A method for generating a report is provided. The method may include acquiring a key word related to an industry field, and acquiring one or more condition values related to the report to be generated. The method may also include determining a report template having one or more data query sections and one or more conclusion sections based on the industry field and the one or more condition values, and acquiring report data based on the one or more data query sections of the report template. The method may further include determining one or more conclusions based on the report data, and generating the report based the data acquired based on the report data, the one or more conclusions, and the template.

A method for generating a report is provided. The method may include acquiring a key word related to an industry field, and acquiring one or more condition values related to the report to be generated. The method may also include determining a report template having one or more data query sections and one or more conclusion sections based on the industry field and the one or more condition values, and acquiring report data based on the one or more data query sections of the report template. The method may further include determining one or more conclusions based on the report data, and generating the report based the data acquired based on the report data, the one or more conclusions, and the template.

Generating structured data from screen recordings is disclosed, including: obtaining, from a client device, a screen recording of a user's activities on the client device with respect to a task; performing, at a server, video validation on the screen recording, including by determining whether the screen recording matches a set of validation parameters associated with the task; and generating a set of structured data based at least in part on the video validation.

An example apparatus includes: at least one memory; instructions in the apparatus; and processor circuitry to execute the instructions to: access a cookie at a client device, the cookie including a priority listing indicative of an order in which beacon requests are to be sent to ones of a plurality of database proprietors; cause a first beacon request to be sent to a first database proprietor server, the first database proprietor server corresponding to a highest priority in the priority listing of the cookie, the first beacon request indicative of access to media at the client device; and cause a second beacon request to be sent to a second database proprietor server, the second database proprietor server corresponding to a lower priority than the highest priority in the priority listing of the cookie, the second beacon request indicative of the access to the media at the client device.

An example apparatus includes: at least one memory; instructions in the apparatus; and processor circuitry to execute the instructions to: access a cookie at a client device, the cookie including a priority listing indicative of an order in which beacon requests are to be sent to ones of a plurality of database proprietors; cause a first beacon request to be sent to a first database proprietor server, the first database proprietor server corresponding to a highest priority in the priority listing of the cookie, the first beacon request indicative of access to media at the client device; and cause a second beacon request to be sent to a second database proprietor server, the second database proprietor server corresponding to a lower priority than the highest priority in the priority listing of the cookie, the second beacon request indicative of the access to the media at the client device.

A computer-implemented method may include: receiving, by a first computer server, content provider data and content item data; identifying a plurality of profile elements by applying machine learning techniques to the received content provider data and content item data; calculating a first plurality of profile element scores for the content provider in each of the plurality of profile elements and a second plurality of profile element scores for the plurality of content items in each of the plurality of profile elements; determining, by utilizing one or more distance algorithms, profile element vector distances between the first plurality of profile element scores for the content provider and the plurality of second profile element scores for the plurality of content items; ranking the plurality of content items based on the determined profile element vector distances; and generating an interactive graphical user interface (GUI) displaying a plurality of radar graphs.

Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.

Methods and systems for analyzing and evaluating item recommendations presented on a web site are disclosed. In one aspect, a user interface is generated for display on a website. Item recommendations personalized for an individual user are displayed within in item recommendation region of the website. Impression, clickstream, and sales data are received from user activity on the website. The impression, clickstream, and sales data are displayed on a dashboard of an administrator user interface. An administrator user can select visualizations to display on the dashboard using selectors for impressions, clicks, sales, users, and time. Two or more sets of data can be overlaid to illustrate relationships between user interactions with recommended items and actual sales of those items. The dashboard is dynamically updated in response to new data received from the website in real-time.

Methods and systems for analyzing and evaluating item recommendations presented on a web site are disclosed. In one aspect, a user interface is generated for display on a website. Item recommendations personalized for an individual user are displayed within in item recommendation region of the website. Impression, clickstream, and sales data are received from user activity on the website. The impression, clickstream, and sales data are displayed on a dashboard of an administrator user interface. An administrator user can select visualizations to display on the dashboard using selectors for impressions, clicks, sales, users, and time. Two or more sets of data can be overlaid to illustrate relationships between user interactions with recommended items and actual sales of those items. The dashboard is dynamically updated in response to new data received from the website in real-time.

A visual tracking system for tracking and identifying persons within a monitored location, comprising a plurality of cameras and a visual processing unit, each camera produces a sequence of video frames depicting one or more of the persons, the visual processing unit is adapted to maintain a coherent track identity for each person across the plurality of cameras using a combination of motion data and visual featurization data, and further determine demographic data and sentiment data using the visual featurization data, the visual tracking system further having a recommendation module adapted to identify a customer need for each person using the sentiment data of the person in addition to context data, and generate an action recommendation for addressing the customer need, the visual tracking system is operably connected to a customer-oriented device configured to perform a customer-oriented action in accordance with the action recommendation.