Abstract: Product recommendations are selected according to a model. Product recommendations may be annotated with rules of the model used to select the products. A user may modify the model and be provided with a URL and a cookie associated with the modified model. Subsequent requests or the URL and presenting the cookie are processed using the modified model. A context may be associated with the cookie and modified by the user to observe performance of the model for the context. An interface may permit a user to specify rules for the model or otherwise model its behavior. User interactions with a website result in recommendations according to the model. A journey is recorded that records content, recommendations, and parameters of the model corresponding to the recommendations. The journeys of users may be filtered and visually presented to a user.

Abstract: Product recommendations are selected according to a model. Product recommendations may be annotated with rules of the model used to select the products. A user may modify the model and be provided with a URL and a cookie associated with the modified model. Subsequent requests or the URL and presenting the cookie are processed using the modified model. A context may be associated with the cookie and modified by the user to observe performance of the model for the context. An interface may permit a user to specify rules for the model or otherwise model its behavior. User interactions with a website result in recommendations according to the model. A journey is recorded that records content, recommendations, and parameters of the model corresponding to the recommendations. The journeys of users may be filtered and visually presented to a user.

Abstract: Product recommendations are selected according to a model. Product recommendations may be annotated with rules of the model used to select the products. A user may modify the model and be provided with a URL and a cookie associated with the modified model. Subsequent requests or the URL and presenting the cookie are processed using the modified model. A context may be associated with the cookie and modified by the user to observe performance of the model for the context. An interface may permit a user to specify rules for the model or otherwise model its behavior. User interactions with a website result in recommendations according to the model. A journey is recorded that records content, recommendations, and parameters of the model corresponding to the recommendations. The journeys of users may be filtered and visually presented to a user.

Abstract: Example search quality improvement systems and methods are described. In one implementation, a search implementation engine receives a request for an item that includes a first color. The search implementation engine identifies a color representation associated with the first color and determines a second color perceptually similar to the first color based on the color representation. The search implementation engine then identifies an instance of the item having a second color and communicates data associated with the instance of the item to a source of the request.

Abstract: Advertising impressions are collected and a block in a block chain is created for each impression or a set of impressions. Each block includes a hash of a preceding block in the block chain. The block chain may be traversed to analyze advertising impressions and determine their effectiveness. Advertising content may include embedded code that invokes transmission of a notification to a server. The server creates a block in response to the notification that includes data such as the advertising content (or a reference to it), attributes of a target consumer, information regarding an advertising campaign, and/or other data describing the advertising impression.

Abstract: Browser requests are received and data included in it is added to a vector. If explicit identification information (username, cookie data, etc.) is present, the vector is associated with a pre-existing user record, which is then updated. If not, candidate user records may be identified according to correspondence with values in the vector. Candidate vectors may be eliminated by identifying inconsistency in OS, device, and browser information. Probability assigned to each candidate vector may be adjusted, e.g., reduced, in response to inconsistency in other data relating to a browser. Personalized results are generated based on collected data for a user if possible. If not possible, fallback results are provided by a front end server based on values provided in a browser request matching entries in a fallback database accessed by the front end server. Default results may be provided where the fallback database does not provide a result.

Abstract: Browser requests are received and data included in it is added to a vector. If explicit identification information (username, cookie data, etc.) is present, the vector is associated with a pre-existing user record, which is then updated. If not, candidate user records may be identified according to correspondence with values in the vector. This may include comparing hashes of one or more values to identify similarities. Candidate vectors may be eliminated by identifying inconsistency in OS, device, and browser information. Probability assigned to each candidate vector may be adjusted, e.g., reduced, in response to inconsistency in other data relating to a browser, device, or of a more global nature, e.g. time zone, user attributes, etc. Records associated with different devices may be associated with one another by evaluating hashes of data values submitted by a user on the different devices. Where the hash values of two records intersect, they may be merged with one another.

Abstract: Data from browser requests is added to a vector. If explicit identification information (username, cookie data, etc.) is present, the vector is associated with a pre-existing user record, which is then updated. If not, candidate user records may be identified according to correspondence with values in the vector. This may include comparing hashes of one or more values to identify similarities. Candidate vectors may be eliminated by identifying inconsistency in OS, device, and browser information. Probability assigned to each candidate vector may be adjusted, e.g., reduced, in response to inconsistency in other data relating to a browser, device, or of a more global nature, e.g. time zone, user attributes, etc. Records associated with different devices may be associated with one another by evaluating hashes of data values submitted by a user on the different devices. Where the hash values of two records intersect, they may be merged with one another.

Abstract: A web page or group of pages can be automatically generated based on images selected by a user. The images are analyzed for color and groups of colors for the page background and image framing are determined. Images are analyzed to determine the shapes of the images and the images are placed within appropriate shapes on a page on the web. Click-through rate can be estimated for images and this click-through rate used during the web page generation. Important sections are evaluated in the images and cropping may occur for the images on a page. Text and video can be part of the web page. Software applications can be accessed from the web page as well. The online web pages can be tailored for presentation on a mobile device.

Abstract: A web page or group of pages can be automatically generated based on images selected by a user. The images are analyzed for color and groups of colors for the page background and image framing are determined. Images are analyzed to determine the shapes of the images and the images are placed within appropriate shapes on a page on the web. Click-through rate can be estimated for images and this click-through rate used during the web page generation. Important sections are evaluated in the images and cropping may occur for the images on a page. Text and video can be part of the web page. Software applications can be accessed from the web page as well. The online web pages can be tailored for presentation on a mobile device.