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Binary-Tree-for-Large-Dimension-Data-Search

This small preject is try to use binary tree to speedup the data whose dimension is very large.

Develop tools and techniques

  • Java
  • NetBeans

Step

  1. Generate 1000000 datas with 10 dimensions, and every dimension is generated by Gaussian distribution
  2. Construct a binary search tree for every dimension
  3. Sort query vector from big attribute to small attribute
  4. Search binary serach tree with accuracy for the biggest dimension of the query and get some similar datas which can be viewed as candidate
  5. For the remaining candidates, we search other dimension by linear search
  6. Get a set of data which is similar to the query

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