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ICDE conference 2014 detailed author index
2014
2014 IEEE 30th International Conference on Data Engineering
Systems
Meira Jr., Wagner
448
Complete Discovery of High-Quality Patterns in Large Numerical Tensors
Meng, Cynthia
1254
KnowLife: A Knowledge Graph for Health and Life Sciences
Menon, Prashanth ...
Join
Kondreddi, Sarath Kumar
988
Combining Information Extraction and Human Computing for Crowdsourced Knowledge
Acquisition
Korn, Flip
1226
iCoDA: Interactive and Exploratory Data Completeness ...
doi:10.1109/icde.2014.6816627
fatcat:bmnfkwqucfcmhet64s2o6ns5ky
Guest Editors' Introduction: special issue of selected papers from ECML PKDD 2011
2012
Data mining and knowledge discovery
Geoff Webb for his great help and support in organizing this special issue. ...
We are indebted to the reviewers for their careful work and for their constructive comments to the authors. We are grateful to the journal Editor-in-Chief Dr. ...
The last edition of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) was held in Athens, Greece, during September 5-9, 2011. ...
doi:10.1007/s10618-012-0282-x
fatcat:cwpjwmz5crei3dvqy2ha3ioihu
Guest editors' introduction: special issue of selected papers from ECML PKDD 2011
2012
Machine Learning
Geoff Webb for his great help and support in organizing this special issue. ...
We are indebted to the reviewers for their careful work and for their constructive comments to the authors. We are grateful to the journal Editor-in-Chief Dr. ...
The last edition of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) was held in Athens, Greece, during September 5-9, 2011. ...
doi:10.1007/s10994-012-5317-4
fatcat:74pag2x6avbsrh45e352azh3b4
Graph Query Reformulation with Diversity
2015
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15
We study a problem of graph-query reformulation enabling explorative query-driven discovery in graph databases. ...
To efficiently solve this step, we show how to compute the objective-function increment of a specialization linearly in the number of its results and derive an upper bound that we exploit to devise an ...
For this reason, we avoid to report efficiency results for Greedy_BF in the remainder. ...
doi:10.1145/2783258.2783343
dblp:conf/kdd/MottinBG15
fatcat:qhwjvkatfzcpdlmdlfu6t5sj24
Pattern detection in large temporal graphs using algebraic fingerprints
[chapter]
2020
Proceedings of the 2020 SIAM International Conference on Data Mining
For example, in a real-world graph dataset with more than six million edges and a multi-set query with ten colors, we can extract an optimal solution in less than eight minutes on a haswell desktop with ...
In particular, given a vertex-colored temporal graph and a multi-set of colors as a query, we search for temporal paths in the graph that contain the colors specified in the query. ...
To the best of our knowledge this is the first paper that applies these approaches for data mining and exploratory graph analysis. ...
doi:10.1137/1.9781611976236.5
dblp:conf/sdm/ThejaswiG20
fatcat:tbljv2j56jb3riym674xncjxlu
Where do I start?
2012
Proceedings of the ACM SIGKDD Workshop on Intelligence and Security Informatics - ISI-KDD '12
We present nine methods with origins in association analysis, graph metrics, and probabilistic modeling, and systematically evaluate them over multiple document collections. ...
Our results reveal selective superiorities of the algorithmic strategies and lead to several design recommendations for creating document exploration capabilities. ...
The centrality measures for each vertex in the entity-entity graph are calculated using the R package igraph [12] , and vertices with large values for each centrality measure are provided to the intelligence ...
doi:10.1145/2331791.2331794
fatcat:tnnlnbdwdba5di2hmqsnx3kjru
Analytic Queries over Geospatial Time-Series Data Using Distributed Hash Tables
2016
IEEE Transactions on Knowledge and Data Engineering
The focus of this study is twofold: exploratory and predictive analytics over voluminous, multidimensional datasets in a distributed environment. ...
While challenging in its own right, storing and managing voluminous datasets is only the precursor to a broader field of research: extracting insights, relationships, and models from the underlying datasets ...
The DiscoveryGraph improves upon (and supersedes) the feature and metadata graphs by making knowledge extraction part of the indexing process. ...
doi:10.1109/tkde.2016.2520475
fatcat:ssokaqybjvgoviv7rwcdim3hsu
AVIST: A GPU-Centric Design for Visual Exploration of Large Multidimensional Datasets
2016
Informatics
Finally, we summarize lessons learned about GPU-based solutions in interactive information visualization with big data. ...
This paper presents the Animated VISualization Tool (AVIST), an exploration-oriented data visualization tool that enables rapidly exploring and filtering large time series multidimensional datasets. ...
