Pattern discovery in multi-dimensional time series using...

Details Pattern discovery in multi-dimensional time series using... Pattern discovery in multi-dimensional time series using...

2006-09-05

2006-09-05

Mancuso, Joseph (Department: 2624)

Image analysis

Pattern recognition

C382S225000

Reexamination Certificate

active

07103222

ABSTRACT:
A method discovers patterns in unknown multi-dimensional data. A time-series of the multi-dimensional data is generated and a point cross-distance matrix is constructed by self-correlating the time-series. All minimum cost paths in the point cross-distance matrix are located at multiple time resolutions. The minimum cost paths are then related to temporal sub-sequences in the multi-dimensional data to discover high-level patterns in the unknown multi-dimensional data.

REFERENCES:
patent: 4718093 (1988-01-01), Brown
patent: 4982438 (1991-01-01), Usami et al.
patent: 5341437 (1994-08-01), Nakayama
patent: 5638460 (1997-06-01), Nishimori et al.
patent: 6014626 (2000-01-01), Cohen
patent: 6067369 (2000-05-01), Kamei
patent: 6369835 (2002-04-01), Lin
patent: 6477515 (2002-11-01), Boroujerdi et al.
patent: 6665852 (2003-12-01), Xing et al.
patent: 2001/0036304 (2001-11-01), Yang et al.
patent: 2003/0001862 (2003-01-01), Chu et al.
patent: 2003/0177112 (2003-09-01), Gardner
patent: 2003/0190060 (2003-10-01), Pengwu
Foote, J., “Visualizing music and audio using self-similarity,” Proceedings of International ACM Conference Multimedia, Oct. 1999, pp. 77-84.
Keogh, E. J., et al., “Scaling up dynamic time warping for data mining applications,” Proceedings, Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2000, pp. 285-289.
Cooper, M., et al., “Scene boundary detection via video self-similarity analysis,” Proceedings 2001 International Conference on Image Processing, Oct. 2001, pp. 378-381.
Helfman, J., “Dotplot patterns: literal look at pattern languages,” Theory and Practice of Object Systems, 1996, Wiley, USA, vol. 2, No. 1, pp. 31-41.
Zait, et al., “A comparative study of clustering methods,” Future Generate Computer Systems, vol. 13, 1997, pp. 149-159.
Zongker, et al., “Algorithms for Feature Selection: An Evaluation.”
Xu, et al., “Algorithms and System for Segmentation and Structure Analysisi n Soccer Video.”
Naphade, et al., “Probabilitic Multimedia Objects (Multijects): A Novel Approach to Video Indexing and Retrieval in Multimedia Systems.”
Aach, et al., “Aligning gene expression time series with time warping algorithms,” Bioinformatics, vol. 17, No. 6, 2001, pp. 495-508.
Agrawal, et al., “Efficient Similarity Search in Sequence Database.”
Church, et al., “Dotplot: A Program for Exploring Self-Similarity in Millions of Lines of Text and Code.”
Reynar, “An Automatic Method of Finding Topic Boundaries.”
Park, et al., “Efficient Searches for Similar Subsequences of Different Lengths in Sequence Databases.”
Mangiameli, et al., “A Comparison of SOM Neural Network and Hierarchical Clustering Methods,” European Journal of Operational Research, vol. 93, 1996, pp. 402-417.

Affiliated with

Also associated with

Rating

Pattern discovery in multi-dimensional time series using... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Pattern discovery in multi-dimensional time series using..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Pattern discovery in multi-dimensional time series using... will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3562129