According to the computational results, the new algorithm is able to efficiently find graph clustering partitions for complete graphs. 展开 关键词: Clustering coefficient – Graph clustering – Combinatorial optimization DOI: 10.1007/s13173-010-0027-x 年份: 2011 ...
van Dongen, Stijn, Graph clustering via a discrete uncoupling process, Siam Journal on Matrix Analysis and Applications 30-1, p121-141, 2008.https://doi.org/10.1137/040608635. The algorithm was conceived in 1998 andfirst published in a technical report in 1998. A PhD thesis and three more...
structure. It is shown that the proposed electrostatic graph algorithm generates graphs with node-measures that are more representative of the structure of the source time-series than the visibility graph. This makes the proposed algorithm more natural rather than algebraic, in comparison with existing...
theconnectome1that can be modeled and analyzed with the tools of network science and graph theory2. Modeling the brain as a network allows us to explore local as well as distributed properties of brain organization, using both descriptive3and generative modeling approaches4. A hallmark of...
[74], users are clustered into different groups using graph clustering, food ingredients are embedded using deep learning techniques, and based on user and food information, the top few foods are recommended to the target customers. Adding other selection techniques and criteria to select more ...
We conduct an overall performance comparison of WBCP with other methods firstly, then we analyze the performance of the feature extraction and prediction components of the WBCP scheme separately. For feature extraction, we employ visual analysis; additionally, for prediction, we evaluate multiple ...
we utilized Moran’s I and Z-value to check the non-stationarity of model space and observed that GL and GWR models would have independent assumptions and inefficient model coefficient estimates. In addition, according to the spatial residual correlation graph drawn at every 300 m, the Moran’s...
Hierarchical clustering tree and co-expression module of lncRNAs. At the top of the graph was a clustering tree of lncRNAs, and at the bottom were different modules cut from the dynamic cutting tree (different colors represent different modules) Full size image Finally, black, blue, brown, gree...
elegans. However, the observation of small-world structure in this organism has been built on a simplification of the weighted wiring diagram to a binary graph. For this reason, we studied both binary and weighted versions of this canonical network. However, even when using the weighted SWP, ...
(a) Dice coefficient graph. (b) Precision graph. The proposed method (blue) represents higher accuracy compared with the BET (orange) and iBEAT (gray). Full size image Figure 8 Brain extraction results of BET and the proposed method using the dHCP brain datasets. (a) the representative ...