EVALUATING QUERY TRANSLATIONS FOR CROSS-LANGUAGE QUERY SUGGESTION

• US 20120330990A1
• Filed: 09/29/2011
• Published: 12/27/2012
• Est. Priority Date: 06/24/2011
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Chen, Qiliang, Tan, Weihua
• Application Number:
  US13/248,775
• Publication Number:
  US 20120330990A1
• Time in Patent Office: Days
• US Class Current: 707/761
• CPC Class Codes: G06F 16/3322 using system suggestions G06F16/3325 takes precedence
• CPC Class Codes: G06F 16/3337 Translation of the query language, e.g. Chinese to English
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30

Abstract

Computer-implemented methods, systems, computer program products for generating cross-language query suggestions are described. For each query suggestion written in a first natural language, candidate segmentations are generated from the query suggestion, and candidate translations are generated from each candidate segmentation. The candidate translations are evaluated based on a measure of segmentation quality associated with the respective candidate segmentation from which each candidate translation is derived, and a frequency of occurrence of the candidate translation in a target language query log. The measure of segmentation quality associated with each candidate segmentation is further based on a frequency of occurrence of the candidate segmentation in a source language query log. A candidate translation is provided as a cross-language query suggestion for the primary language query suggestion based on the result of the evaluation.

Claims

1. A computer-implemented method, comprising:

receiving a query written in a first language, the query being a primary-language query suggestion generated based on a user input submitted to a search engine;

obtaining one or more unique candidate segmentations of the query in the first language, each unique candidate segmentation consisting of a respective sequence of segments resulted from segmenting the query in the first language;

for each of the one or more unique candidate segmentations, determining a respective set of one or more candidate translations in a second language by translating the respective sequence of segments of the candidate segmentation;

for each candidate translation of each of the one or more unique candidate segmentations;

determining a respective segmentation quality for the unique candidate segmentation based at least in part on how many stop words have been removed from the respective sequence of segments of the unique candidate segmentation and a respective first frequency of occurrence of the unique candidate segmentation in a first query log as a complete query written in the first language; and

determining a respective score for the candidate translation based at least on the respective segmentation quality determined for the unique candidate segmentation and a respective second frequency of occurrence of the candidate translation in a second query log as a complete query written in the second language; and

providing at least one of the candidate translations as a cross-language query suggestion for the query based on respective scores of the candidate translations.

2. A computer-implemented method, comprising:

receiving a query written in a first language;

obtaining one or more unique candidate segmentations of the query in the first language, each unique candidate segmentation consisting of a respective sequence of segments resulted from segmenting the query in the first language;

for each of the one or more unique candidate segmentations;

determining a respective measure of segmentation quality for the unique candidate segmentation; and

obtaining a respective set of one or more candidate translations in a second language by translating the respective sequence of segments of the candidate segmentation;

for each candidate translation of each of the one or more unique candidate segmentations;

determining a first frequency of occurrence of the candidate translation in a first query log as a complete query written in the second language; and

determining a respective score for the candidate translation based at least on the first frequency of occurrence of the candidate translation in the first query log as a complete query written in the second language, and the measure of segmentation quality for the candidate segmentation; and

providing at least one of the candidate translations as a cross-language query suggestion for the query based on respective scores of the candidate translations.

3. The computer-implemented method of claim 2, wherein obtaining the one or more unique candidate segmentations of the query in the first language further comprises:

obtaining at least one candidate segmentation that is a partition of the query in the first language.

4. The computer-implemented method of claim 2, wherein obtaining the one or more unique candidate segmentations of the query in the first language further comprises:

obtaining at least one candidate segmentation that has one or more stop words removed from the candidate segmentation.

5. The computer-implemented method of claim 4, wherein, for each of the one or more unique candidate segmentations, determining the respective measure of segmentation quality for the unique candidate segmentation further comprises:

determining the respective measure of segmentation quality based at least in part on how many stop words have been removed from the respective sequence of segments of the candidate segmentation.

6. The method of claim 2, wherein, for each of the one or more unique candidate segmentations, determining the respective measure of segmentation quality for the unique candidate segmentation further comprises:

determining a respective second frequency of occurrence for the candidate segmentation in a second query log as a complete query written in the first language; and

determining the respective measure of segmentation quality based at least in part on the respective second frequency of occurrence of the candidate segmentation in the second query log as a complete query written in the first language.

7. A system, comprising:

one or more processors; and

memory having instructions stored thereon, the instructions, when executed by the one or more processors, cause the one or more processors to perform operations comprising;

receiving a query written in a first language;

obtaining one or more unique candidate segmentations of the query in the first language, each unique candidate segmentation consisting of a respective sequence of segments resulted from segmenting the query in the first language;

for each of the one or more unique candidate segmentations;

determining a respective measure of segmentation quality for the unique candidate segmentation; and

obtaining a respective set of one or more candidate translation in a second language by translating the respective sequence of segments of the candidate segmentation;

for each candidate translation of each of the one or more unique candidate segmentations;

determining a first frequency of occurrence of the candidate translation in a first query log as a complete query written in the second language; and

determining a respective score for the candidate translation based at least on the first frequency of occurrence of the candidate translation in the first query log as a complete query written in the second language, and the

measure of segmentation quality for the candidate segmentation; and

providing at least one of the candidate translations as a cross-language query suggestion for the query based on respective scores of the candidate translations.

8. The system of claim 7, wherein obtaining the one or more unique candidate segmentations of the query in the first language further comprises:

obtaining at least one segmentation that is a partition of the query in the first language.

9. The system of claim 7, wherein obtaining the one or more unique candidate segmentations of the query in the first language further comprises:

obtaining at least one candidate segmentation that has one or more stop words removed from the candidate segmentation.

10. The system of claim 9, wherein, for each of the one or more unique candidate segmentations, determining the respective measure of segmentation quality for the unique candidate segmentation further comprises:

determining the respective measure of segmentation quality based at least in part on how many stop words have been removed from the respective sequence of segments of the candidate segmentation.

11. The system of claim 7, wherein, for each of the one or more unique candidate segmentations, determining the respective measure of segmentation quality for the unique candidate segmentation further comprises:

determining a respective second frequency of occurrence for the candidate segmentation in a second query log as a complete query written in the first language; and

determining the respective measure of segmentation quality based at least in part on the respective second frequency of occurrence of the candidate segmentation in the second query log as a complete query written in the first language.