Thus, interactive exploration of large time series and multidimensional datasets is a key ingredient for knowledge discovery [9] . ...
doi:10.3390/informatics3040018
fatcat:wxfo7udylvavrffdj3anrq3nzy
Flexible and efficient querying and ranking on hyperlinked data sources
2009
Proceedings of the 12th International Conference on Extending Database Technology Advances in Database Technology - EDBT '09
We propose the Graph Information Discovery (GID) framework to support sophisticated user queries on a rich web of annotated and hyperlinked data entries, where query answers need to be ranked in terms ...
Our techniques can produce high quality (Top K) answers with a savings of up to an order of magnitude, in comparison to the evaluation time for the exact solution. ...
Experiments performed over large real and synthetic graphs show the feasibility of our techniques in supporting an interactive, exploratory and high-quality discovery process. ...
doi:10.1145/1516360.1516425
dblp:conf/edbt/VaradarajanHRVIR09
fatcat:hmddl3ejk5f3vpv33n52gho7ri
Data exploration and knowledge discovery in a patient wellness tracking (PWT) system at a nurse-managed health services center
2012
Proceedings of the 2nd ACM SIGHIT symposium on International health informatics - IHI '12
In this paper, we present (1) an exploratory data browser based on information content in information theory for searching granularity patient data, and (2) a knowledge discovery component based on probabilistic ...
This paper describes our ongoing research on data exploration and knowledge discovery in a patient wellness tracking (PWT) information system developed for a nurse-managed community health center. ...
KNOWLEDGE DISCOVERY In this section, we describe data analysis and knowledge discovery in the PWT system in helping the clinician make decisions. ...
doi:10.1145/2110363.2110437
dblp:conf/ihi/AnKSH12
fatcat:4sbhy7btjbgoxgpklkn2mof3aa
Motif-Driven Contrastive Learning of Graph Representations
[article]
2021
arXiv
pre-print
Our framework MotIf-driven Contrastive leaRning Of Graph representations (MICRO-Graph) can: 1) use GNNs to extract motifs from large graph datasets; 2) leverage learned motifs to sample informative subgraphs ...
To solve it, we propose to learn graph motifs, which are frequently-occurring subgraph patterns (e.g. functional groups of molecules), for better subgraph sampling. ...
This constrained optimization problem can be solved efficiently using a fast Sinkhorn-Knopp algorithm as shown in Cuturi [7] . ...
arXiv:2012.12533v3
fatcat:kknuji2x7zek7bsy7ziuiv5byu
Semantic Blossom Graph: A New Approach for Visual Graph Exploration
2014
2014 18th International Conference on Information Visualisation
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. ...
A preliminary evaluation showed that our approach is intuitive and useful for graph exploration and provided insightful ideas for future improvements. ...
ACKNOWLEDGMENT The Know-Center is funded within the Austrian COMET Program -Competence Centers for Excellent Technologies -of the Austrian Federal Ministry of Transport, Innovation and Technology, the ...
doi:10.1109/iv.2014.36
dblp:conf/iv/RauchWVS14
fatcat:d5bysi22tnatpgxrssti3nlz5a
Estimating genomic coexpression networks using first-order conditional independence
2004
Genome Biology
We describe a complementary unsupervised graph search algorithm for discovering locally distinct subgraphs of a large weighted graph. ...
We describe a computationally efficient statistical framework for estimating networks of coexpressed genes. ...
We thank members of the Kim lab for constructive comments and critiques of the methods described in this paper. ...
doi:10.1186/gb-2004-5-12-r100
pmid:15575966
pmcid:PMC545795
fatcat:guqv3eeqpjem7ffxyzjhsfyo5e
Scalable Explanation of Inferences on Large Graphs
[article]
2019
arXiv
pre-print
on large and dense graphs without hurting faithfulness. ...
Probabilistic inferences distill knowledge from graphs to aid human make important decisions. ...
Variants of GE-L To further speed up GE-L (see Fig. 4 ), especially on graphs that a user has prior knowledge about the topology of the explaining subgraph, its search space can be further constrained ...
arXiv:1908.06482v2
fatcat:4onvh3p2nvegdgbo42v26hajh4
2018 Index IEEE Transactions on Knowledge and Data Engineering Vol. 30
2019
IEEE Transactions on Knowledge and Data Engineering
., þ, TKDE Nov. 2018 2106-2119 MCS-GPM: Multi-Constrained Simulation Based Graph Pattern Matching in Contextual Social Graphs. ...
Li, C., þ, TKDE Aug. 2018 1440-1453 MCS-GPM: Multi-Constrained Simulation Based Graph Pattern Matching in Contextual Social Graphs. ...
doi:10.1109/tkde.2018.2882359
fatcat:asiids266jagrkx5eac6higrlq
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