Abstract: In an exemplary embodiment, a computer-implemented method includes providing a mapping between a set of two or more IP addresses and a set of two more servers. A weight recommendation for the servers is received, based at least in part on server data related to current states of the servers, where the weight recommendation represents a goal for distributing a plurality of transactions among the servers. The mapping is modified based at least in part on the weight recommendation. A transaction is received, directed toward a first IP address of the two or more IP addresses. The transaction is routed to a first server, of the two or more servers, associated with the first IP address according to the modified mapping.

Abstract: According to one exemplary embodiment, a method for reducing load on a mobile network after the occurrence of a disaster event is provided. The method may include receiving a disaster location time. The method may include determining a target area based on the disaster location. The method may include determining target persons located within the target area. The method may include predicting the location of each target person based on historical movement data associated with each target person. The method may include determining a plurality of filtered persons based on the predicted location of each target person and the disaster time. The method may include determining a plurality of safe persons based on the filtered persons and a safety indicator. The method may include sending a safety notification to a plurality of concerned contacts associated with each safe person and blocking network traffic associated with each safe person.

Abstract: Provided are techniques for the generation of advertising content based upon users' needs and use cases. The techniques include monitoring social media to generate a history of user interest; identifying a current interest of a user based upon information derived from a group of sources, the first group of sources comprising: social media data corresponding to the user; communications to and from the user; interactions between the user and other users; calendar entries of the user; and a location corresponding to the user; predicting a user case corresponding to a product such that the use case conforms to the current interest; generating an advertisement based upon the use case and a second group of sources, the second group of sources comprising literature corresponding to the product; user feedback with respect to the product; user ratings of the product; and blogs referencing the product; and displaying the advertisement to the user.

Abstract: Provided are techniques for the generation of advertising content based upon users' needs and use cases. The techniques include monitoring social media to generate a history of user interest; identifying a current interest of a user based upon information derived from a group of sources, the first group of sources comprising: social media data corresponding to the user; communications to and from the user; interactions between the user and other users; calendar entries of the user; and a location corresponding to the user; predicting a user case corresponding to a product such that the use case conforms to the current interest; generating an advertisement based upon the use case and a second group of sources, the second group of sources comprising literature corresponding to the product; user feedback with respect to the product; user ratings of the product; and blogs referencing the product; and displaying the advertisement to the user.

Abstract: Automatically screen data associated with a user that may have already been shared on a social network or about to be shared on the social network for a potential security risk and assign a risk score to the data. If the assigned risk score is above a threshold risk score, a risk mitigation measure is generated and executed.

Abstract: Automatically screen data associated with a user that may have already been shared on a social network or about to be shared on the social network for a potential security risk and assign a risk score to the data. If the assigned risk score is above a threshold risk score, a risk mitigation measure is generated and executed.

Abstract: A system, method, and program product that prioritizes Internet advertising for a particular product for a consumer. A system is disclosed that includes: an information gathering system that gathers purchasing information of a consumer; an identification analyzer that identifies at least one potential product for the consumer; a product analyzer that determines whether the at least one potential product is a utility item or a vanity item; and a prioritizing engine including: a vanity scoring engine that assigns an advertising score based on whether the consumer owns the vanity item, whether the vanity item is consumable, and a vanity score for the consumer and a utility scoring engine that assigns an advertising score based on whether the consumer owns the utility item and whether the utility item is consumable, wherein in response to the assigned advertising score exceeding an advertising threshold, an Internet advertisement is presented to the consumer.

Abstract: According to one exemplary embodiment, a method for reducing load on a mobile network after the occurrence of a disaster event is provided. The method may include receiving a disaster location time. The method may include determining a target area based on the disaster location. The method may include determining target persons located within the target area. The method may include predicting the location of each target person based on historical movement data associated with each target person. The method may include determining a plurality of filtered persons based on the predicted location of each target person and the disaster time. The method may include determining a plurality of safe persons based on the filtered persons and a safety indicator. The method may include sending a safety notification to a plurality of concerned contacts associated with each safe person and blocking network traffic associated with each safe person.

Abstract: According to one exemplary embodiment, a method for reducing load on a mobile network after the occurrence of a disaster event is provided. The method may include receiving a disaster location time. The method may include determining a target area based on the disaster location. The method may include determining target persons located within the target area. The method may include predicting the location of each target person based on historical movement data associated with each target person. The method may include determining a plurality of filtered persons based on the predicted location of each target person and the disaster time. The method may include determining a plurality of safe persons based on the filtered persons and a safety indicator. The method may include sending a safety notification to a plurality of concerned contacts associated with each safe person and blocking network traffic associated with each safe person.

