Random graph generator

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Random graph generator may not have real life implementations but it offers nice test suite for Wandora and topics maps. It is also interesting to note that the association distribution of random topic maps are variations of bell curves rather than power law curves found in many real life graphs.
 
Random graph generator may not have real life implementations but it offers nice test suite for Wandora and topics maps. It is also interesting to note that the association distribution of random topic maps are variations of bell curves rather than power law curves found in many real life graphs.
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You should also note that creating very dense topic map requires much memory as the number of associations increases.

Revision as of 20:40, 8 June 2007

Random graph generator creates a topic map with random number of topics and associations between. New topics and associations are created to current layer. Random graph generator has two different association creation algorithms. First algorithm is

  1. Create n topics
  2. Loop m times
    1. Select two random topics
    2. Create association between selected topics

Here n and m are integers given by the user. Note the possibility of two or more identical associations. Wandora's topic map model merges identical associations and the overall number of associations created by the algorithm may be smaller than m. Second algrithm relies on association probability and is

  1. Create n topics
  2. For each topic combination (n * n)
    1. Get random number
    2. if random number is bigger than given limit p then create association between the topic combination

Here n and p are user defined. n is integer while p is a float between 0 and 1.

Random graph generator may not have real life implementations but it offers nice test suite for Wandora and topics maps. It is also interesting to note that the association distribution of random topic maps are variations of bell curves rather than power law curves found in many real life graphs.

You should also note that creating very dense topic map requires much memory as the number of associations increases.

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