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Bi-pattern mining of attributed networks

Henry Soldano, Guillaume Santini, Dominique Bouthinon, Sophie Bary, Emmanuel Lazega
2019 Applied Network Science  
Applying closed pattern mining to attributed two-mode networks requires two conditions.  ...  We need to consider appropriate core definitions for two-mode networks and define accordingly closed bi-patterns. We describe in this article a general framework to define closed bi-pattern mining.  ...  Availability of data and materials The datasets and program sources are available at https://lipn.univ-paris13.fr/MinerLC/ under a particular "Submission to Applied NetWork Science" section.  ... 
doi:10.1007/s41109-019-0144-1 fatcat:pxjdhyf4rrf25glxjmz674e2ly

MINE: A method of Multi-Interaction heterogeneous information Network Embedding

Dongjie Zhu, Yundong Sun, Xiaofang Li, Haiwen Du, Rongning Qu, Pingping Yu, Xuefeng Piao, Russell Higgs, Ning Cao
2020 Computers Materials & Continua  
and mining of potential deep interactions between nodes.  ...  Interactivity is the most significant feature of network data, especially in social networks.  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmc.2020.010008 fatcat:zexmrpvbxncozcpqi4jsmbvxmq

MINE: Mutual Information Neural Estimation [article]

Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, R Devon Hjelm
2021 arXiv   pre-print
We argue that the estimation of mutual information between high dimensional continuous random variables can be achieved by gradient descent over neural networks.  ...  We present a handful of applications on which MINE can be used to minimize or maximize mutual information. We apply MINE to improve adversarially trained generative models.  ...  Decoder network for bi-directional model(ALI, ALICE) experiments using MINE on CelebA.Table 13. Discriminator network for bi-directional models on CelebA.  ... 
arXiv:1801.04062v5 fatcat:tnk23sqrhvg6poezaxuksfjyuq

Domain-Specific Chinese Word Segmentation Based on Bi-Directional Long-Short Term Memory Model

Dangguo Shao, Na Zheng, Zhaoqiang Yang, Zhenhua Chen, Yan Xiang, Yantuan Xian, Zhengtao Yu
2019 IEEE Access  
This paper takes the field of metallurgy as an example and proposes a domain-specific Chinese word segmentation based on Bi-directional long-short term memory (Bi-directional LSTM) model in the metallurgical  ...  INDEX TERMS Bi-directional long-short term memory (Bi-directional LSTM) model, Chinese word segmentation, combination of weight, domain-specific.  ...  The Bi-directional LSTM neural network consists of two parts:forward LSTM and backward LSTM, which can be referred to Figure 4 .  ... 
doi:10.1109/access.2019.2892836 fatcat:flilx35775d2rogxzo23zx2lwq

Applying modality and equivalence concepts to pattern finding in social process-produced data

Robert A. Hanneman, Christian R. Shelton
2010 Social Network Analysis and Mining  
Dimensional and generalized "block models" of multi-modal social networks provide tools for designing searches to identify patterns.  ...  Large amounts of detailed transactional information are generated by ongoing social processes. For managing and mining such data, we treat them as "objects" and "relations".  ...  Social network analysis identifies two very abstract classes of relations: directed and ''bonded''.  ... 
doi:10.1007/s13278-010-0009-1 fatcat:ycnq32gr2fhvjgd2rnb3pm4zsi

Brain network analysis

Xiangnan Kong, Philip S. Yu
2014 SIGKDD Explorations  
Brain network data pose many unique challenges for data mining research.  ...  The network structure can be very noisy and uncertain. Therefore, innovative methods are required for brain network analysis. Many research e↵orts have been devoted to this area.  ...  In brain network analysis, the ideal patterns we want to mine from the data should combine the two schemes together.  ... 
doi:10.1145/2641190.2641196 fatcat:l7gnbu3zufbvjmw67ptxycyoyu

Code Failure Prediction and Pattern Extraction using LSTM Networks [article]

Mahdi Hajiaghayi, Ehsan Vahedi
2018 arXiv   pre-print
Using the proposed greedy method, we are able to find the contributors and blockers in the synthetic data in more than 90% of the cases, with a performance better than sequential rule and pattern mining  ...  We also use LSTM networks to extract telemetry patterns that lead to a specific code failure.  ...  Bidirectional LSTM networks can be thought of as two attached standard LSTMs with forward and backward directions.  ... 
arXiv:1812.05237v1 fatcat:ho72krrqijdrho4gcx6fr35bym

Web Social Mining [chapter]

Hady W. Lauw, Ee-Peng Lim
2009 Encyclopedia of Library and Information Sciences, Third Edition  
In this article, we describe three Web social mining topics, namely, social network discovery, social network analysis and social network applications.  ...  With increasing user presence in the Web and Web 2.0, Web social mining becomes an important and challenging task that finds a wide range of new applications relevant to e-commerce and social software.  ...  If there are two types of actors (e.g., people and organizations), it is a two-mode network.  ... 
doi:10.1081/e-elis3-120043522 fatcat:7e7ajhkhingy7bwhsijm3iu3we

