INFORMATION CONVERSION DEVICE AND INFORMATION SEARCH DEVICE

• US 20130262489A1
• Filed: 12/18/2012
• Published: 10/03/2013
• Est. Priority Date: 03/28/2012
• Status: Abandoned Application

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: SHIRAKAWA, Shinichi
• Application Number:
  US13/718,146
• Publication Number:
  US 20130262489A1
• Time in Patent Office: Days
• US Class Current: 707/756
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/24558 Binary matching operations

Abstract

An information conversion device includes a memory and a processor coupled to the memory. The processor executes a process including converting a feature quantity vector of data which is a target of a search process using a Hamming distance into a symbol string including a binary symbol and a wild card symbol that causes a Hamming distance from the binary symbol to be zero (0).

Claims

1. An information conversion device comprising:

a memory; and

a processor coupled to the memory, wherein the processor executes a process comprising converting a feature quantity vector of data which is a target of a search process using a Hamming distance into a symbol string including a binary symbol and a wild card symbol that causes a Hamming distance from the binary symbol to be zero (0).

2. The information conversion device according to claim 1,

wherein the converting includes converting the feature quantity vector into the symbol string such that when a certain component of the feature quantity vector of the data which is the target of the search process using the Hamming distance falls within a predetermined range from a boundary with a feature quantity vector of a different class, the certain component is converted into the wild card symbol that causes the Hamming distance from the binary symbol to be zero (0), and when the certain component of the feature quantity vector of the data which is the target of the search process using the Hamming distance does not fall within the predetermined range from the boundary with the feature quantity vector of the different class, the certain component is converted into a binary symbol.

3. The information conversion device according to claim 1,

wherein the converting includes calculating a product of a predetermined conversion matrix and the feature quantity vector, and

converting the feature quantity vector into the symbol string such that when a certain component of the calculated product is included in a predetermined range, the certain component is converted into the wild card symbol, and when the component is not included in the predetermined range, the certain component is converted into a binary symbol corresponding to a value of the component.

4. The information conversion device according to claim 1,

wherein the process further comprises:

extracting a plurality of pieces of data from the data which is a target of a search process using a Hamming distance;

evaluating a predetermined conversion function based on a distance between feature quantity vectors of the data extracted at the extracting and a Hamming distance between symbol strings obtained by converting the feature quantity vectors by the predetermined conversion function; and

optimizing a parameter of the predetermined conversion function based on evaluation at the evaluating,

wherein the converting includes converting the feature quantity vector of the data into the symbol string using a conversion function having the parameter optimized at the optimizing.

5. The information conversion device according to claim 4,

wherein the evaluating includes decreasing an evaluation value of the conversion function, when the data extracted at the extracting belongs to the same class and the Hamming distance between the symbol strings converted from the data extracted at the extracting is a predetermined value or less, or when the data extracted at the extracting belongs to different classes and the Hamming distance between the symbol strings converted from the data extracted at the extracting is the predetermined value or more, and

the optimizing includes optimizes the parameter such that an upper limit of the evaluation value is decreased.

6. The information conversion device according to claim 1,

Wherein the process further comprises:

storing the data in association with a symbol string converted from the feature quantity vector of the data at the converting; and

searching data associated with a symbol string that a Hamming distance from a binary string converted from query data is a predetermined value or less from among data stored at the storing.

7. An information search device comprising:

a memory; and

a processor coupled to the memory, wherein the processor executes a process comprising;

converting a feature quantity vector of data which is a target of a search process using a Hamming distance into a symbol string including a binary symbol and a wild card symbol that causes a Hamming distance from the binary symbol to be zero (0); and

searching data that causes a Hamming distance between a symbol string converted at the converting and a binary string converted from query data is a predetermined value or less from among the data.

8. An information conversion method comprising executing, by an information conversion device that manages data which is a target of a search process using a Hamming distance, a process of converting a feature quantity vector of the data into a symbol string including a binary symbol and a wild card symbol that causes a Hamming distance from the binary symbol to be zero (0), using a processor.

9. The information conversion method according to claim 8,

wherein the converting includes converting the feature quantity vector into the symbol string such that when a certain component of the feature quantity vector of the data which is the target of the search process using the Hamming distance falls within a predetermined range from a boundary with a feature quantity vector of a different class, the certain component is converted into the wild card symbol that causes the Hamming distance from the binary symbol to be zero (0), and when the certain component of the feature quantity vector of the data which is the target of the search process using the Hamming distance does not fall within the predetermined range from the boundary with the feature quantity vector of the different class, the certain component is converted into a binary symbol.

10. The information conversion method according to claim 8,

wherein the converting includes calculating a product of a predetermined conversion matrix and the feature quantity vector, and

converting the feature quantity vector into the symbol string such that when a certain component of the calculated product is included in a predetermined range, the certain component is converted into the wild card symbol, and when the component is not included in the predetermined range, the certain component is converted into a binary symbol corresponding to a value of the component.

11. The information conversion method according to claim 8,

wherein the process further comprises:

extracting a plurality of pieces of data from the data which is a target of a search process using a Hamming distance;

evaluating a predetermined conversion function based on a distance between feature quantity vectors of the data extracted at the extracting and a Hamming distance between symbol strings obtained by converting the feature quantity vectors by the predetermined conversion function; and

optimizing a parameter of the predetermined conversion function based on evaluation at the evaluating,

wherein the converting includes converting the feature quantity vector of the data into the symbol string using a conversion function having the parameter optimized at the optimizing.

12. The information conversion method according to claim 11,

wherein the evaluating includes decreasing an evaluation value of the conversion function, when the data extracted at the extracting belongs to the same class and the Hamming distance between the symbol strings converted from the data extracted at the extracting is a predetermined value or less, or when the data extracted at the extracting belongs to different classes and the Hamming distance between the symbol strings converted from the data extracted at the extracting is the predetermined value or more, and

the optimizing includes optimizes the parameter such that an upper limit of the evaluation value is decreased.

13. The information conversion method according to claim 8,

wherein the process further comprises:

storing the data in association with a symbol string converted from the feature quantity vector of the data at the converting; and

searching data associated with a symbol string that a Hamming distance from a binary string converted from query data is a predetermined value or less from among data stored at the storing.

14. An information search method comprising:

converting a feature quantity vector of data which is a target of the search process into a symbol string including a binary symbol and a wild card symbol that causes a Hamming distance from the binary symbol to be zero (0), using a processor; and

searching data that causes a Hamming distance between the converted symbol string and a binary string converted from query data is a predetermined value or less, using the processor.

15. A computer-readable recording medium having stored therein a program for causing a computer to execute an information conversion process comprising converting a feature quantity vector of data which is a target of a search process using a Hamming distance into a symbol string including a binary symbol and a wild card symbol that causes a Hamming distance from the binary symbol to be zero (0).

16. A computer-readable recording medium having stored therein a program for causing a computer to execute an information search process comprising:

converting a feature quantity vector of data which is a target of the search process into a symbol string including a binary symbol and a wild card symbol that causes a Hamming distance from the binary symbol to be zero (0); and

searching data that causes a Hamming distance between the converted symbol string and a binary string converted from query data is a predetermined value or less.