People search using proximity

• US 9,870,391 B1
• Filed: 07/30/2010
• Issued: 01/16/2018
• Est. Priority Date: 07/30/2010
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Strand, William Alexander, Lane, III, Jerry C.
• Primary Examiner(s): Dwivedi, Mahesh
• Application Number:
  US12/847,282
• Time in Patent Office: 2,727 Days
• Field of Search: 707722
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

Disclosed are various embodiments for providing a people search that uses proximity in ranking results. A search query for a person is obtained from a user. The search query is executed on a directory comprising profiles that each correspond to a respective person. Resulting profiles that match the search query are thereby obtained. The resulting profiles are ordered based at least in part on a measure of proximity of each respective person to the user.

Claims

1. A non-transitory computer-readable medium embodying a program executable in a computing device, wherein when executed the program causes the computing device to at least:

obtain a search string from a client;

obtain a user profile associated with the client from a directory of person profiles;

execute a name search in the directory using the search string, thereby obtaining a plurality of person profiles from the directory that at least approximately match the search string based at least in part on respective names associated with individual ones of the plurality of person profiles;

generate a corresponding proximity score for the individual ones of the plurality of person profiles based at least in part on comparing location information for the user profile with respective location information and department data for the individual ones of the plurality of person profiles, a weight of the department data being greater than a weight of the location information for the corresponding proximity score; and

generate a plurality of search results for the name search, individual ones of the plurality of search results corresponding to individual ones of the plurality of person profiles, the plurality of search results being ordered based at least in part on a name match quality of the respective names to the search string and the corresponding proximity score for the individual ones of the plurality of person profiles to the user profile.

2. The non-transitory computer-readable medium of claim 1, wherein the name match quality is based at least in part on a phonetic algorithm.

3. The non-transitory computer-readable medium of claim 1, wherein the user profile is identified by at least one security credential for authentication.

4. A system, comprising:

at least one computing device; and

a people search application executable in the at least one computing device, wherein when executed the people search application causes the at least one computing device to at least;

obtain a search string from a client device;

identify a user profile of a user;

execute a name search for the search string on a directory, thereby obtaining a plurality of resulting profiles, individual ones of the plurality of resulting profiles comprising a name that matches the search string;

determine a name match quality for individual ones of the plurality of resulting profiles based at least in part on the search string;

determine a profile proximity for individual ones of the plurality of resulting profiles to the user profile based at least in part on a comparison of department data and location data for the user profile with department data and location data for the individual ones of the plurality of resulting profiles, a weight of department data being considered greater than a weight of the location data for the profile proximity; and

generate a plurality of search results for the name search, individual ones of the plurality of search results being ordered using the name match quality based at least in part on the search string and the profile proximity for the individual ones of the plurality of resulting profiles to the user profile.

5. The system of claim 4, wherein when executed the people search application further causes the at least one computing device to at least obtain the user profile according to an at least one security credential.

6. The system of claim 5, wherein the plurality of resulting profiles are further ranked based at least in part on a corresponding similarity score associated with each one of the plurality of resulting profiles, the corresponding similarity score being derived from a comparison of the user profile and a respective one of the plurality of resulting profiles.

7. The system of claim 6, wherein the comparison involves comparing a plurality of data fields of the user profile with a corresponding plurality of data fields in a respective one of the resulting profiles to produce a plurality of intermediate scores, applying a respective weight to each of the intermediate scores to produce a plurality of weighted intermediate scores, and summing the weighted intermediate scores to produce the corresponding similarity score.

8. The system of claim 4, wherein executing the search includes executing the search on other data, thereby obtaining a plurality of other results that match the search string.

9. The system of claim 4, wherein the directory corresponds to a staff directory of an organization.

10. The system of claim 4, wherein when executed the people search application further causes the at least one computing device to at least determine the profile proximity by comparing a current physical location of the user to respective location information.

11. The system of claim 10, wherein the current physical location is a corresponding designated work location.

12. The system of claim 10, wherein the current physical location of the user is determined by a Global Positioning System (GPS) device associated with the user.

13. A method, comprising:

obtaining, in at least one computing device, a search string and an identification of a user;

determining, in the at least one computing device, a plurality of profiles in a person profile directory that match the search string;

determining, in the at least one computing device, a name match quality score and a proximity score for each of the plurality of profiles, each name match quality score indicating a measure of quality of a match between the search string and a respective name field included in a respective profile, each proximity score indicating a measure of proximity between a user profile associated with the user and the respective profile based at least in part on a location, a department, and a team identified for each of the user and the respective profile, a weight of the department being greater than a weight of the location for the proximity score; and

generating, in the at least one computing device, a listing of the plurality of profiles that is ordered based at least in part on corresponding name match quality scores of the respective name field to the search string and corresponding proximity scores of the respective profile to the user profile.

14. The method of claim 13, wherein the proximity score is determined based at least in part on a distance between a current location associated with the user and a geographic location associated with the respective profile based at least in part on a building and a floor of the building identified for the respective profile.

15. The method of claim 13, wherein the proximity score is determined based at least in part on a comparison between a data field of the user profile associated with the user and a corresponding data field of the respective profile.

16. The method of claim 13, wherein the proximity score is determined based at least in part on a comparison between an organizational department of the user profile and an organizational department listed in the respective profile.

17. The method of claim 13, wherein the match between the search string and the respective name field is identified when the respective name field of the respective profile includes at least one term of the search string.

18. The method of claim 13, wherein the match between the search string and the respective name field is identified when a similarity scoring component applied to at least one term of the search string and the respective name field of the respective profile produces a similarity score that meets a threshold.

19. The method of claim 18, wherein the similarity scoring component employs a phonetic algorithm to produce the similarity score.

20. The method of claim 13, wherein the proximity score is determined based at least in part on a comparison between an academic major of the user and an academic major listed in the respective profile.

21. The method of claim 13, wherein the proximity score is determined based at least in part on a comparison between access privileges of the user and access privileges indicated in the respective profile.