Partition-based high dimensional similarity join method

Details Partition-based high dimensional similarity join method Partition-based high dimensional similarity join method

2007-01-23

2007-01-23

Corrielus, Jean M. (Department: 2166)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000, C707S793000, C707S793000

Reexamination Certificate

active

10639597

ABSTRACT:
A partition-based high dimensional similarity join method allowing similarity to be efficiently measured by beforehand dynamically selecting space partitioning dimensions and the number of the partitioning dimensions using a dimension selection algorithm. A method of efficiently performing similarity join for high dimensional data during a relatively short period of time without requiring massive storage space. The method includes according to the present invention comprises the steps of partitioning a high dimensional data space and performing joins between predetermined data sets. Dimensions for use in partitioning the high dimensional data space and the number of partitioning dimensions are determined in advance before the space partitioning, and the joins are performed only when respective cells of the data sets are overlapping with each other or are neighboring each other.

REFERENCES:
patent: 5987468 (1999-11-01), Singh et al.
patent: 11-242688 (1999-09-01), None
Kyuseok Shim, et al./ “High Dimensional Similarity Joins”/Proceedings of the 1997 IEEE International Conference on Data Engineering, 1997.
Christian Bohm, et al./ Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data/ Proceedings of the 2001 ACM-SIGMOD Conference, 2001.

Affiliated with

Also associated with

Rating

Partition-based high dimensional similarity join method does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Partition-based high dimensional similarity join method, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Partition-based high dimensional similarity join method will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3765264