Abstract: Systems, methods, and computer-readable media for providing fresh product listing advertisements in response to a search query are presented. More particularly, in response to receiving a search query, a plurality of search results are identified, which search results are relevant to the search query. Additionally, a first set of product listing advertisements is identified. A second set of product listing advertisements, which are fresh product listing advertisements, are also identified and combined into the first set. Upon generating the search results page, at least some of the identified search results and some of the product listing advertisements are included. At least one of the fresh product listing advertisements is included in the generated search results page. The at least one fresh product listing advertisement is tagged with an annotation indicating that the advertisement is a fresh product listing advertisement.

Abstract: Described are a system and method for selecting a training sample from a sample set. The method comprises determining proximities between all data samples in a set of the data samples, forming edges between the data samples as a function of the proximities, computing weights for the edges as a function of the proximities, selecting a plurality of the data samples as a function of the weights to form a subset of the data samples, and storing the subset of the data samples.

Abstract: Described are a system and method for selecting a training sample from a sample set. The method comprises determining proximities between all data samples in a set of the data samples, forming edges between the data samples as a function of the proximities, computing weights for the edges as a function of the proximities, selecting a plurality of the data samples as a function of the weights to form a subset of the data samples, and storing the subset of the data samples.

Abstract: The present invention is directed towards systems and methods for generating a linear regression model based on statistically frequent query pairs. The method of the present invention comprises storing statistically frequent query pairs, the query pairs constituting a query and a query rewrite. Query pair samples are generated based on the statistically frequent query pairs and an active learning algorithm is utilized to select the most informative query pairs. A linear regression algorithm is then utilized to generate a linear regression model based on the selected most informative query pairs.