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A Survey Of Business Component Identification Methods And Related Techniques

Zhongjie Wang, Xiaofei Xu, Dechen Zhan
2008 Zenodo  
Then various CI methods presented in literatures are classified into four types, i.e., domain analysis based methods, cohesion-coupling based clustering methods, CRUD matrix based methods, and other methods  ...  Based on the concept and classification of CI, its technical stack is briefly discussed from four views, i.e., form of input business models, identification goals, identification strategies, and identification  ...  A feasible plan is to combine current CI methods together, e.g., using DE-based methods for optimization on reusability and stability, using cluster analysis based and CRUD-based methods to optimize reuse  ... 
doi:10.5281/zenodo.1062024 fatcat:gqzi4gpssnckpfwg26xrqdwki4

A graph-based approach for the structural analysis of road and building layouts

Mathieu Domingo, Rémy Thibaud, Christophe Claramunt
2019 Geo-spatial Information Science  
Based on these local and global properties derived from the topological and graph-based representation, and on building density metrics, this paper proposes an analysis of road and building layouts at  ...  A better understanding of the relationship between the structure and functions of urban and suburban spaces is one of the avenues of research still open for geographical information science.  ...  Notes on contributors Mathieu Domingo is a PhD in computer science, currently a research assistant and full stack developer at the University of Pau and Pays de l'Adour in France.  ... 
doi:10.1080/10095020.2019.1568736 fatcat:56ndyqyv4ravpazrhrmegcoeay

Performance Evaluation of Automobile Fuel Consumption Using a Fuzzy-Based Granular Model with Coverage and Specificity

Yeom, Kwak
2019 Symmetry  
GMs are defined by input and output space information transformations using context-based fuzzy C-means clustering.  ...  The predictive performance of different granular models (GMs) was compared and analyzed for methods that evenly divide linguistic context in information granulation-based GMs and perform flexible partitioning  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sym11121480 fatcat:7n555nejebaijif3gajjjfikte

dg2pix: Pixel-Based Visual Analysis of Dynamic Graphs

Eren Cakmak, Dominik Jackle, Tobias Schreck, Daniel Keim
2020 2020 Visualization in Data Science (VDS)  
RELATED WORK In the following, we briefly discuss related work from dynamic graph visualizations, the visual analysis of dimensionality reduction methods, and pixel-based visualization techniques.  ...  The reoccurring states (A-C) have for each time step the same amount of nodes (2500) and edges (350000) with a different number of clusters.  ...  ., 2D embeddings [48] ), they still fail to provide a scalable overview of the structural changes as the approaches depend on the temporal analysis scale and the designed feature vector (e.g., graph metrics  ... 
doi:10.1109/vds51726.2020.00008 fatcat:yca23ponvbfcjnmuzqyyl7mdra

dg2pix: Pixel-Based Visual Analysis of Dynamic Graphs [article]

Eren Cakmak, Dominik Jäckle, Tobias Schreck, Daniel Keim
2020 arXiv   pre-print
We propose dg2pix, a novel pixel-based visualization technique, to visually explore temporal and structural properties in long sequences of large-scale graphs.  ...  suitable intermediate representation between node-link diagrams at the high detail end and matrix representations on the low detail end.  ...  ., 2D embeddings [48] ), they still fail to provide a scalable overview of the structural changes as the approaches depend on the temporal analysis scale and the designed feature vector (e.g., graph metrics  ... 
arXiv:2009.07322v1 fatcat:dxrhzrrcpncallve4xg7sui67i

Multi-Granularity Whole-Brain Segmentation Based Functional Network Analysis Using Resting-State fMRI

Yujing Gong, Huijun Wu, Jingyuan Li, Nizhuan Wang, Hanjun Liu, Xiaoying Tang
2018 Frontiers in Neuroscience  
Furthermore, we validated the aforementioned conclusions and measured the reproducibility of this multi-granularity network analysis pipeline using another dataset of 49 healthy young subjects that had  ...  segmentations with each level linked through ontology-based, hierarchical, structural relationships.  ...  Zhengjia Dai at Sun Yat-sen University for valuable discussions on brain network analysis. The authors would also like to acknowledge Dr. Mingrui Xia and Dr.  ... 
doi:10.3389/fnins.2018.00942 pmid:30618571 pmcid:PMC6299028 fatcat:4mwtwig6w5em7nee35xirl63lm

MSGC: Multi-scale grid clustering by fusing analytical granularity and visual cognition for detecting hierarchical spatial patterns

Zhipeng Gui, Dehua Peng, Huayi Wu, Xi Long
2020 Future generations computer systems  
Spatial clustering is scale dependent and linked to the size of analysis unit as well as the hierarchy of visual cognition.  ...  Comparative experiments validated the proposed algorithm against the classical Density-based Spatial Clustering of Applications with Noise (DBSCAN) and WaveCluster algorithms on both synthetic and real-world  ...  analysis and GeoAI; 2) High-performance geocomputation and spatial cloud computing; 3) Geospatial service chain modeling and optimization; 4) QoGIS-aware monitoring and evaluation of geospatial web services  ... 
doi:10.1016/j.future.2020.06.053 fatcat:jqkpxwc4dbffnku65qunsmay6m

