Automated surfacing of tagged content in vertical applications

• US 9,235,648 B2
• Filed: 01/16/2008
• Issued: 01/12/2016
• Est. Priority Date: 01/16/2008
• Status: Active Grant

• Current Assignee: AirBNB Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: O'Sullivan, Patrick J., Stern, Edith H., Weir, Robert C., Willner, Barry E.
• Primary Examiner(s): Chbouki, Tarek
• Application Number:
  US12/015,245
• Publication Number:
  US 20090182713A1
• Time in Patent Office: 2,918 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9562 Bookmark management
• CPC Class Codes: G06F 40/109 Font handling; Temporal or kinetic typography
• CPC Class Codes: G06F 40/205 Parsing

Abstract

Embodiments of the present invention address deficiencies of the art in respect to social bookmarking and provide a method, system and computer program product for automated surfacing of tagged content in a vertical application. In an embodiment of the invention, a method for automatically surfacing tagged content in a vertical application can be provided. The method can include parsing text from content in an end user application, comparing the parsed text to social bookmarks and associated metadata in a social bookmarking system and matching portions of the content to respective ones of the social bookmarks based upon the comparison, and visually emphasizing the matched portions of the content in the end user application.

Claims

1. A method for automatically surfacing tagged content in a vertical application, the method comprising:

parsing text from content in an end user application;

comparing the parsed text to social bookmarks and associated metadata in a social bookmarking system to determine whether the parsed text matches at least one of the social bookmarks in the social bookmarking system by matching portions of the parsed text to respective ones of the social bookmarks and associated metadata; and

,

upon determining that the parsed text matches the at least one of the social bookmarks in the social bookmarking system, visually emphasizing the matched portions of the parsed text from the content in the end user application by determining a frequency of match to respective ones of the social bookmarks and associated metadata and adjusting a color of text associated with the matched portions of the parsed text proportionately based upon the determined frequency of match so as to visually differentiate the matched portions from the content.

2. The method of claim 1, wherein

comparing the parsed text to social bookmarks comprises restricting the parsed text to a limited vocabulary during the comparing.

3. The method of claim 1, further comprising

toggling the visual emphasis of the matched portions of the parsed text in the end user application.

4. The method of claim 1, further comprising

appending a source indicator in the end user application indicating which one of the social bookmarks for the visually emphasized matched portions of the parsed text.

5. The method of claim 1, wherein the color of text being adjusted is at least one of bolder and deeper for text associated with a high frequency of match to respective ones of the social bookmarks and associated metadata.

6. The method of claim 1, wherein visually emphasizing the matched portions of the parsed text from the content in the end user application by visually differentiating the matched portions of the parsed text from the content further comprises adjusting a font size of text associated with the matched portions of the parsed text proportionately based upon the determined frequency of match to respective ones of the social bookmarks and associated metadata.

7. The method of claim 6, wherein the font size of text being adjusted is greater for text associated with a high frequency of match to respective ones of the social bookmarks and associated metadata.

8. The method of claim 1, wherein the frequency of match is a number of occurrences that portions of the parsed text match respective ones of the social bookmarks and associated metadata.

9. A social bookmarking data processing hardware system, comprising:

a host server executing a social bookmarking system managing a plurality of social bookmarks and associated metadata;

an end user application executing separately from the social bookmarking system and providing content in a display; and

at least one processor, the at least one processor configured to

extract display content,

pass the display content to the social bookmarking system for parsing the display content into text,

compare the parsed text to social bookmarks and associated metadata in the social bookmarking system to determine whether the parsed text matches at least one of the social bookmarks in the social bookmarking system by matching portions of the parsed text to respective ones of the social bookmarks and associated metadata, and

direct a visual emphasis of the matched portions of the parsed text from the display content by determining a frequency of match to respective ones of the social bookmarks and associated metadata and adjusting a color of text associated with the matched portions of the parsed text proportionately based upon the determined frequency of match so as to visually differentiate the matched portions from the display content in the end user application.

10. The system of claim 9, wherein

the at least one processor is further configured to subclass a display event in the end user application.

11. The system of claim 9, wherein

the at least one processor configured by a helper application coupled to the end user application.

12. The system of claim 9, wherein

the at least one processor is configured by the end user application.

13. The system of claim 9, wherein

the at least one processor resides in the host server and has a hook into the end user application.

14. The system of claim 9, wherein the frequency of match is a number of occurrences that portions of the parsed text match respective ones of the social bookmarks and associated metadata.

15. A computer program product comprising a computer usable storage medium having stored therein computer usable program code for automatically surfacing tagged content in a vertical application, the computer program computer usable program code, which when executed by a computer hardware system, causes the computer hardware system to perform

parsing text from content in an end user application;

comparing the parsed text to social bookmarks and associated metadata in a social bookmarking system to determine whether the parsed text matches at least one of the social bookmarks in the social bookmarking system by matching portions of the parsed text to respective ones of the social bookmarks and associated metadata; and

,

upon determining that the parsed text matches the at least one of the social bookmarks in the social bookmarking system, visually emphasizing the matched portions of the parsed text from the content in the end user application by determining a frequency of match to respective ones of the social bookmarks and associated metadata and adjusting a color of text associated with the matched portions of the parsed text proportionately based upon the determined frequency of match so as to visually differentiate the matched portions from the content.

16. The computer program product of claim 15, wherein

comparing the parsed text to the social bookmarks comprises restricting the parsed text to a limited vocabulary during the comparing.

17. The computer program product of claim 15, wherein the computer hardware system is further caused to perform

toggling the visual emphasis of the matched portions of the parsed text in the end user application.

18. The computer program product of claim 15, wherein the computer hardware system is further caused to perform

appending a source indicator in the end user application indicating which one of the social bookmarks for the visually emphasized matched portions of the parsed text.

19. The computer program product of claim 15, wherein the frequency of match is a number of occurrences that portions of the parsed text match respective ones of the social bookmarks and associated metadata.

20. The computer program product of claim 15, wherein visually emphasizing the matched portions of the parsed text from the content in the end user application by visually differentiating the matched portions of the parsed text from the content further comprises adjusting a font size of text associated with the matched portions of the parsed text proportionately based upon the determined frequency of match to respective ones of the social bookmarks and associated metadata.