# US 2014/0195501 A1 · System and method for fingerprinting datasets

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- Number: US 2014/0195501 A1
- Document ID: US20140195501A1
- Status: Published application
- Kind: A1
- Application number: 14/169,218
- Filed: 2014-01-31
- Published: 2014-07-10
- Earliest claimed: 2012-03-28
- Assignees: Interactive Intelligence, Inc.
- Applicants: Interactive Intelligence, Inc.
- Inventors: Kevin Vlack; Felix Immanuel Wyss
- Web page: https://patentgrep.com/patent/US20140195501A1

## CPC

- G06F 16/284: {Relational databases}
- G06F 16/683: using metadata automatically derived from the content
- G10L 19/018: Audio watermarking, i.e. embedding inaudible data in the audio signal
- G10L 25/54: for retrieval
- H03M 7/3059: {Digital compression and data reduction techniques where the original information is represented by a subset or similar information, e.g. lossy compression}
- H03M 7/3066: {by means of a mask or a bit-map}
- H03M 7/3082: {Vector coding (for television signals, see H04N19/94)}
- H04M 3/5158: {in combination with automated outdialling systems (devices for signalling identity of wanted subscriber H04M1/26)}
- H04M 2203/2027: Live party detection
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- H03M: CODING; DECODING; CODE CONVERSION IN GENERAL (using fluidic means F15C4/00; optical analogue/digital converters G02F7/00; coding, decoding or code conversion, specially adapted for particular applications, see the relevant subclasses, e.g. G01D, G01R, G06F, G06T, G09G, G10L, G11B, G11C, H04B, H04L, H04M, H04N; ciphering or deciphering for cryptography or other purposes involving the need for secrecy G09C)
- H04M: TELEPHONIC COMMUNICATION (circuits for controlling other apparatus via a telephone cable and not involving telephone switching apparatus G08)

## 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.

## Claims

### Claim 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;
c. after step (b), computing another compressed representation of the dataset;
d. repeating steps (b) and (c) a plurality of times to create a plurality of compressed representations; and
e. combining the plurality of compressed representations into a weighted compressed representation, where each weight in the weighted compressed representation is computed as a function of elements in the plurality of compressed representations.

### Claim 2 (depends on 1)

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

### Claim 3 (depends on 2)

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

### Claim 4 (depends on 3)

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

### Claim 5 (depends on 1)

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

### Claim 6 (depends on 5)

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

### Claim 7 (depends on 1)

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.

### Claim 8 (depends on 7)

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.

### Claim 9 (depends on 8)

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

### Claim 10 (depends on 8)

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

### Claim 11 (depends on 8)

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.

### Claim 12 (depends on 1)

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

### Claim 13 (depends on 12)

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