IP Library Granted Patent US 9,384,244
Granted Patent B1
US 9,384,244 · App. 14/092,567 · Granted Jul 5, 2016

Search with autosuggest and refinements

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Quick Facts
Patent No.
US 9,384,244
App. No.
14/092,567
Granted
Jul 5, 2016
Kind
B1
Abstract

Techniques for search with autosuggest and refinements are disclosed. In some embodiments, search with autosuggest includes determining a plurality of potential query suggestions for a partially entered query string; and automatically suggesting a plurality of queries based on a query count for each of the queries. For example, the query count can correspond to a popularity of the query. In some implementations, the query count can be determined based on a number of times that the query was received, and the plurality of queries can be listed based on the popularity of each of the plurality of queries (e.g., to facilitate display of more popular queries higher in the list of suggested queries).

Claims (62)

1. A system for search with autosuggest, comprising:

a processor configured to:

determine a plurality of potential query suggestions for a partially entered query string;

automatically suggest a plurality of queries based on a query count for each of the queries, comprising to:

determine a weight for each of the plurality of potential search query suggestions, comprising to:

determine a first weight of a first potential search query suggestion based on a first query count;

determine a first position weight based on a position of a first matching word in the first potential search query suggestion;

adjust the first weight of the first potential search query suggestion based on the first position weight to obtain a first adjusted weight for the first potential search query suggestion, comprising to:

 determine whether a portion of the query string matches a field in a document associated with the first potential search query suggestion; and

 in the event that the portion of the query string matches the field in the document:

 adjust the first adjusted weight by a first value in the event that the field corresponds to a first type; and

 adjust the first adjusted weight by a second value in the event that the field corresponds to a second type, the first value being different from the second value; and

a memory coupled to the processor and configured to provide the processor with instructions.

2. The system recited in claim 1 , wherein the query count corresponds to a popularity of the query.

3. The system recited in claim 1 , wherein the query count corresponds to a popularity of the query, and wherein the query count is determined based on a number of times that the query was received.

4. The system recited in claim 1 , wherein the query count corresponds to a popularity of the query, and wherein the plurality of queries are listed based on a popularity of each of the plurality of queries.

5. The system recited in claim 1 , wherein the processor is further configured to:

dynamically optimize search results for a merchant web site based on user demand for automatically suggesting the plurality of queries.

6. The system recited in claim 1 , wherein the processor is further configured to:

determine that the partially entered query string is associated with product or category of a merchant web site.

7. The system recited in claim 1 , wherein the processor is further configured to:

merge a plurality of categories associated with a merchant web site.

8. The system recited in claim 1 , wherein the processor is further configured to:

merge a plurality of categories associated with a merchant web site, wherein at least one of the automatically suggested plurality of queries corresponds to a merged category.

9. The system recited in claim 1 , wherein the processor is further configured to:

determine a number of automatically suggested plurality of queries to return based on a device platform.

10. The system recited in claim 1 , wherein a match starting at a position at a beginning of the potential search query suggestion is weighted higher than a match starting at a position other than a beginning of the potential search query suggestion.

11. The system recited in claim 1 , wherein the processor is further configured to:

merge more than one potential search query suggestions into a single suggested search query, the more than one potential search query suggestions being selected based on their associated weights.

12. The system recited in claim 1 , wherein the field includes title of the document, description of the document, color of a product item, name of a product, product brand, keywords, or any combination thereof.

13. A method of search with autosuggest, comprising:

determining a plurality of potential query suggestions for a partially entered query string; and

automatically suggesting a plurality of queries based on a query count for each of the queries, comprising:

determining a weight for each of the plurality of potential search query suggestions, comprising:

determining a first weight of a first potential search query suggestion based on a first query count;

determining a first position weight based on a position of a first matching word in the first potential search query suggestion;

adjusting the first weight of the first potential search query suggestion based on the first position weight to obtain a first adjusted weight for the first potential search query suggestion, comprising:

determining whether a portion of the query string matches a field in a document associated with the first potential search query suggestion; and

in the event that the portion of the query string matches the field in the document:

 adjusting the first adjusted weight by a first value in the event that the field corresponds to a first type; and

 adjusting the first adjusted weight by a second value in the event that the field corresponds to a second type, the first value being different from the second value.

14. The method of claim 13 , wherein the query count corresponds to a popularity of the query.

15. The method of claim 13 , wherein the query count corresponds to a popularity of the query, and wherein the query count is determined based on a number of times that the query was received.

16. The method of claim 13 , wherein the query count corresponds to a popularity of the query, and wherein the plurality of queries are listed based on a popularity of each of the plurality of queries.

17. The method of claim 13 , further comprising:

determining a number of automatically suggested plurality of queries to return based on a device platform.

18. A computer program product for search with autosuggest, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for:

determining a plurality of potential query suggestions for a partially entered query string; and

automatically suggesting a plurality of queries based on a query count for each of the queries, comprising:

determining a weight for each of the plurality of potential search query suggestions, comprising:

determining a first weight of a first potential search query suggestion based on a first query count;

determining a first position weight based on a position of a first matching word in the first potential search query suggestion;

adjusting the first weight of the first potential search query suggestion based on the first position weight to obtain a first adjusted weight for the first potential search query suggestion, comprising:

determining whether a portion of the query string matches a field in a document associated with the first potential search query suggestion; and

in the event that the portion of the query string matches the field in the document:

 adjusting the first adjusted weight by a first value in the event that the field corresponds to a first type; and

 adjusting the first adjusted weight by a second value in the event that the field corresponds to a second type, the first value being different from the second value.

19. The computer program product recited in claim 18 , wherein the query count corresponds to a popularity of the query.

20. The computer program product recited in claim 18 , wherein the query count corresponds to a popularity of the query, and wherein the query count is determined based on a number of times that the query was received.

21. The computer program product recited in claim 18 , wherein the query count corresponds to a popularity of the query, and wherein the plurality of queries are listed based on a popularity of each of the plurality of queries.

22. The computer program product recited in claim 18 , further comprising computer instructions for:

determining a number of automatically suggested plurality of queries to return based on a device platform.

Assignments (6)
SECURITY INTEREST Recorded Sep 6, 2022
From: BLOOMREACH, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 060997/0569 →
RELEASE OF SECURITY INTEREST Recorded Aug 1, 2022
From: COMERICA BANK
To: BLOOMREACH, INC.
Reel/Frame 060689/0715 →
RELEASE OF SECURITY INTEREST Recorded Mar 7, 2022
From: ORIX GROWTH CAPITAL, LLC
To: BLOOMREACH, INC.
Reel/Frame 059189/0696 →
SECURITY INTEREST Recorded Jan 17, 2020
From: BLOOMREACH, INC.
To: ORIX GROWTH CAPITAL, LLC
Reel/Frame 051546/0192 →
SECURITY INTEREST Recorded Jan 16, 2020
From: BLOOMREACH, INC.
To: COMERICA BANK
Reel/Frame 051540/0285 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 10, 2014
From: GARG, ASHUTOSH; RAGHURAMAN, ANAND; RAVINDRANATH, VINODH KUMAR; JAIN, MOHIT; AUGUSTINE, CHRISTINA; BHATI, GAURAV
To: BLOOMREACH INC.
Reel/Frame 032188/0057 →