Selecting high quality text within identified reviews for display in review snippets

• US 8,010,480 B2
• Filed: 09/30/2005
• Issued: 08/30/2011
• Est. Priority Date: 09/30/2005
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Dave, Kushal B., Hylton, Jeremy A.
• Primary Examiner(s): Fernandez Rivas; Omar F
• Application Number:
  US11/241,702
• Publication Number:
  US 20070078671A1
• Time in Patent Office: 2,160 Days
• Field of Search: 706/11, 706/45, 706/46, 706/50, 706/60, 706/62, 707/1, 707/7, 707/100, 705/1, 705/10, 705/500
• US Class Current: 706/62
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products

Abstract

A method and system of selecting content from reviews for display are described. A review is identified and partitioned. A subset of the partitions is selected based on predefined criteria. A snippet is generated from the selected partitions. A response that includes the snippet is generated.

Claims

1. A computer implemented method of generating a review sample of a single review in a corpus of reviews, comprising:

at a server having one or more processors and memory storing one or more programs for execution by the one or more processors;

identifying the single review;

partitioning the review into partitions;

selecting a plurality of the partitions of the single review based on predefined criteria, wherein selecting the plurality of the partitions comprises;

identifying two or more combinations of the partitions, determining a quality score for each respective combination, and selecting the respective combination having a highest quality score;

generating a snippet solely for the single review including content from each of the selected plurality of the partitions, wherein the review sample of the single review comprises the generated snippet; and

generating a response including the snippet for the single review.

2. The method of claim 1, wherein selecting comprises:

determining a quality score for each of the partitions; and

selecting a plurality of the partitions of the single review based on the quality scores.

3. The method of claim 2, wherein determining comprises determining a quality score for each of the partitions based on a length of the respective partition and at least one of the group consisting of:

inverse document frequency values associated with one or more words in the respective partition, and a position of the respective partition within the review.

4. The method of claim 1, wherein selecting comprises:

determining a quality score for each of the partitions; and

selecting a plurality of the partitions based on a combined quality score that is based on the quality scores.

5. The method of claim 1, including limiting a length of the selected plurality of the partitions so that the length of the selected plurality of the partitions exceeds a predefined maximum snippet length by less than a full sentence.

6. A computer implemented method of processing reviews, comprising:

at a server having one or more processors and memory storing one or more programs for execution by the one or more processors;

identifying a single review;

partitioning the review into one or more partitions;

selecting a plurality of the partitions based on predefined criteria;

generating a snippet solely for the single review including content from the selected plurality of the partitions; and

generating a response including the snippet for the single review,

wherein selecting a plurality of the partitions comprises identifying one or more combinations of the partitions, each combination including a respective subset of the partitions that are consecutive within the review and satisfying predefined length criteria.

7. The method of claim 6, wherein selecting a plurality of the partitions comprises:

determining a quality score for each partition in a respective combination; and

selecting the respective combination having a highest respective combination score, the respective combination score based on respective quality scores of the partitions in the respective combination.

8. A system for generating a review sample of a single review in a corpus of reviews, comprising:

one or more processors; and

memory storing one or more programs to be executed by the one or more processors, the one or more modules including instructions;

to identify the single review;

to partition the review into partitions;

to select a plurality of the partitions of the single review based on predefined criteria;

to generate a snippet solely for the single review including content from each of the selected plurality of the partitions, wherein the review sample of the single review comprises the generated snippet; and

to generate a response including the snippet for the single review,

wherein the instructions to select the plurality of the partitions include instructions to;

identify two or more combinations of the partitions, determine a quality score for each respective combination, and select the respective combination having a highest quality score.

9. The system of claim 8, wherein the one more modules include instructions:

to determine a quality score for each of the partitions; and

to select a plurality of the partitions of the single review based on the quality scores.

10. The system of claim 9, wherein the one or more modules include instructions to determine a quality score for each of the partitions based on a length of the respective partition and at least one of the group consisting of:

inverse document frequency values associated with one or more words in the respective partition, and a position of the respective partition within the review.

11. The system of claim 8, wherein the one more modules include instructions:

to determine a quality score for each of the partitions;

to select a plurality of the partitions based on a combined quality score that is based on the quality scores.

12. A system for processing reviews, comprising:

one or more processors; and

memory storing one or more programs to be executed by the one or more processors, the one or more modules including instructions;

to identify a single review;

to partition the review into one or more partitions;

to select a plurality of the partitions based on predefined criteria;

to generate a snippet solely for the single review including content from the selected plurality of the partitions; and

to generate a response including the snippet for the single review,

wherein the one or more modules include instructions to identify one or more combinations of the partitions, each combination including a respective plurality of the partitions that are consecutive within the review and satisfying predefined length criteria.

13. The system of claim 12, wherein the one or more modules include instructions:

to determine a quality score for each partition in a respective combination; and

to select the respective combination having a highest respective combination score, the respective combination score based on respective quality scores of the partitions in the respective combination.

19. The computer readable storage medium of claim 12, wherein the instructions for selecting a plurality of the partitions based on the quality scores comprise instructions for:

determining a quality score for each partition in a respective combination; and

selecting the respective combination having a highest respective combination score, the respective combination score based on respective quality scores of the partitions in the respective combination.

14. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors at a server computer, the one or more programs comprising instructions for:

identifying a single review;

partitioning the review into partitions;

selecting a plurality of the partitions of the single review based on predefined criteria, wherein selecting the plurality of the partitions comprises;

identifying two or more combinations of the partitions, determining a quality score for each respective combination, and selecting the respective combination having a highest quality score;

generating a snippet solely for the single review including content from each of the selected plurality of the partitions; and

generating a response including the snippet for the single review.

15. The computer readable storage medium of claim 14, wherein the instructions for selecting comprise instructions for:

determining a quality score for each of the partitions; and

selecting a plurality of the partitions of the single review based on the quality scores.

16. The computer readable storage medium of claim 15, wherein the instructions for determining comprise instructions for determining a quality score for each of the partitions based on a length of the respective partition and at least one of the group consisting of:

inverse document frequency values associated with one or more words in the respective partition, and a position of the respective partition within the review.

17. The computer readable storage medium of claim 14, wherein instructions for selecting comprise:

instructions for determining a quality score for each of the partitions; and

instructions for selecting a plurality of the partitions based on a combined quality score that is based on the quality scores.

18. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors at a server computer, the one or more programs comprising instructions for:

identifying a single review;

partitioning the review into one or more partitions;

selecting a plurality of the partitions based on predefined criteria;

generating a snippet solely for the single review including content from each of the selected plurality of the partitions; and

generating a response including the snippet for the single review,

wherein the instructions for selecting a plurality of the partitions comprise identifying one or more combinations of the partitions, each combination including a respective subset of the partitions that are consecutive within the review and satisfying predefined length criteria.