Compressing Graphs with combinatorial functions
I am working on a project that its goal is text compression. First by using Lampel-Ziv algorithm, I turned text to numerical codes. Then map this codes to a data structure (Graph or tree) and solve it with submodular functions.
Is it better to build a tree for each sentence or there is a better way? and how partitioning or clustering this jungle (graph) and applying submodualr combinatorial optimization algorithms to this problem?
Please help me to convert this procedure to submodular functions optimization problems (Constrained or Unconstrained). If their exists a better way for the problem, your suggestion are welcome.
Thanks in advance
I am working on a project that its goal is text compression. First by using Lampel-Ziv algorithm, I turned text to numerical codes. Then map this codes to a data structure (Graph or tree) and solve it with submodular functions.
Is it better to build a tree for each sentence or there is a better way? and how partitioning or clustering this jungle (graph) and applying submodualr combinatorial optimization algorithms to this problem?
Please help me to convert this procedure to submodular functions optimization problems (Constrained or Unconstrained). If their exists a better way for the problem, your suggestion are welcome.
Thanks in advance
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