Single-Fiber Bi-Directional Burst-Mode EDFA for TWDM-PON

Zehao Xiao, Lilin Yi, Lei Xue, Weisheng Hu
2018 IEEE Photonics Journal  
reflection power up to −14 dBm, which proves the promising applications in PONs of the proposed single-fiber bi-directional burst-mode EDFA.  ...  Abstract: In this paper, we propose a single-fiber bi-directional burst-mode erbium-doped fiber amplifier (EDFA) to simultaneously improve upstream and downstream loss budget in time and wavelength division  ...  (b) The schematic of the TWDM-PON system with a bi-directional EDFA, ONU: optical network unit, OLT: optical line terminal, OC: optical circulator.  ... 
doi:10.1109/jphot.2018.2873208 fatcat:ohipycrd4bb4lhkfhtlbwlc6he

Time Series Clustering for Human Behavior Pattern Mining [article]

Rohan Kabra, Divya Saxena, Dhaval Patel, Jiannong Cao
2021 arXiv   pre-print
Existing pattern mining techniques either assume human dynamics is strictly periodic, or require the number of modes as input, or do not consider uncertainty in the sensor data.  ...  Empirical studies on two real-world datasets and a simulated dataset demonstrate the effectiveness of MTpattern with respect to internal and external measures of clustering.  ...  Most of the techniques need the number of modes of behavior as input and only identify patterns that span the entire time period.  ... 
arXiv:2110.07549v2 fatcat:vkzrfgidrrhrjgrcwz37sadntq

Large-scale modulation of reconstituted Min protein patterns and gradients by defined mutations in MinE's membrane targeting sequence

Simon Kretschmer, Katja Zieske, Petra Schwille, Colin Johnson
2017 PLoS ONE  
These oscillations appeared to require direct membrane interaction of the ATPase activating protein MinE.  ...  Here, we dissect the role of MinE's membrane targeting sequence (MTS) by reconstituting various MinE mutants in 2D and 3D geometries.  ...  Acknowledgments We thank the biochemistry core facility at MPI-B for help with protein purification, Michaela Schaper and Katharina Nakel for help with cloning as well as Michael Heymann and Frank Visualization  ... 
doi:10.1371/journal.pone.0179582 pmid:28622374 pmcid:PMC5473585 fatcat:qm23rrrpj5einihoe4khhgtdle

Big graph mining

U. Kang, Christos Faloutsos
2013 SIGKDD Explorations  
How do we find patterns and anomalies in very large graphs with billions of nodes and edges? How to mine such big graphs efficiently?  ...  Big graphs are everywhere, ranging from social networks and mobile call networks to biological networks and the World Wide Web.  ...  The views and conclusions are those of the authors and should not be interpreted as representing the official policies, of the U.S.  ... 
doi:10.1145/2481244.2481249 fatcat:fzidqzmctndj3nxh2qw55txyuu

Frequent Pattern Mining in Continuous-time Temporal Networks [article]

Ali Jazayeri, Christopher C. Yang
2021 arXiv   pre-print
In addition to the numerous applications, the investigation of frequent pattern mining in networks directly impacts other analytical approaches, such as clustering, quasi-clique and clique mining, and  ...  Next, we develop a series of algorithms for mining the complete set of frequent temporal patterns in a temporal network data set.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  ... 
arXiv:2105.06399v1 fatcat:qzo3l4wqmjf3tgbcj2s5nsdyh4

A Survey of Graph Mining Techniques for Biological Datasets [chapter]

S. Parthasarathy, S. Tatikonda, D. Ucar
2010 Managing and Mining Graph Data  
We conclude this article with a discussion of the key results and identify some interesting directions for future research.  ...  Mining structured information has been the source of much research in the data mining community over the last decade.  ...  Acknowledgments The authors wish to acknowledge the support of NSF CAREER Grant IIS-0347662.  ... 
doi:10.1007/978-1-4419-6045-0_18 dblp:series/ads/ParthasarathyTU10 fatcat:aeu53r3dbzd67d5whkjypv64uq

CRM System Using PA-AKD Approach of D3M

Ajay kumar, Tejaswi A, Lakshmi Prasad Koyi, G.Narasinga Rao, S.Srinivasa Rao Illapu
2010 International Journal of Computer Science & Information Technology (IJCSIT)  
Then the structure of CRM is described with the help of D 3 M, discusses the procedure to Data warehouse and the significance of D 3 M applied to CRM.  ...  Inspite of the unpredictable economy, CRM is being forced into corporate budgets and is believed to be the leading and initiative factor by many companies.  ...  D 3 M that is the most important step to find knowledge in E-commerce consists of two parts: one is to mine information which customers visit web sites to find behavior and mode which customers browse  ... 
doi:10.5121/ijcsit.2010.2209 fatcat:ney4he6n4nf5rgboycylzyxu2e
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