bringing Context to Big Data Discovery.  ... 
doi:10.14778/3007263.3007308 fatcat:osz2f2axljdupmnihuolyb5l7y

D-Graph: AI-Assisted Design Concept Exploration Graph [article]

Shin Sano, Seiji Yamada
2022 arXiv   pre-print
D-Graph retrieves adjectives from a ConceptNet knowledge graph as nodes and visualizes them in a dynamically scalable 3D graph as users explore words.  ...  We present an AI-assisted search tool, the "Design Concept Exploration Graph" ("D-Graph").  ...  The large space below them is allocated to a "playground, " in which graphs of explored words are visualized in 3D hub-and-spoke style.  ... 
arXiv:2201.03737v1 fatcat:wdpv2tijfffb7eatisqhoizqpa

Exploring EOSIO via Graph Characterization [article]

Yijing Zhao, Jieli Liu, Qing Han, Weilin Zheng, Jiajing Wu
2020 arXiv   pre-print
To fill this gap, we conduct a systematic graph analysis on the early EOSIO by investigating its four major activities, namely account creation, account vote, money transfer and contract authorization.  ...  We obtain some novel observations via graph metric analysis, and our results reveal some abnormal phenomenons like voting gangs and sham transactions.  ...  Since the large volume of transaction data, it is infeasible to obtain all transaction data we need by directly crawling them from blockchain explorer.  ... 
arXiv:2004.10017v1 fatcat:ljnoxlqbtbaytdbfjz3ejlrxke

Visual exploration of multivariate graphs

Martin Wattenberg
2006 Proceedings of the SIGCHI conference on Human Factors in computing systems - CHI '06  
Unlike visualizations which emphasize global graph topology, PivotGraph uses a simple grid-based approach to focus on the relationship between node attributes and connections.  ...  The interaction technique is derived from an analogy with methods seen in spreadsheet pivot tables and in online analytical processing (OLAP).  ...  This paper has been improved greatly by comments from Steve Rohall, Fernanda Viegas, and the anonymous referees.  ... 
doi:10.1145/1124772.1124891 dblp:conf/chi/Wattenberg06 fatcat:6bmtdr725rdifmzs227tqjrc5a

GraphVista: Interactive Exploration Of Large Graphs [article]

Marcus Paradies and Michael Rudolf and Wolfgang Lehner
2015 arXiv   pre-print
To lower the burden for the user to explore an unknown graph without prior knowledge of a graph query language, visual graph exploration provides an effective and intuitive query interface to navigate  ...  The potential to gain business insights from graph-structured data through graph analytics is increasingly attracting companies from a variety of industries, ranging from web companies to traditional enterprise  ...  an interactive graph exploration starting from those entry points performed by the user at run-time.  ... 
arXiv:1506.00394v2 fatcat:tyouqcxa4vbv3pr5iqfn6jxjz4

Stochastic Graph Exploration

Aris Anagnostopoulos, Ilan R. Cohen, Stefano Leonardi, Jakub Lacki, Michael Wagner
2019 International Colloquium on Automata, Languages and Programming  
To model this process, we introduce the stochastic graph exploration problem.  ...  Exploring large-scale networks is a time consuming and expensive task which is usually operated in a complex and uncertain environment.  ...  In the case of the exploration of the Twitter graph, an edge-probing strategy allows to gain information on those tweets of a user that are retweeted from his followers.  ... 
doi:10.4230/lipics.icalp.2019.136 dblp:conf/icalp/Anagnostopoulos19 fatcat:g7d4k7isqjdhzbhe6vofpar35a

Learning Transferable Graph Exploration [article]

Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
2019 arXiv   pre-print
We propose a 'learning to explore' framework where we learn a policy from a distribution of environments.  ...  At test time, presented with an unseen environment from the same distribution, the policy aims to generalize the exploration strategy to visit the maximum number of unique states in a limited number of  ...  Acknowledgments We would like to thank Hengxiang Hu, Shu-Wei Cheng and other members in the team for providing data and engineering suggestions.  ... 
arXiv:1910.12980v1 fatcat:4qruvw3szjfvdo2v7xmb3jv5oq

Semantic Blossom Graph: A New Approach for Visual Graph Exploration

Manuela Rauch, Ralph Wozelka, Eduardo Veas, Vedran Sabol
2014 2014 18th International Conference on Information Visualisation  
Users apply selective expansion to traverse the graph and discover the subset of interest.  ...  However, graphs pose several challenges for visual analysis. A large number of entities or a densely connected set quickly render the graph unreadable due to clutter.  ...  GRAPHICAL REPRESENTATION: BLOSSOM AND LAYOUTING We are searching for a representation that gives users an overview of the graph starting from a subset of nodes that encourages them to explore the graph  ... 
doi:10.1109/iv.2014.36 dblp:conf/iv/RauchWVS14 fatcat:d5bysi22tnatpgxrssti3nlz5a

GRAPHIE: graph based histology image explorer

Hao Ding, Chao Wang, Kun Huang, Raghu Machiraju
2015 BMC Bioinformatics  
Thus, our design of GRAPHIE allows for the users to navigate and explore large collections of histology image datasets.  ...  By representing each image with informative features and then subsequently visualizing the image collection with a graph, GRAPHIE allows users to effectively explore the image collection.  ...  (b) Graph created with selected features.  ... 
doi:10.1186/1471-2105-16-s11-s10 pmid:26330277 pmcid:PMC4547152 fatcat:7ftsrum2bzfy5fz47cfsjugb6m

Big graph mining

U. Kang, Christos Faloutsos
2013 SIGKDD Explorations  
Big graphs are everywhere, ranging from social networks and mobile call networks to biological networks and the World Wide Web.  ...  How do we find patterns and anomalies in very large graphs with billions of nodes and edges? How to mine such big graphs efficiently?  ...  The challenge is to effectively summarize the graphs so that users can easily understand the graphs in a screen with limited resolution.  ... 
doi:10.1145/2481244.2481249 fatcat:fzidqzmctndj3nxh2qw55txyuu

Navigation Recommendations for Exploring Hierarchical Graphs [chapter]

Stefan Gladisch, Heidrun Schumann, Christian Tominski
2013 Lecture Notes in Computer Science  
Particularly for unknown graphs, the user often faces situations where it is not entirely clear where to go next.  ...  For hierarchical graphs, the user may also ponder whether it is useful to look at the data at a higher or lower level of abstraction.  ...  Acknowledgements This research has been supported by the German Research Foundation (DFG) in the context of the project GEMS -graph exploration and manipulation on interactive surfaces.  ... 
doi:10.1007/978-3-642-41939-3_4 fatcat:4uq4xcbqincnrpttfvkagzyrdy

Graphle: Interactive exploration of large, dense graphs

Curtis Huttenhower, Sajid O Mehmood, Olga G Troyanskaya
2009 BMC Bioinformatics  
Investigators often wish to explore specific portions of such networks from a detailed, gene-specific perspective, and balancing this requirement with the networks' large size, complex structure, and rich  ...  The Graphle applet allows a user to examine specific portions of a graph, retrieving the relevant neighborhood around a set of query vertices (genes).  ...  Acknowledgements We would like to thank Brian Kernighan, Philip Stern, Adam Sanders, and Anson Hook for work on an early prototype of Graphle, as well as Anjali Iyer-Pascuzzi, Jørgen Aarøe, Vanessa Dumeaux  ... 
doi:10.1186/1471-2105-10-417 pmid:20003429 pmcid:PMC2803856 fatcat:cdhq6uu3v5fzvdf52l2qhkhq3e
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