Data processing: artificial intelligence – Neural network – Structure
Reexamination Certificate
2005-04-19
2005-04-19
Davis, George (Department: 2121)
Data processing: artificial intelligence
Neural network
Structure
C706S050000
Reexamination Certificate
active
06882991
ABSTRACT:
The invention relates to a method of searching a predetermined number of objects which are closest to an example, in a hierarchical object structure which is obtained by using a hierarchical object classification method.The proposed method consists of going through the hierarchical structure starting from the root, descending as far as the first node closest to the searched example of which a number of leaves lower than the number of lacking results depend, and then going back up to the brother node of this node which is closest to the searched example, so as to add other results and so on and so forth until said predetermined number is arrived at. Application: MPEG-7 descriptions.
REFERENCES:
patent: 5832182 (1998-11-01), Zhang et al.
patent: WO9923578 (1998-10-01), None
Khaled Alsabti et al, “An Efficeint K-Means Clustering Algorithm”, IPPS/SPDP Workshop on High Performance Data Mining, 1998, Orlando FL.
S. Pramanik et al; “An Efficient Searching Algorithm for Approximate Nearest Neighbor Queries in the Dimensions”, Proceedings of ICMCS99: IEEE Multimedia Systems '99: International Conference on Multimedia Comuting and Systems, Florence, Italy, Jun. 7-11, 1999, pp. 865-869, vol. 1, XP002174907.
Mory Benoit
Santini Nicolas
Davis George
Koninklijke Philips Electronics , N.V.
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