Subgraph matching on a large graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including question answering and community detection. However, traditional edge-cutting strategy destroys the structure of indivisible knowledge in a large RDF graph. On the premise of load-balancing on subgraph division, a dominance-partitioned strategy is proposed to divide a large RDF graph without compromising the knowledge structure. Firstly, a dominance-connected pattern graph is extracted from a pattern graph (...) to construct a dominance-partitioned pattern hypergraph, which divides a pattern graph as multiple fish-shaped pattern subgraphs. Secondly, a dominance-driven spectrum clustering strategy is used to gather the pattern subgraphs into multiple clusters. Thirdly, the dominance-partitioned subgraph matching algorithm is designed to conduct all isomorphic subgraphs on a cluster-partitioned RDF graph. Finally, experimental evaluation verifies that our strategy has higher time-efficiency of complex queries, and it has a better scalability on multiple machines and different data scales. (shrink)

Although prior studies have extensively investigated the effect of working conditions upon professional satisfaction, the cross-national variance in the effect remains largely understudied due to technical or financial restrictions. The Teaching and Learning International Survey provides an opportunity to investigate the cross-country differences in the impact of working conditions upon principals’ professional satisfaction. The current study attempts to investigate the overall and specific effects of principals’ workplace environment satisfaction, rewards satisfaction, and workload stress on their professional satisfaction in 47 countries (...) included in the TALIS 2018. The results indicate that workplace environment, rather than the typically regarded effort-reward issues, is the most powerful contributor to individual principals’ professional satisfaction across 47 countries, while, in countries with low overall professional satisfaction, rewards satisfaction and workload stress are more powerful predictors for principals’ professional satisfaction on the country level. This study may inform policymakers in school principal stimulation and retention that effective practice to stimulate and/or retain school principals may vary across countries and research findings derived from data on the individual level may not be applicable to practice on the country level. (shrink)

Continuous subgraph matching problem on dynamic graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including information retrieval and community detection. Specifically, given a query graph q, an initial graph G 0, and a graph update stream △ G i, the problem of continuous subgraph matching is to sequentially conduct all possible isomorphic subgraphs covering △ G i of q on G i. Since knowledge graph is a directed labeled (...) multigraph having multiple edges between a pair of vertices, it brings new challenges for the problem focusing on dynamic knowledge graph. One challenge is that the multigraph characteristic of knowledge graph intensifies the complexity of candidate calculation, which is the combination of complex topological and attributed structures. Another challenge is that the isomorphic subgraphs covering a given region are conducted on a huge search space of seed candidates, which causes a lot of time consumption for searching the unpromising candidates. To address these challenges, a method of subgraph-indexed sequential subdivision is proposed to accelerating the continuous subgraph matching on dynamic knowledge graph. Firstly, a flow graph index is proposed to arrange the search space of seed candidates in topological knowledge graph and an adjacent index is designed to accelerate the identification of candidate activation states in attributed knowledge graph. Secondly, the sequential subdivision of flow graph index and the transition state model are employed to incrementally conduct subgraph matching and maintain the regional influence of changed candidates, respectively. Finally, extensive empirical studies on real and synthetic graphs demonstrate that our techniques outperform the state-of-the-art algorithms. (shrink)