Abstract: Embodiments of the disclosure relate to performing correction on incoming messages. Embodiments include receiving a message from a sender and determining if a portion of the message has been auto-corrected by the sender. Embodiments also include performing a correction on the portion of the message that was auto-corrected by the sender and storing the correction made by the receiver for each individual sender.

Abstract: Embodiments of the disclosure relate to performing correction on incoming messages. Embodiments include receiving a message from a sender and determining if a portion of the message has been auto-corrected by the sender. Embodiments also include performing a correction on the portion of the message that was auto-corrected by the sender and storing the correction made by the receiver for each individual sender.

Abstract: Embodiments of the disclosure relate to providing auto-correction feedback in a messaging application. Embodiments include receiving a message from a sender and selecting a portion of the message for clarification. Embodiments also include creating a proposed modification to the message and transmitting the proposed modification to the message to the sender. Embodiments further include receiving a response from the sender regarding the proposed modification.

Abstract: Embodiments of the disclosure relate to performing correction on incoming messages. Embodiments include receiving a message from a sender and determining if a portion of the message has been auto-corrected by the sender. Embodiments also include performing a correction on the portion of the message that was auto-corrected by the sender and storing the correction made by the receiver for each individual sender.

Abstract: A method of generating a targeted advertisement by identifying a target criteria from an entry of a search history associated with a user, identifying an intended recipient based on social information associated with the user and the target criteria, and associating at least one item with the intended recipient by analyzing the social information and the target criteria. Further, the method includes outputting as advertisement information the at least one item and at least one of a plurality of advertisement recipients. The advertisement information enables the generation of the targeted advertisement and the at least one item is utilized in the targeted advertisement.

Abstract: A method of generating a targeted advertisement by identifying a target criteria from an entry of a search history associated with a user, identifying an intended recipient based on social information associated with the user and the target criteria, and associating at least one item with the intended recipient by analyzing the social information and the target criteria. Further, the method includes outputting as advertisement information the at least one item and at least one of a plurality of advertisement recipients. The advertisement information enables the generation of the targeted advertisement and the at least one item is utilized in the targeted advertisement.

Abstract: In one embodiment, a computer-implemented method includes receiving a plurality of tasks to be assigned to a plurality of subgroups of virtual servers. A first plurality of the tasks is assigned to a first subgroup, where the first subgroup includes two or more virtual servers. For each of the first plurality of tasks assigned to the first subgroup, a virtual server is selected within the first subgroup, and the task is assigned to the selected virtual server. A first virtual server is migrated, by a computer processor, from the first subgroup of virtual servers to a second subgroup of virtual servers, if at least one predetermined condition is met, where the migration maintains in the first subgroup at least one of the first plurality of tasks assigned to the first subgroup.

Abstract: In an exemplary embodiment, a computer-implemented method includes identifying at least a portion of an image as a taggable product appearing in the image. A tag is generated, by a computer processor, for the taggable product. The tag is associated with the identified portion of the image and includes information about the taggable product, where generating the tag converts the taggable product into a tagged product. A first ad is prioritized over a plurality of other ads for display on a web page in conjunction with the image, where the prioritization is based at least in part on the first ad being related to the tagged product.

Abstract: In an exemplary embodiment, a computer-implemented method includes receiving a photo showing a taggable object, wherein the taggable object is a purchasable object that has not yet been identified. First purchase data is collected related to past purchases of a first user associated with the photo. The first purchase data is compared to the taggable object to determine whether one or more purchased items potentially match the taggable object. A set of potential matches is generated, by a computer processor, based at least in part on comparing the first purchase data to the taggable object. The taggable object is tagged in the photo with an identifier representing at least one of the potential matches.

Abstract: In an exemplary embodiment, a computer-implemented method includes identifying at least a portion of an image as a taggable product appearing in the image. A tag is generated, by a computer processor, for the taggable product. The tag is associated with the identified portion of the image and includes information about the taggable product, where generating the tag converts the taggable product into a tagged product. A first ad is prioritized over a plurality of other ads for display on a web page in conjunction with the image, where the prioritization is based at least in part on the first ad being related to the tagged product.

Abstract: In an exemplary embodiment, a computer-implemented method includes receiving a photo showing a taggable object, wherein the taggable object is a purchasable object that has not yet been identified. First purchase data is collected related to past purchases of a first user associated with the photo. The first purchase data is compared to the taggable object to determine whether one or more purchased items potentially match the taggable object. A set of potential matches is generated, by a computer processor, based at least in part on comparing the first purchase data to the taggable object. The taggable object is tagged in the photo with an identifier representing at least one of the potential matches.