System and method for fingerprinting datasets

Patent metadata

Field	Value
Publication number	US-9679042-B2
Application number	US-201414169218-A
Country	US
Kind code	B2
Filing date	Jan 31, 2014
Priority date	Mar 28, 2012
Publication date	Jun 13, 2017
Grant date	Jun 13, 2017

Abstract

Systems and methods for the matching of datasets, such as input audio segments, with known datasets in a database are disclosed. In an illustrative embodiment, the use of the presently disclosed systems and methods is described in conjunction with recognizing known network message recordings encountered during an outbound telephone call. The methodologies include creation of a ternary fingerprint bitmap to make the comparison process more efficient. Also disclosed are automated methodologies for creating the database of known datasets from a larger collection of datasets.

First claim

What is claimed is:

1. A method for creating a weighted compressed representation of a dataset, the method comprising the steps of:
a. computing a compressed representation of the dataset;
b. applying a transformation to the dataset to create a transformed dataset;
c. after step (b), computing another compressed representation of the transformed dataset;
d. repeating steps (b) and (c) a plurality of times to create a plurality of compressed representations of the dataset; and
e. combining the plurality of compressed representations into a weighted compressed representation of the dataset, where each weight in the weighted compressed representation is computed as a function of elements in the plurality of compressed representations.

2. The method of claim 1 , wherein said compressed representation is a two-dimensional vector of first numbers.

3. The method of claim 2 , wherein said first numbers are each represented with a first number of bits.

4. The method of claim 3 , wherein said first number of bits is one.

5. The method of claim 1 , wherein said weighted compressed representation is a two-dimensional vector of second numbers.

6. The method of claim 5 , wherein said second numbers are represented with a second number of bits each.

7. The method of claim 1 , wherein said function computes said each weight as a correlation coefficient of the elements in said plurality of compressed representations.

8. The method of claim 7 , wherein said correlation coefficient is computed as follows:
(1) If an element is below a first predetermined threshold in a first predetermined number of said plurality of compressed representations, set the correlation coefficient to a first value;
(2) If an element is above a second predetermined threshold in a second predetermined number of said plurality of compressed representations, set the correlation coefficient to a second value;
(3) Otherwise, set the correlation coefficient to a third value.

9. The method of claim 8 , wherein said first value is +1, said second value is −1, and said third value is 0 (zero).

10. The method of claim 8 , wherein said first predetermined threshold is 1 (one) and said second predetermined threshold is 0 (zero).

11. The method of claim 8 , wherein said first predetermined number comprises all of the plurality of compressed representations and said second predetermined number comprises all of the plurality of compressed representations.

12. The method of claim 1 , wherein said transformation comprises deleting a first number of elements from said dataset.

13. The method of claim 12 , wherein said first number is one.

Assignees

• Interactive Intelligence Inc
• Interactive Intelligence Group Inc

Inventors

• Vlack Kevin
• Wyss Felix Immanuel

Classifications

• H03M7/3066

  by means of a mask or a bit-map · CPC title

• H03M7/3082

  Vector coding (for television signals, see H04N19/94) · CPC title

• G06F16/683

  using metadata automatically derived from the content · CPC title

• G06F16/284 Primary

  Relational databases · CPC title

• H04M3/5158 Primary

  in combination with automated outdialling systems (devices for signalling identity of wanted subscriber H04M1/26) · CPC title