Methods for enhancing digital search query techniques based on task-oriented user activity

• US 8,706,748 B2
• Filed: 12/12/2007
• Issued: 04/22/2014
• Est. Priority Date: 12/12/2007
• Status: Active Grant

• Current Assignee: Emc IP Holding Company LLC (Dell Technologies Inc.)
• Original Assignee: DECHO Corporation (Open Text Corporation)
• Inventors: Herlocker, Jonathan L., Dietterich, Thomas G., Forbes, John B., Maritz, Paul
• Primary Examiner(s): Ly, Cheyne D
• Application Number:
  US12/001,987
• Publication Number:
  US 20090157617A1
• Time in Patent Office: 2,323 Days
• Field of Search: 707/759, 707/760, 707/765, 707/732, 707/705, 707/723, 707/736, 707/749
• US Class Current: 707/760
• CPC Class Codes: G06F 16/2452 Query translation
• CPC Class Codes: G06F 16/24542 Plan optimisation
• CPC Class Codes: G06F 16/3322 using system suggestions G06F16/3325 takes precedence
• CPC Class Codes: G06F 16/90324 using system suggestions

Abstract

Methods for using task-related information to enhance digital searching are provided. A task-oriented user activity system maintains task-related information about resources accessed by a user and current user task. This task-related information is used to enhance search queries to include task-related search criteria that improve relevance of search results. The task-related information can also be used to include task-related metadata in search engine index, e.g., by storing the metadata in the index or by storing it in resources which are subsequently indexed. Task-related information can also be used to enhance search results by filtering and ranking results to increase relevance with respect to a user'"'"'s current task.

Claims

1. A computer-implemented method for digital search, the method comprising:

generating, using a task-related query processor, a search query in an enhanced search query language that includes a task-related search term, the task-related search term being related to a current task being performed by a user;

predicting a predicted task based on the task-related search term and stored event records that correspond to an activity history of the user and that identify content of documents previously visited by the user, wherein the predicted task is a particular task, from among a plurality of tasks, that is predicted as the current task being performed by the user according to a probability determination and using the stored event records; and

translating the enhanced search query language into a traditional search engine language by supplementing the search query with additional search terms to generate a supplemented search query, wherein the additional search terms of the supplemented search query are different from the task-related search term and are generated according to task-related features that are representative of the predicted task, wherein the supplemented search query corresponds to the task-related search term and the additional search terms;

retrieving, from a search engine, search results matching the traditional search engine language corresponding to the supplemented search query; and

presenting the search results.

7. The method of claim 1, wherein the processing uses a lookup table to map the task-related features to search terms appropriate for a particular search engine.

8. The method of claim 1, wherein the task-related search term includes a task-related metadata criterion specifying the current task, and wherein the search engine is an enhanced search engine supporting task-oriented query language extensions.

9. The method of claim 8, wherein generating the search query includes mapping the task-related metadata criterion to query terms of the search engine using a lookup table.

2. A computer-implemented method for digital search with a task-enhanced search query, the method comprising:

generating, using a task-related query processor, a search query based on interaction with a user, wherein the search query is in an enhanced search query language that includes a task-related search term, wherein the task-related search term is related to a current task being performed by the user;

predicting a predicted task based on the task-related search term and stored event records that correspond to an activity history of the user and that identify content of documents previously visited by the user, wherein the predicted task is a particular task, from among a plurality of tasks, that is predicted as the current task being performed by the user according to a probability determination and using the stored event records; and

translating the enhanced search query language into a traditional search engine language by supplementing the search query with additional search terms to generate a supplemented search query, wherein the additional search terms of the supplemented search query are different from the task-related search term and are generated according to task-related features that are representative of the predicted task, wherein the supplemented search query corresponds to the task-related search term and the additional search terms;

retrieving, from a search engine, search results matching the traditional search engine language corresponding to the supplemented search query; and

presenting the search results to the user.

3. The method of claim 2, wherein generating the search query further includes submitting the predicted current task to a task-oriented activity system to obtain the additional search terms that represent task-related features related to the predicted current task, and processing the search query to include the additional search terms and generate the supplemented search query.

4. The method of claim 3, wherein the processing uses a lookup table to map the features to search terms that are appropriate for a particular search engine.

5. The method of claim 2, wherein the task-related search term includes a task-related metadata criterion specifying the current task, and wherein the search engine is an enhanced search engine supporting task-oriented query language extensions.

6. The method of claim 5, wherein generating the search query comprises mapping the task-related metadata criterion to query terms of the search engine using a lookup table.

10. A system for performing a digital search, comprising:

a task-related query processor that;

generates a search query in an enhanced search query language that includes a task-related search term, the task-related search term being related to a current task being performed by the user;

predicts a predicted task based on the task-related search term and stored event records that correspond to an activity history of the user and that identify content of documents previously visited by the user, wherein the predicted task is a particular task, from among a plurality of tasks, that is predicted as the current task being performed by the user according to a probability determination and using the stored event records; and

translates the enhanced search query language into a traditional search engine language by supplementing the search query with additional search terms to generate a supplemented search query, wherein the additional search terms of the supplemented search query are different from the task-related search term and are generated according to task-related features that are representative of the predicted task, wherein the supplemented search query corresponds to the task-related search term and the additional search terms;

a search engine that retrieves search results matching the traditional search engine language corresponding to the supplemented search query; and

display components that present the search results.

11. The system of claim 10, wherein the task-related query processor generates the search query based on interaction with the user.

12. The system of claim 11, wherein the task-related query processor obtains the additional search terms representing features related to the predicted current task from a task-oriented activity system and processes the search query to generate the supplemented search query that includes the additional search terms.

13. The system of claim 10, wherein the task-related query processor uses a lookup table to map the task-related features to search terms appropriate for a particular search engine.

14. The system of claim 10, wherein the task-related search term includes, a task-related metadata criterion specifying the current task, and wherein the search engine is an enhanced search engine supporting task-oriented query language extensions.

15. A system for performing a digital search, comprising:

a task-related query processor that;

generates a search query, wherein the search query is in an enhanced search query language that includes a task-related search term, the task-related search term being related to a current task being performed by the user;

predicts a predicted task based on the task-related search term and stored event records that correspond to an activity history of the user and that identify content of documents previously visited by the user, wherein the predicted task is a particular task, from among a plurality of tasks, that is predicted as the current task being performed by the user according to a probability determination and using the stored event records; and

translates the enhanced search query language into a traditional search engine language by supplementing the search query with additional search terms to generate a supplemented search query, wherein the additional search terms of the supplemented search query are different from the task-related search term and are generated according to the task-related features generated according to task-related features that are representative of the predicted task, wherein the supplemented search query corresponds to the task-related search term and the additional search terms;

a processor for retrieving, from a search engine, search results matching the traditional search engine language corresponding to the supplemented search query; and

a processor for presenting the search results.

16. The system of claim 15, wherein the task-related query processor uses a lookup table to map the task-related features to search terms appropriate for a particular search engine.

17. The system of claim 15, wherein the task-related query processor obtain the additional search terms representing features related to the predicted current task from a task-oriented activity system and processes the search query to generate the supplemented search query that includes the additional search terms.

18. The system of claim 17, wherein the task-related query processor uses a lookup table to map the task-related features to search terms appropriate for a particular search engine.

19. The system of claim 15, wherein the task-related search term includes a task-related metadata criterion specifying the current task, and wherein the search engine is an enhanced search engine supporting task-oriented query language extensions.

20. The system of claim 19, wherein the task-related query processor maps the task-related metadata criterion to query terms of the search engine using a lookup table.