Abstract:
Various example embodiments are provided for inferring relationships between queries. In an example, queries are related based on the identification of common terms between the queries. Another example is to relate queries based on the identification that the queries are associated with a single search session. Yet another example is to infer relationships based on the identification of relationships between item attributes retrieved from the submission of the queries.
Abstract:
An apparatus and method for obtaining image feature data of an image are disclosed herein. A color histogram of the image is extracted from the image, the extraction of the color histogram including performing one-dimensional sampling of pixels comprising the image in each of a first dimension of a color space, a second dimension of the color space, and a third dimension of the color space. An edge map corresponding to the image is analyzed to detect a pattern included in the image. In response to a confidence level of the pattern detection being below a pre-defined threshold, extracting from the image an orientation histogram of the image. And identify a dominant color of the image.
Abstract:
In various example embodiments, a system and method for sketch based queries are presented. A sketch corresponding to a search item may be received from a user. At least a portion of the sketch may be generated by the user. An item attribute may be extracted from the sketch. The item attributed may correspond to a physical attribute of the search item. A set of inventory items similar to the search item may be identified based on the extracted item attribute and a search scope. The identified set of inventory items may be presented to the user.
Abstract:
A system and method for determining relevancy for dynamic data sets is disclosed. A specific embodiment for use in an internet marketplace is presented wherein the relevancy for a descriptive factor associated with an item is increased when a user selects that item. To prevent abuse of the relevancy determination system, various embodiments incorporate abuse prevention measures. In one embodiment, a user's selection of the user's own items does not affect the relevancy system. In one embodiment, only a first selection of a particular item by a user will affect the relevancy system and any additional selections of that item will have no effect. In another embodiment, the size of the changes made due to the selections of particular user to the relevancy system are correlated to that user's reputation score.
Abstract:
In an example embodiment, a method is provided for image categorization. Here, images are displayed. In turn, a user input that describes a characteristic shared between the images from a comparison between the images is received. The user input may then be classified into categorization data.
Abstract:
In an example embodiment, a method is provided for image categorization. Here, images are displayed. In turn, a user input that describes a characteristic shared between the images from a comparison between the images is received. The user input may then be classified into categorization data.
Abstract:
A system receives context data associated with a context and a user. The system then associates the context data to a user identifier and retrieves data associated with the context. The system then filters the data according to the context data to create result data. In another embodiment, the system also receives context data from a plurality of users, where the context data pertains to one or more attributes of a context. The system then using the context data ranks the one or more attributes of the context to create ranked data and generates a user interface based on the ranked data. In yet another embodiment, the system communicates context data associated with a context and a user to a server, and receives result data created by the server filtering data retrieved based on the context data. The system then generates a user interface based on the result data.
Abstract:
An apparatus and method for obtaining image feature data of an image are disclosed herein. A color histogram of the image is extracted from the image, the extraction of the color histogram including performing one-dimensional sampling of pixels comprising the image in each of a first dimension of a color space, a second dimension of the color space, and a third dimension of the color space. An edge map corresponding to the image is analyzed to detect a pattern included in the image. In response to a confidence level of the pattern detection being below a pre-defined threshold, extracting from the image an orientation histogram of the image. And identify a dominant color of the image.
Abstract:
An apparatus and method to facilitate finding complementary recommendations are disclosed herein. One or more fashion trend or pleasing color combination rules are determined based on data obtained from one or more sources. One or more template images and rule triggers corresponding to the fashion trend or pleasing color combination rules are generated, each of the rule triggers associated with at least one of the template images. A processor compares a first image attribute of a particular one of the template images to a second image attribute of each of a plurality of inventory images corresponding to the plurality of inventory items to identify the inventory items complementary to the query image. The particular one of the template images is selected based on the rule trigger corresponding to the particular one of the template images being applicable for a query image.
Abstract:
A system receives context data associated with a context and a user. The system then associates the context data to a user identifier and retrieves data associated with the context. The system then filters the data according to the context data to create result data. In another embodiment, the system also receives context data from a plurality of users, where the context data pertains to one or more attributes of a context. The system then using the context data ranks the one or more attributes of the context to create ranked data and generates a user interface based on the ranked data. In yet another embodiment, the system communicates context data associated with a context and a user to a server, and receives result data created by the server filtering data retrieved based on the context data. The system then generates a user interface based on the result data.