Conceptualizing Visual Uncertainty in Parallel Coordinates

Aritra Dasgupta, Min Chen, Robert Kosara
2012 Computer graphics forum (Print)  
By building a taxonomy, we aim to identify different sources of uncertainty in the screen space and relate them to different effects of uncertainty upon the user.  ...  Existing research on uncertainty in visualization mainly focuses on depicting data-space uncertainty in a visual form.  ...  In privacy-preserving visualization, a clustering technique based on screen-space metrics is used to set a lower bound on the number of records per cluster.  ... 
doi:10.1111/j.1467-8659.2012.03094.x fatcat:jyel6h6wczeehdcdlb5lrd27pa

A Review on Evolving Interval and Fuzzy Granular Systems

Daniel Leite, Pyramo Costa Jr., Fernando Gomide
2016 Learning and Nonlinear Models  
Essential notions of interval analysis and fuzzy sets are addressed from the granular computing point of view.  ...  This article provides definitions and principles of granular computing and discusses the generation and online adaptation of rule-based models from data streams.  ...  The ePL approach is based on unsupervised clustering and therefore is a candidate to find rule base structures in adaptive fuzzy modeling. ePL uses participatory learning fuzzy clustering instead of scattering  ... 
doi:10.21528/lnlm-vol14-no2-art3 fatcat:mw4xwirbsbg3ln2fciuovvlg6u

Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs [article]

Eren Cakmak, Udo Schlegel, Dominik Jäckle, Daniel Keim, Tobias Schreck
2020 arXiv   pre-print
The approach enables to discover similar temporal summaries (e.g., recurring states), reduces the temporal data to speed up automatic analysis, and to explore both structural and temporal properties of  ...  The overview-driven visual analysis of large-scale dynamic graphs poses a major challenge.  ...  Evaluation Metrics The following metrics are used to evaluate the approach. We compute the accuracy of the 5-nearest neighbor queries based on the ground-truth.  ... 
arXiv:2008.08282v2 fatcat:x3xsbzot3fhc7iijx7nssjlxsq

Granular Computing in the Information Transformation of Pattern Recognition

Hong Hu, Zhongzhi Shi
2007 2007 IEEE International Conference on Granular Computing (GRC 2007)  
Many GrC researches are based on equivalence relation or more generally tolerance relation, equivalence relation or tolerance relation can be described by some distance functions and GrC can be geometrically  ...  The key points of GrC are (1) there are two granular computing approaches to change a high dimensional complex distribution domain to a low dimensional and simple domain,(2)these two kind approaches can  ...  space(X,г)induced from a metric space (X,dis)by the metric dis.  ... 
doi:10.1109/grc.2007.42 dblp:conf/grc/HuS07 fatcat:roakaapngnc5lir2gbsro6lsqq

Granular Computing in the Information Transformation of Pattern Recognition

Hong Hu, Zhongzhi Shi
2007 2007 IEEE International Conference on Granular Computing (GRC 2007)  
Many GrC researches are based on equivalence relation or more generally tolerance relation, equivalence relation or tolerance relation can be described by some distance functions and GrC can be geometrically  ...  The key points of GrC are (1) there are two granular computing approaches to change a high dimensional complex distribution domain to a low dimensional and simple domain,(2)these two kind approaches can  ...  space(X,г)induced from a metric space (X,dis)by the metric dis.  ... 
doi:10.1109/grc.2007.4403062 fatcat:kd33nbd7zbdedohiqffygqnvu4

Interactive selection of multivariate features in large spatiotemporal data

Jingyuan Wang, Robert Sisneros, Jian Huang
2013 2013 IEEE Pacific Visualization Symposium (PacificVis)  
Our findings demonstrate that the CO 3 metrics are useful for simplifying the problem space and revealing potential unknown possibilities of scientific discoveries by assisting users to effectively select  ...  The system integrates CO 3 metrics with an elegant multi-space user interaction tool to provide various forms of quantitative user feedback.  ...  The CO 3 metrics are computed based on the distribution of clusters on the partition of the physical space, hence, the choice of bin size affects the values of the metrics.  ... 
doi:10.1109/pacificvis.2013.6596139 dblp:conf/apvis/WangSH13 fatcat:kszkamkbcnhc3jjpfz7ohopxpe

A new nature inspired modularity function adapted for unsupervised learning involving spatially embedded networks: A comparative analysis [article]

Raj Kishore, Zohar Nussinov, Kisor Kumar Sahu
2020 arXiv   pre-print
Two specific examples include the structure of granular materials and atomic structure of metallic glasses.  ...  One thing is common in both the examples is that the particles are the elements of the ensembles that are embedded in Euclidean space and one can create a spatially embedded network to represent their  ...  Acknowledgement KKS was partially funded by UAY project (84/IITBBS-006) and ZN was partially funded by NSF grant number 1411229.  ... 
arXiv:2007.09330v1 fatcat:qx7mq3djdfawjeimpm7qlstqxq

Hierarchical Clustering with Prior Knowledge [article]

Xiaofei Ma, Satya Dhavala
2018 arXiv   pre-print
The clustering results oftentimes depend on not only the distribution of the underlying data, but also the choice of dissimilarity measure and the clustering algorithm.  ...  As a case study, we applied this method on real data in the building of a customer behavior based product taxonomy for an Amazon service, leveraging the information from a larger Amazon-wide browse structure  ...  The whole space is one cluster. Condition 3 ensures that the structure of dendrogram is nested. Condition 4 requires that the partition is stable under small perturbation of size ϵ.  ... 
arXiv:1806.03432v3 fatcat:cwhfeplxvvahdhgm2jt3xzyht4
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