Apparatus and method for combinatorial hypermap based data representations and operations
A technology of data representation and graph representation, applied in the field of apparatuses and methods for data representation and manipulation based on combined hypergraphs, and can solve problems such as multi-CPU time, consumption, etc.
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[0030] Graphs can provide powerful representations of knowledge and relationships in many domains. Graph databases store graph structures rather than tables of data. In general, graph databases can be applied in domains that need to store and retrieve complex topological information, such as neural networks, semantic networks, social networks, networks of related stories, scenes, routes, paths, roads, or geographic information systems (GIS). One of the main problems in graph databases is to retrieve membership graphs based on structural matching. Structural matching of graphs is a known NP-complete problem. In large graph databases, structural matching becomes very difficult because structural matching has to be performed against a large number of graphs in the database. Retrieval from dynamic topological graph databases is even harder than retrieval from pre-indexed attribute-based graph databases because there is no decomposition space and the space is always changing dyna...
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