SYSTEM AND METHOD FOR MANAGING DIGITAL CONTENTS

• US 20120117090A1
• Filed: 11/01/2011
• Published: 05/10/2012
• Est. Priority Date: 11/04/2010
• Status: Abandoned Application

• Current Assignee: Electronics and Telecommunications Research Institute
• Original Assignee: Electronics and Telecommunications Research Institute
• Inventors: Chung, Yun Su, Park, So Hee, Kim, Jeong Nyeo, Cho, Hyun Sook, Lee, Han Sung, Lee, Yong Jin
• Application Number:
  US13/286,682
• Publication Number:
  US 20120117090A1
• Time in Patent Office: Days
• US Class Current: 707/752
• CPC Class Codes: G06F 16/3347 using vector based model
• CPC Class Codes: G06F 16/353 into predefined classes

Abstract

Disclosed are a system and method for managing digital contents. An exemplary embodiment according to the present invention provides to a system for managing digital contents, including a learning module extracting feature vectors of input digital contents and performing column subspace mapping on the feature vectors to calculate a column subspace projection matrix; an index module using the matrix to perform an index work on the digital contents and then, storing the matrix and the digital contents; and a search module performing the column subspace mapping on the feature vectors of query data when the query data for searching the digital contents are input and searching the digital contents indexed by the matrix having high similarity to the mapped feature vectors of the query data.

Claims

1. A system for managing digital contents, comprising:

a learning module extracting feature vectors of input digital contents and performing column subspace mapping on the feature vectors to calculate a column subspace projection matrix;

an index module using the matrix to perform an index work on the digital contents and then, storing the matrix and the digital contents; and

a search module performing the column subspace mapping on the feature vectors of query data when the query data for searching the digital contents are input and searching the digital contents indexed by the matrix having high similarity to the mapped feature vectors of the query data.

2. The system of claim 1, wherein the learning module includes:

a sort unit sorting a type of the digital contents;

a feature extraction unit extracting the feature vectors of the digital contents in a predetermined manner according to the sorting; and

a subspace learning unit performing subspace learning on the feature vectors to calculate a column subspace projection matrix.

3. The system of claim 2, wherein the sort unit sorts the digital contents based on a text, a still image, an audio, and a moving picture.

4. The system of claim 2, wherein the feature extraction unit extracts the feature vectors using a word frequency when the digital contents is a text, extracts the feature vectors by a method including a color histogram when the digital contents is a still image, and extracts the feature vectors by a method including a multi-modality method when the digital contents is an audio or a moving picture.

5. The system of claim 2, wherein the subspace learning unit calculates the matrix (CSM) using following Equation 1 or Equation 2

CSM=A^T(AA^T)⁻

1  

 

Equation 1;

CSM=(A^TA)<sup>−

1</sup>A^T (where, A is the feature vectors).  

 

Equation 2;

6. A method for managing digital contents, comprising:

extracting feature vectors of input digital contents;

calculating a column subspace projection matrix performing column subspace mapping on the feature vectors; and

storing the matrix and the digital contents after performing an index work on the digital contents using the matrix.

7. The method of claim 6, further comprising:

performing the column subspace mapping on the feature vectors of query data when the query data for searching the digital contents are input; and

searching the digital contents indexed by the matrix having high similarity to the mapped feature vectors of the query data.

8. The method of claim 6, wherein the extracting of the feature vectors includes:

sorting a type of the digital contents;

extracting the feature vectors of the digital contents in a predetermined manner according to the sorting; and

calculating the column subspace projection matrix by performing the column subspace learning on the feature vectors.

9. The method of claim 8, wherein the extracting of the feature vectors includes at least one of:

extracting the feature vectors using a word frequency when the digital contents is a text;

extracting the feature vectors by a method including a color histogram when the digital contents is a still image; and

extracting the feature vectors by a method including a multi-modality method when the digital contents is an audio or a moving picture.

10. The method of claim 6, wherein the calculating calculates the matrix using following Equation 1 or Equation 2

CSM=A^T(AA^T)⁻

1  

 

Equation 1;

CSM=(A^TA)<sup>−

1</sup>A^T (where, A is the feature vectors).  

 

Equation 2;