SEARCH METHOD AND SYSTEM

• US 20110145234A1
• Filed: 02/24/2011
• Published: 06/16/2011
• Est. Priority Date: 08/26/2008
• Status: Abandoned Application

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Inventors: HU, Hanqiang
• Application Number:
  US13/034,071
• Publication Number:
  US 20110145234A1
• Time in Patent Office: Days
• US Class Current: 707/728
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

A search method provides a search client user with personalized search that may provide related search results according to the interest model of the search client user. The search method includes: receiving a search request from a search client, where the search request includes one or more search key words; extracting an interest model of a user according to the personalized data of the user; distributing the one or more search key words and the interest model to one or more member search devices; receiving search results and corresponding ranking scores of the search results from the one or more member search devices, where the ranking scores are calculated according to the interest model; and sorting the search results according to the ranking scores, obtaining final search results, and returning the final search results to the search client. A search system is also provided. With the present invention, the search results are more personalized, and the search service may be promoted more conveniently.

Claims

1. A search method, comprising:

receiving a search request;

carrying an interest model of a user in the search request, and distributing the search request to a search device; and

receiving personalized search results that are obtained according to the interest model from the search device, and returning the personalized search results.

2. The search method of claim 1, wherein the search request comprises search key words input in text mode and/or search key words recognized in speech mode.

3. The search method of claim 1, further comprising:

receiving an interest model of the user extracted according to personalized data of the user or a pre-extracted interest model of the user from an application server.

4. The search method of claim 1, wherein the step of carrying the interest model of the user in the search request and distributing the search request to the search device further comprises:

specifying a unified algorithm for personalization of the search results.

5. The search method of claim 4, further comprising:

receiving personalized ranking scores of the search results that are calculated according to the unified algorithm from the search device.

6. The search method of claim 5, further comprising:

receiving search results that are sorted according to the personalized ranking scores from the search device.

7. The search method of claim 1, further comprising:

re-ranking the search results according to the personalized relevance scores and/or related factors, and sorting the search results according to the re-ranking scores.

8. The search method of claim 7, wherein the related factors comprise the level information of member search devices or a member search server and/or price ranking information.

9. The search method of claim 8, wherein the step of re-ranking the search results according to the level information of the member search devices or the member search server comprises:

calculating level ranking information by using the following formula;

P=r1×

returned ranking scores+r2×

level factor

wherein P refers to a level ranking score, r1 refers to the weight of a returned ranking score, r2 refers to the weight of a level factor, the returned ranking scores refer to the ranking scores returned by the member search devices, and the level factors refer to levels of the member search devices.

10. The search method of claim 9, wherein the step of re-ranking the search results according to the level information of the member search devices or the member search server comprises:

calculating overall ranking information by using the following formula;

R=P+r3×

price factor ranking score

wherein R refers to an overall ranking score, r3 refers to the ranking weight of a price factor, and r1+r2+r3=1.

11. The search method of claim 1, further comprising:

receiving personalized relevance ranking scores of the search results that are calculated according to a private algorithm from the search device.

12. The search method of claim 11, further comprising:

receiving search results that are sorted according to the personalized relevance ranking scores from the search device.

13. A search method, comprising:

receiving a search request from a search client;

extracting an interest model of a user according to personalized data of the user or taking out a pre-stored interest model of the user;

carrying the interest model of the user in the search request, and sending the search request to a search server;

receiving personalized search results obtained according to the interest model of the user from the search server; and

returning the personalized search results to the search client.

14. The search method of claim 13, wherein the interest model is an interest model vector composed of N-dimensional ranking scores of the user, wherein N≧

2.

15. The search method of claim 13, wherein the interest model vector is a sum of vectors of one or more static interest models and vectors of one or more dynamic interest models or a weighted sum of vectors of one or more static interest models and vectors of one or more dynamic interest models.

16. The search method of claim 15, wherein the vectors of the one or more static interest models, the vectors of the one or more dynamic interest models or the interest model vector may be represented as follows:

W1=(p1, p2, . . . , pi, . . . , pn), wherein W1 refers to a vector, pi refers to a sum of word frequencies of an i^th interest dimension, and n is greater than or equal to 2.

17. The search method of claim 16, wherein the pi value may vary with history search time or vary according to user evaluation.

18. The search method of claim 13, wherein the interest model comprises the personalized data of the user, wherein the personalized data of the user comprises one or more of the following:

static user profile, search history, position information and presence information.

19. A search device, comprising:

a tool adapted to receive a search request;

a tool adapted to carry an interest model of a user in the search request, and distribute the search request to a search device;

a tool adapted to receive personalized search results obtained according to the interest model from the search device; and

a tool adapted to return the personalized search results.