For the purpose of investigating conditions of earthquake pregnancies,a heterogeneous 2-D single fault model with 81 × 81 cells is set up. By using cellular automata models and changing the model heterogeneity an...For the purpose of investigating conditions of earthquake pregnancies,a heterogeneous 2-D single fault model with 81 × 81 cells is set up. By using cellular automata models and changing the model heterogeneity and correlation parameters, we compute and get different synthetic event catalogues for analyzing general seismic activity and intensity distribution properties. The results show that different heterogeneous structures produce different seismic sequence types and G-R relationship,so the heterogeneity is an important influencing factor on seismicity. Nevertheless,both the coefficients of stress redistribution and local friction loss can also influence seismicity to some extent. This is possibly useful for further understanding of the complexity of earthquake processes.展开更多
Information networks that can be extracted from many domains are widely studied recently. Different functions for mining these networks are proposed and developed, such as ranking, community detection, and link predic...Information networks that can be extracted from many domains are widely studied recently. Different functions for mining these networks are proposed and developed, such as ranking, community detection, and link prediction. Most existing network studies are on homogeneous networks, where nodes and links are assumed from one single type. In reality, however, heterogeneous information networks can better model the real-world systems, which are typically semi-structured and typed, following a network schema. In order to mine these heterogeneous information networks directly, we propose to explore the meta structure of the information network, i.e., the network schema. The concepts of meta-paths are proposed to systematically capture numerous semantic relationships across multiple types of objects, which are defined as a path over the graph of network schema. Meta-paths can provide guidance for search and mining of the network and help analyze and understand the semantic meaning of the objects and relations in the network. Under this framework, similarity search and other mining tasks such as relationship prediction and clustering can be addressed by systematic exploration of the network meta structure. Moreover, with user＇s guidance or feedback, we can select the best meta-path or their weighted combination for a specific mining task.展开更多
基金funded by the National Natural Science Foundation of China ( Grant No. 40774015)
文摘For the purpose of investigating conditions of earthquake pregnancies,a heterogeneous 2-D single fault model with 81 × 81 cells is set up. By using cellular automata models and changing the model heterogeneity and correlation parameters, we compute and get different synthetic event catalogues for analyzing general seismic activity and intensity distribution properties. The results show that different heterogeneous structures produce different seismic sequence types and G-R relationship,so the heterogeneity is an important influencing factor on seismicity. Nevertheless,both the coefficients of stress redistribution and local friction loss can also influence seismicity to some extent. This is possibly useful for further understanding of the complexity of earthquake processes.
基金supported in part by the U.S.Army Research Laboratory under Cooperative Agreement No.W911NF-09-2-0053(NS-CTA),NSF ⅡS-0905215,CNS-09-31975MIAS,a DHS-IDS Center for Multimodal Information Access and Synthesis at UIUC
文摘Information networks that can be extracted from many domains are widely studied recently. Different functions for mining these networks are proposed and developed, such as ranking, community detection, and link prediction. Most existing network studies are on homogeneous networks, where nodes and links are assumed from one single type. In reality, however, heterogeneous information networks can better model the real-world systems, which are typically semi-structured and typed, following a network schema. In order to mine these heterogeneous information networks directly, we propose to explore the meta structure of the information network, i.e., the network schema. The concepts of meta-paths are proposed to systematically capture numerous semantic relationships across multiple types of objects, which are defined as a path over the graph of network schema. Meta-paths can provide guidance for search and mining of the network and help analyze and understand the semantic meaning of the objects and relations in the network. Under this framework, similarity search and other mining tasks such as relationship prediction and clustering can be addressed by systematic exploration of the network meta structure. Moreover, with user＇s guidance or feedback, we can select the best meta-path or their weighted combination for a specific mining task.
