Techniques are described for promoting content items in a page to load in a different order than the order in which they were initially designated to load in the page. A page may include critical content items designated to load earlier than non-critical content items. In instances where there is a delay due to latency in generating or retrieving the critical content items, one or more non-critical content items may be promoted to load earlier than initially designated. By promoting non-critical content items to load during the period in which the loading of the page may otherwise be stalled, overall page load times may be reduced. Content transport may employ a multi-stream networking protocol that multiplexes a plurality of streams, and promotion may include writing to a particular stream during the delay in availability of the critical content items.

A computer-implemented method includes generating, using a transaction management computing subsystem of an advertising platform, a set of primary bid requests responsive to receipt of an advertising call. Each primary bid request includes information sufficient to characterize an impression consumer and information sufficient to characterize each of one or more impressions identified in the advertising call. The method also includes sending the set of primary bid requests from the transaction management computing subsystem to a first set of decisioning computing subsystems of the advertising platform. Each decisioning computing subsystem of the first set being operable to generate a bid response based on the information included in a primary bid request. The method further includes selecting, using the transaction management computing subsystem, a first bid response from among the bid responses generated by the first set of decisioning computing subsystems; and taking, by the transaction management computing subsystem, an action on the first bid response.

Techniques are disclosed utilizing cognitive computing to improve banking experiences. A user's financial account(s) and location may be monitored to predict when a user is near a retail store and the user has not used a particular account in a predetermined amount of time. The techniques disclosed include receiving a location for a user's mobile device, and determining when the mobile device is within a predetermined threshold distance of a retail store. The techniques include building a shopping profile for the user based upon shopping habits for the user. The shopping profile may be used to determine what commercial communications should be transmitted to the user to encourage them to utilize an inactive account to make a purchase at the retail store when the user is within the threshold distance of the retail store.

A content providing entity controls use of a cookie that is placed on individual computers that download a resource from a publisher site, hosted at publisher domain. The individual computers can be programmatically triggered to directly transmit cookie data, collected through placement of the cookie on the respective computer, to a network location that resides with a domain of the content providing entity. The content providing entity can select, using the cookie data, a subset group of the visitors to receive content items selected from an inventory database of the content providing entity. The content providing entity transmits the selected content items to the computers of the subset group using the cookie stored with each of the visitor computers.

An online transaction processing service may be used by a merchant to process payments for purchase transactions. The service may also support the merchant in other ways, such as by managing sales promotions and points-based loyalty programs. The service is configured to analyze customer purchasing behaviors, to identify groups of customers exhibiting similar purchasing behaviors, and to recommend sales promotions to particular groups of customers. The particular groups to which promotions are directed may be selected by the system based on sales priorities of the merchant and/or the business type of the merchant. The products offered as part of the promotions may similarly be selected based on sales priorities and business types, as well as existing inventories of products and profit margins associated with the products.

A method for identifying and removing malicious code uses a personal computing device that can communicate with a remote server. The remote server manages a blacklist and a whitelist. The blacklist is a list of programs that are known to contain malicious code. The whitelist is a list of programs that are known to be free of malicious code. The method begins when a scan request is received. The scan request is a command that directs the personal computing device to work with the remote server to perform a scan of a collection of files that will identify malicious code. The method then performs a sandboxed-evaluation process to identify files that are found to contain malicious code. The sandboxed-evaluation process is an isolated testing routine that runs program files to detect malicious code. Finally, the method executes a threat remediation process if malicious code is found.

A method and system for placement of graphical objects on a page to optimize the occurrence of an event associated with such objects. The graphical objects might include, for instance, advertisements on a webpage, and the event would include a user clicking on that ad. The page includes positions for receipt of the object material. Data regarding the past performance of the objects is stored and updated as new data is received. A user requests a page from a server associated with system. The server uses the performance data to derive a prioritized arrangement of the objects on the page. The objects are arranged according to a calculation and returned to the user on the requested page.

A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. The sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. The first or second activity information can include a cookie, which can be used to identify a node in a social graph as being representative of a particular person or user. When a match is not found, a fingerprinting approach can be performed using attributes, such as device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, or behavioral patterns.

Systems and methods are for identifying online advertisements to display to a user based on historical user data collected across the user's use of a plurality of Internet devices. One method includes receiving, over a network, a request for an advertisement to display at a first device of the user, the request including a unique identifier stored on the user's first device; accessing, in a database, a demographic or browsing history information generated from the user's use of a second device, the demographic or browsing history information being stored in the database in relation to the unique identifier; and identifying, based on the demographic or browsing history information, an advertisement to display at the user's first device. The demographic or browsing history information is synchronized based on the unique identifier being stored on the user's first device and the user's second device.

A revenue share analysis module can determine individual session revenues for content items provided by content providers. The module can also determine total session content revenues for each of the content items according to the determined individual session revenues, and determine respective content values for each of the content items according to the determined total session revenues for each of the content items. It also may determine total session provider revenues for each of the content providers according to the determined total session revenues for each of the content items, and determine respective provider values for each of the content providers according to the determined total session revenues for each of the content providers. Also, it can determine revenue share offers according to the content values and/or the provider values.