Automatic Diagnosis With Efficient Medical Case Searching Based on Evolving Graphs
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2871769
Abstract: The clinical data are often multimodal and consist of both structured data and unstructured data. The modeling of clinical data has become a very important and challenging problem in healthcare big data analytics. Most existing… read more here.
Keywords: diagnosis; evolving graphs; method; graph ... See more keywords
Incremental Frequent Subgraph Mining on Large Evolving Graphs
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2017.2743075
Abstract: Frequent subgraph mining is a core graph operation used in many domains, such as graph data management and knowledge exploration, bioinformatics, and security. Most existing techniques target static graphs. However, modern applications, such as social… read more here.
Keywords: frequent subgraph; evolving graphs; large evolving; subgraph mining ... See more keywords
Accelerate Incremental TSP Algorithms on Time Evolving Graphs with Partitioning Methods
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DOI: 10.3390/a15020064
Abstract: In time-evolving graphs, the graph changes at each time interval, and the previously computed results become invalid. We addressed this issue for the traveling salesman problem (TSP) in our previous work and proposed an incremental… read more here.
Keywords: time; evolving graphs; accelerate incremental; time evolving ... See more keywords