METHODS FOR AUTOMATIC QUERY TRANSLATION
User-specific queries for items may be collected from a search engine in language A and corresponding behavioral data with respect to items returned for the queries, such as items viewed, watched, liked, clicked, and bought by the user may also be collected. Similar data may be gathered for user specific queries from a search engine in language B. For query pairs, each in a different language, the system may measure the similarity of their user behavioral data using language independent features such as images, UPC codes, price, seller, category, and the like, and using translated features such as descriptors that comprise keywords that describe the items returned in response to the queries. Those pairs of queries in the two languages with high similarity of user behavior are statistically translations of each other.
1 . A method of translating queries comprising:
collecting query data in a first language, the query data in the first language comprising queries for items and user behavioral data with respect to items returned in response to the queries;
collecting query data in a second language, the query data in the second language comprising queries in the second language for items and user behavioral data with respect to items returned in response to the queries in the second language;
for query data pairs comprising query data in the first language and query data in the second language, measuring, by at least one computer processor, the similarity of the user behavioral data of the respective query data of the query data pairs;
determining respective pairs of queries in the first language and queries in the second language that have high similarity of user behavioral data to each other; and
using the determined respective pairs of queries as statistical translations of each other.
2 . The method of claim 1 wherein the query data in the first language are converted to first feature vectors and the query data in the second language are converted to second feature vectors, and the measuring the similarity of the user behavioral data of the respective query data of the query data pairs comprises measuring the similarity of the first feature vectors to second feature vectors.
3 . The method of claim 2 wherein the determining respective pairs of queries that have high similarity of user behavioral data to each other comprises computing a pairwise distance matrix for the feature vectors of the queries and, for respective first feature vectors, searching for the most similar second feature vector.
4 . The method of claim 2 wherein the first feature vectors and the second feature vectors comprise translation invariant features and translated features.
5 . The method of claim 4 wherein the translation invariant features comprise at least one of UPC code, price, category information, model numbers, brand names, attributes, seller identification, or country of origin of the items returned in response to the queries.
6 . The method of claim 4 wherein the translated features comprise descriptors that comprise keywords that describe the items returned in response to the queries.
7 . The method of claim 1 wherein the query data comprises queries issued by one of a mobile communication device, a laptop, or a stationary communication device.
8 . One or more computer-readable hardware storage device having embedded therein a set of instructions which, when executed by one or more processors of a computer, causes the computer to execute operations comprising:
collecting query data in a first language, the query data in the first language comprising queries for items and user behavioral data with respect to items returned in response to the queries;
collecting query data in a second language, the query data in the second language comprising queries in the second language for items and user behavioral data with respect to items returned in response to the queries in the second language;
for query data pairs comprising query data in the first language and query data in the second language, measuring, by at least one computer processor, the similarity of the user behavioral data of the respective query data of the query data pairs;
determining respective pairs of queries in the first language and queries in the second language that have high similarity of user behavioral data to each other; and
using the determined respective pairs of queries as statistical translations of each other.
9 . The one or more computer-readable hardware storage device of claim 8 wherein the query data in the first language are converted to first feature vectors and the query data in the second language are converted to second feature vectors, and the measuring the similarity of the user behavioral data of the respective query data of the query data pairs comprises measuring the similarity of the first feature vectors to the second feature vectors.
10 . The one or more computer-readable hardware storage device of claim 9 wherein the determining respective pairs of queries that have high similarity of user behavioral data to each other comprises computing a pairwise distance matrix for the feature vectors of the queries and, for respective first feature vectors, searching for the most similar second feature vector.
11 . The one or more computer-readable hardware storage device of claim 9 wherein the feature vectors comprise translation invariant features and translated features.
12 . The one or more computer-readable hardware storage device of claim 11 wherein the translation invariant features comprise at least one of UPC code, price, category information, model numbers, brand names, attributes, seller identification, or country of origin of the items returned in response to the queries.
13 . The one or more computer-readable hardware storage device of claim 11 wherein the translated features comprise descriptors that comprise keywords that describe the items returned in response to the queries.
14 . The one or more computer-readable hardware storage device of claim 8 wherein the query data comprises queries issued by one of a mobile communication device, a laptop, or a stationary communication device.
15 . A system for translating queries comprising:
one or more computer processors and storage configured to execute
a query/behavior gathering module for collecting query data in a first language, the query data in the first language comprising queries for items and user behavioral data with respect to items returned in response to the queries;
a query/behavior gathering module collecting query data in a second language, the query data in the second language comprising queries in the second language for items and user behavioral data with respect to items returned in response to the queries in the second language;
a vector similarity measurement module that, for query data pairs comprising query data in the first language and query data in the second language, measures the similarity of the user behavioral data of the respective query data of the query data pairs; and
a query pair translation module for determining respective pairs of queries in the first language and queries in the second language that have high similarity of user behavioral data to each other, and using the determined respective pairs of queries as statistical translations of each other.
16 . The system of claim 15 wherein the one or more computer processors and storage are further configured to execute feature vector modules to convert the query data in the first language to first feature vectors and the query data in the second language to second feature vectors, and the measuring the similarity of the user behavioral data of the respective query data of the query data pairs comprises measuring the similarity of the first feature vectors to the second feature vectors.
17 . The system of claim 16 wherein the determining respective pairs of queries that have high similarity of user behavioral data to each other comprises computing a pairwise distance matrix for the feature vectors of the queries and, for respective first feature vectors, searching for the most similar second feature vector.
18 . The system of claim 16 wherein the feature vectors comprise translation invariant features and translated features.
19 . The system of claim 18 wherein the translation invariant features comprise at least one of UPC code, price, category information, model numbers, brand names, attributes, seller identification, or country of origin of the items returned in response to the queries.
20 . The system of claim 18 wherein the translated features comprise descriptors that comprise keywords that describe the items returned in response to the queries.