APPARATUS FOR RECOMMENDING CONTENTS USING HIERARCHICAL CONTEXT MODEL AND METHOD THEREOF

• US 20150026166A1
• Filed: 07/22/2014
• Published: 01/22/2015
• Est. Priority Date: 07/22/2013
• Status: Abandoned Application

• Current Assignee: Gwangju Institute of Science and Technology
• Original Assignee: Gwangju Institute of Science and Technology
• Inventors: HAN, Jong Hyun, WOO, Woontack
• Application Number:
  US14/338,004
• Publication Number:
  US 20150026166A1
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information

Abstract

According to an embodiment of the present invention, an apparatus for recommending contents using a hierarchical context model includes: an input unit configured to receive a keyword to be retrieved from a user according to an operation of a key or a menu; a sensing unit configured to acquire context information of the user when the keyword is received; a control unit configured to match tag information of contents and the context information of the user corresponding to the received keyword with preset hierarchical context models, respectively to extract contents relevant words and context relevant words based on the matched results and calculate contents similarity based on the extracted contents relevant words and context relevant words to rank at least one pre-collected contents based on the calculated contents similarity; and a display unit configured to display some or all of the at least one ranked contents on a screen.

Claims

1. An apparatus for recommending contents using a hierarchical context model, the apparatus comprising:

an input unit configured to receive a keyword to be retrieved from a user according to an operation of a key or a menu;

a sensing unit configured to acquire context information of the user when the keyword is received;

a control unit configured to match tag information of contents and the context information of the user corresponding to the received keyword with preset hierarchical context models, respectively to extract contents relevant words and context relevant words based on the matched results and calculate contents similarity based on the extracted contents relevant words and context relevant words to rank at least one pre-collected contents based on the calculated contents similarity; and

a display unit configured to display some or all of the at least one ranked contents on a screen.

2. The apparatus of claim 1, wherein the control unit confirms whether the acquired context information of the user is updated when the context information of the user is acquired, and

maps the acquired context information of the user to the hierarchical context model when the context information of the user is updated.

3. The apparatus of claim 2, wherein the control unit confirms whether the acquired context information of the user is updated when the context information of the user is acquired, and

does not map the acquired context information of the user to the hierarchical context model when the context information of the user is not updated.

4. The apparatus of claim 1, wherein the contents similarity is obtained by Equation

5. The apparatus of claim 4, wherein the similarity is obtained by Equation sim(x,y)=spec(LCS(x,y)) when tax=x and ctx=y,

in the above Equation, LCS (x, y) represents a least common subsumer between node x and node y.

6. The apparatus of claim 1, wherein the control unit matches the tag information of the contents with the preset hierarchical context model to extract contents relevant words based on the matched result, and

extracts the contents relevant words from a node corresponding to the tag information of the contents and all upper nodes connected to the node within the hierarchical context model.

7. The apparatus of claim 1, wherein the control unit matches the context information of the user with the preset hierarchical context model to extract context relevant words based on the matched result, and

extracts the context relevant words from a node corresponding to the context information of the user and all upper nodes connected to the node within the hierarchical context model.

8. The apparatus of claim 1, further comprising:

a storage unit configured to store the hierarchical context model for recommending contents to be retrieved by the user.

9. An apparatus for recommending contents using a hierarchical context model, the apparatus comprising:

an input unit configured to receive a keyword to be retrieved from a user according to an operation of a key or a menu;

a control unit configured to match tag information of contents and context information of a user corresponding to the received keyword with preset hierarchical context models, respectively to extract contents relevant words and context relevant words based on the matched results and calculate contents similarity based on the extracted contents relevant words and context relevant words to rank at least one pre-collected contents based on the calculated contents similarity; and

a display unit configured to display some or all of the at least one ranked contents on a screen.

10. The apparatus of claim 9, wherein the control unit confirms whether the acquired context information of the user is updated when the context information of the user is acquired, and

maps the acquired context information of the user to the hierarchical context model when the context information of the user is updated.

11. The apparatus of claim 10, wherein the control unit confirms whether the acquired context information of the user is updated when the context information of the user is acquired, and

does not map the acquired context information of the user to the hierarchical context model when the context information of the user is not updated.

12. The apparatus of claim 9, wherein the contents similarity is obtained by Equation

13. The apparatus of claim 12, wherein the similarity is obtained by Equation sim(x,y)=spec(LCS(x,y)) when tax=x and ctx=y,

in the above Equation, LCS (x, y) represents a least common subsumer between node x and node y.

14. A method for recommending contents using a hierarchical context model, the method comprising:

receiving a keyword to be retrieved from a user according to an operation of a key or a menu;

matching tag information of contents and context information of the user corresponding to the received keyword with preset hierarchical context models, respectively to extract contents relevant words and context relevant words based on the matched result;

calculating contents similarity based on the extracted contents relevant words and context relevant words and ranking at least one pre-collected contents based on the calculated contents similarity; and

displaying some or all of the at least one ranked contents on a screen.

15. The method of claim 14, wherein in the extracting, when the context information of the user is acquired, it is confirmed whether the acquired context information of the user is updated, and

when the context information of the user is updated, the acquired context information of the user maps the hierarchical context model.

16. The method of claim 15, wherein in the extracting, when the context information of the user is acquired, it is confirmed whether the acquired context information of the user is updated, and

when the context information of the user is not updated, the acquired context information of the user does not map the hierarchical context model.

17. The method of claim 14, wherein the contents similarity is obtained by Equation

18. The method of claim 17, wherein the similarity is obtained by Equation sim(x,y)=spec(LCS(x,y)) when tax=x and ctx=y,

in the above Equation, LCS (x, y) represents a least common subsumer between node x and node y.

19. The method of claim 14, wherein in the extracting, the tag information of the contents matches the preset hierarchical context model to extract contents relevant words based on the matched result, and

the contents relevant words are extracted from a node corresponding to the tag information of the contents and all upper nodes connected to the node within the hierarchical context model.

20. The method of claim 14, wherein in the extracting, the context information of the user matches the preset hierarchical context model to extract context relevant words based on the matched result, and

the context relevant words are extracted from a node corresponding to the context information of the user and all upper nodes connected to the node within the hierarchical context model.