System and method for searching and recommending objects from a categorically organized information repository

• US 7,031,961 B2
• Filed: 12/04/2000
• Issued: 04/18/2006
• Est. Priority Date: 05/05/1999
• Status: Expired due to Term

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Schuetze, Hinrich, Pitkow, James B.
• Primary Examiner(s): RIMELL, SAMUEL G
• Application Number:
  US09/730,501
• Publication Number:
  US 20020016786A1
• Time in Patent Office: 1,961 Days
• Field of Search: 707/3, 707/4, 707/5, 707/10, 707/100
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9562 Bookmark management
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation

Abstract

A search and recommendation system employs the preferences and profiles of individual users and groups within a community of users, as well as information derived from categorically organized content pointers, to augment Internet searches, re-rank search results, and provide recommendations for objects based on an initial subject-matter query. The search and recommendation system operates in the context of a content pointer manager, which stores individual users'"'"' content pointers (some of which may be published or shared for group use) on a centralized content pointer database connected to the Internet. The shared content pointer manager is implemented as a distributed program, portions of which operate on users'"'"' terminals and other portions of which operate on the centralized content pointer database. A user'"'"'s content pointers are organized in accordance with a local topical categorical hierarchy. The hierarchical organization is used to define a relevance context within which returned objects are evaluated and ordered.

Claims

1. A method for searching an information repository, the repository characterized as a hierarchical object space, the method comprising the steps of:

establishing a collection of shared content pointers, each shared content pointer corresponding to an object;

receiving at least one query keyword;

searching at least a portion of the collection of shared content pointers in accordance with the keyword query;

deriving at least one additional keyword from the collection, the additional keyword associated with the query keyword;

augmenting the query with at the least one additional keyword derived from the collection;

searching the information repository in accordance with the augmented query;

retrieving a group of objects that match the augmented query;

identifying a context within the group of objects;

ordering the group of retrieved objects based a computed match with the context; and

ordering the group of retrieved content pointers in a ranking order, the order determined by a weighted set of user metrics, wherein the set of user metrics are chosen from a group consisting of a popularity metric, a frequency of access metric, a recency of access metric, and a link structure metric.

2. The method of claim 1, wherein the context comprises a profile for a group of users chosen from a plurality of users.

3. The method of claim 1, wherein the context comprises a profile for a single user chosen from a plurality of users.

4. The method of claim 3, wherein the profile comprises a content vector derived from at least one object represented by at least one content pointer in at least one selected topical category of objects contributed by the single user.

5. The method of claim 2, wherein the profile comprises a content vector derived from at least one object represented by at least one content pointer in at least one selected topical category of objects contributed by the group.

6. The method of claim 1, wherein the context comprises a profile for the plurality of users, said profile comprising a content vector derived from at least one document represented by at least one content pointer in at least one selected topical category of content pointers contributed by the plurality of users.

7. The method of claim 1, wherein the context comprises a hierarchical relevance model.

8. The method of claim 1, wherein the searching step is performed by a search engine and wherein the ordering step is performed by a separate recommendation engine.

9. A method for searching an information repository, the information repository characterized as a topical hierarchical object space, the method comprising the steps of:

establishing a collection of shared content pointers, the shared content pointers corresponding to objects contained within the information repository, each contributed by at least one user of a plurality of users, the collection organized in accordance with a topical categorical hierarchy;

searching at least a portion of the collection of shared content pointers in accordance with a keyword query;

augmenting the query with at least one additional keyword derived from the collection;

searching the information repository in accordance with the first keyword and the additional keyword;

retrieving at least one of a group of objects, each including content indicia, at least one content index matching the query keyword;

identifying a context within the collection of content pointers;

identifying a set of user metrics, the set of user metrics chosen from a group consisting of a popularity metric, a frequency of access metric, a recency of access metric, a link structure metric and a topical categorical organizational metric;

combining a computed match with the context, and at least one of the set of user metrics, for each content pointer in to a composite measure; and

ranking the group of retrieved objects based on the composite measure.

10. The method of claim 9, wherein the context comprises a profile, the profile selected from a group consisting of a user profile for a single user chosen from the plurality of users, a group profile for a group of users chosen from the plurality of users, and a profile for the plurality of users.

11. The method of claim 10, wherein the profile is derived from at least one object represented by at least one content pointer in at least one selected topical category of content pointers contributed by at least one user.

12. The method of claim 9 wherein the collection of content pointers is established by at least one user and wherein the context is derived from the topical categorical organization of the collection.

13. The method of claim 12, wherein the collection of content pointers is established by a group of users and wherein the context is derived from the topical categorical organization of the collection.

14. The method of claim 12, wherein the context is passed to a search engine as a content vector, the search engine retrieving at least one of a group of objects whose content index matches the context.

15. The method of claim 14, further comprising the step of ordering the retrieved objects in a ranking order, the order determined by a degree of matching between each object'"'"'s content index and the context.

16. The method of claim 15, wherein the searching step is performed by a search engine and wherein the ordering step is performed by a separate recommendation engine.

17. The method of claim 9, further comprising the steps of:

identifying a group of users comprising at least one user selected from the plurality of users; and

wherein, the set of user metrics are identified with respect to the group of users.

18. A method for generating ordered recommendations of content sources from an information repository comprising the steps of:

establishing a collection of content pointers, the content pointers corresponding to objects contained within the information repository, each contributed by at least one user of a plurality of users, the collection organized in accordance with a topical categorical hierarchy;

receiving at least one query keyword;

searching the information repository;

retrieving a group of objects that each includes a content profile matching the query keyword;

identifying a context within the collection;

ranking the group of content sources based on a computed match between each object'"'"'s content profile and the identified context;

wherein the ranking step further comprises the step of ordering the group of retrieved content sources in accordance with at set of user recommendation priority metrics; and

wherein the user recommendation priority metrics are chosen from a group consisting of a popularity metric, a frequency of access metric, a recency of access metric, and a link structure metric.

19. The method of claim 18, wherein the context is derived from the topical categorical organization of the collection.

20. The method of claim 18, wherein the context comprises a profile, the profile selected from a group consisting of a user profile for a single user chosen from the plurality of users, and a profile for the plurality of users.

21. The method of claim 19, wherein the context comprises a profile, the profile derived from at least one object represented by at least one content pointer in at least one selected topical category of content pointers contributed by at least one user.

22. The method of claim 18, further comprising the steps of:

identifying at least one associate keyword from within the collection;

augmenting the query with at least one associate keyword derived from the collection;

searching the information repository; and

retrieving at least one of a group of objects, each including a content profile matching the augmented query keyword.

23. The method of claim 22, wherein the augmented query keyword is derived from the collection context.