METHOD AND SYSTEM FOR PREDICTING SEARCH RESULTS QUALITY IN VERTICAL RANKING
First Claim
1. A method, implemented on at least one machine each of which has at least one processor, storage, and a communication platform connected to a network for predicting search results quality, the method comprising the steps of:
- receiving a search query from a user;
obtaining a plurality of search results from a content source based on the search query, wherein the plurality of search results are ranked based on their relevance scores with respect to the search query;
normalizing a distribution of the relevance scores of the plurality of search results in each position of the ranking; and
computing a metric of the content source based on the normalized distribution of the relevance scores, wherein the metric indicates a relevance between the plurality of search results and the search query.
9 Assignments
0 Petitions
Accused Products
Abstract
Methods, systems and programming for predicting search results quality. In one example, a search query is received from a user. A plurality of search results are obtained from a content source based on the search query. The plurality of search results are ranked based on their relevance scores with respect to the search query. A distribution of the relevance scores of the plurality of search results is normalized in each position of the ranking. A metric of the content source is computed based on the normalized distribution of the relevance scores. The metric indicates a relevance between the plurality of search results and the search query.
25 Citations
20 Claims
-
1. A method, implemented on at least one machine each of which has at least one processor, storage, and a communication platform connected to a network for predicting search results quality, the method comprising the steps of:
-
receiving a search query from a user; obtaining a plurality of search results from a content source based on the search query, wherein the plurality of search results are ranked based on their relevance scores with respect to the search query; normalizing a distribution of the relevance scores of the plurality of search results in each position of the ranking; and computing a metric of the content source based on the normalized distribution of the relevance scores, wherein the metric indicates a relevance between the plurality of search results and the search query. - View Dependent Claims (4, 5, 6, 7, 8, 9)
-
-
3-2. The system of claim 12, wherein the mean and the standard deviation of relevance scores in the position are obtained by:
-
obtaining a plurality of sample query results from the content source based on each of a plurality of sample queries, each of the sample query results being ranked in the position; and computing the mean and the standard deviation of the plurality of sample queries results in the position.
-
-
10. The method of claim 1, wherein the content source includes a vertical in vertical search.
-
10-1. A system having at least one processor storage, and a communication platform for predicting search results quality, the system comprising:
-
a search engine configured to receive a search query from a user and obtain a plurality of search results from a content source based on the search query, wherein the plurality of search results are ranked based on their relevance scores with respect to the search query; a normalization module configured to normalize a distribution of the relevance scores of the plurality of search results in each position of the ranking; and a ranking module configured to compute a metric of the content source based on the normalized distribution of the relevance scores, wherein the metric indicates a relevance between the plurality of search results and the search query.
-
- 12. The system of claim 11, wherein the ranking engine includes a normalization module configured to, in each position of the ranking, compute a normalized relevance score of the respective search result based on a mean and a standard deviation of relevance scores in the position.
-
14. The system of claim 11, wherein the ranking engine includes a normalization module configured to
build an order-statistic model based on a first set of the search results; - and
generate estimated relevance scores of a second set of the search results based on the order-statistic model. - View Dependent Claims (15, 16, 17, 18, 19)
- and
-
20. A non-transitory machine-readable medium having information recorded thereon for predicting, search results quality, wherein the information, when read by the machine, causes the machine to perform the following:
-
receiving a search query from a user; obtaining a plurality of search results from a content source based on the search query, wherein the plurality of search results are ranked based on their relevance scores with respect to the search query; normalizing a distribution of the relevance scores of the plurality of search results in each position of the ranking; and computing a metric of the content source based on the normalized distribution of the relevance scores, wherein the metric indicates a relevance between the plurality of search results and the search query.
-
Specification