Abstract: A system for trading goods over a computer network based on image processing includes an image processor that analyzes a picture received from a user to build a description of entities in the picture and correlations among the entities, a description interpreter that analyzes the description to determine an underlying message in the picture and detect information regarding the user's interests, emotions and affinities to goods and services, wherein the information is stored with the user's profile, the user's list of items to trade, and the user's past transaction history, and a trade matching component that uses the user's profile and produces a ranked list of other users with items to trade, or intermediary trade steps, when another user initiates a new trading transaction.

Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: A method for processing an attempted payment made using a mobile device includes receiving information about the attempted payment, receiving data indicative of a behavior of a user of the mobile device at the time of the attempted payment, computing a likelihood that the attempted payment is fraudulent, based on a comparison of the behavior of the user to an historical behavior pattern of the user, and sending an instruction indicating how to proceed with the attempted payment, based on the likelihood.

Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: A method includes generating one or more computing deployment solutions, each of the one or more computing deployment solutions specifying one or more parameters for deployment of a corresponding computing solution. The method also includes evaluating adoption of the one or more computing deployment solutions by respective ones of a plurality of computing systems utilizing one or more component evaluators connected via a network to the plurality of computing systems. The method further includes generating one or more solution deployment adoption reports for respective ones of the one or more computing deployment solutions based on information obtained over the network from the plurality of computing systems, and presenting the one or more solution deployment adoption reports via a dashboard user interface.

Abstract: A method for processing an attempted payment made using a mobile device includes receiving information about the attempted payment, receiving data indicative of a behavior of a user of the mobile device at the time of the attempted payment, computing a likelihood that the attempted payment is fraudulent, based on a comparison of the behavior of the user to an historical behavior pattern of the user, and sending an instruction indicating how to proceed with the attempted payment, based on the likelihood.

Abstract: A method for processing an attempted payment made using a mobile device includes receiving information about the attempted payment, receiving data indicative of a behavior of a user of the mobile device at the time of the attempted payment, computing a likelihood that the attempted payment is fraudulent, based on a comparison of the behavior of the user to an historical behavior pattern of the user, and sending an instruction indicating how to proceed with the attempted payment, based on the likelihood.

Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: A system for trading goods over a computer network based on image processing includes an image processor that analyzes a picture received from a user to build a description of entities in the picture and correlations among the entities, a description interpreter that analyzes the description to determine an underlying message in the picture and detect information regarding the user's interests, emotions and affinities to goods and services, wherein the information is stored with the user's profile, the user's list of items to trade, and the user's past transaction history, and a trade matching component that uses the user's profile and produces a ranked list of other users with items to trade, or intermediary trade steps, when another user initiates a new trading transaction.

Abstract: A data distribution system, method and a computer program product therefor. Computers provisioned with operations centers supporting individual locations share resources with organizations in multiple locations. Each operations center receives and evaluates local information for the supported location and selectively provides evaluated information for reuse by other locations. A data exchange agent in each operations center publishes information available from a supported location to a publication subscription unit. The operations center also subscribes to the publication subscription unit for information available from other locations. The publication subscription unit identifies matches between subscriptions and publications. A negotiation unit negotiates matched information transfers between operations centers.

Abstract: A trust rating is computed for a data requester across one or more dimensions by identifying the data requester, collecting information regarding the data requester from one or more sources, and generating the trust rating for the data requester across the one or more dimensions based on the collected information. The trust rating is utilized to either grant or deny a request by the data requester to access data associated with one or more data providers.

Abstract: A method for provisioning IT resources includes receiving a signal from an e-book reading device indicating that a user of the e-book reading device is approaching a practical procedure section within an e-book being read by the user on the e-book reading device. The practical procedure section includes an exercise to be performed by the user pertaining to the subject matter of the e-book. What IT resources are needed for the user to perform the exercise are determined. The needed IT resources are provisioned such that the IT resources that the needed IT resources are available when the user is ready to perform the exercise.

Abstract: A trust rating is computed for a data requester across one or more dimensions by identifying the data requester, collecting information regarding the data requester from one or more sources, and generating the trust rating for the data requester across the one or more dimensions based on the collected information. The trust rating is utilized to either grant or deny a request by the data requester to access data associated with one or more data providers.

Abstract: A method includes generating one or more computing deployment solutions, each of the one or more computing deployment solutions specifying one or more parameters for deployment of a corresponding computing solution. The method also includes evaluating adoption of the one or more computing deployment solutions by respective ones of a plurality of computing systems utilizing one or more component evaluators connected via a network to the plurality of computing systems. The method further includes generating one or more solution deployment adoption reports for respective ones of the one or more computing deployment solutions based on information obtained over the network from the plurality of computing systems, and presenting the one or more solution deployment adoption reports via a dashboard user interface.

Abstract: A system for trading goods over a computer network based on image processing includes an image processor that analyzes a picture received from a user to build a description of entities in the picture and correlations among the entities, a description interpreter that analyzes the description to determine an underlying message in the picture and detect information regarding the user's interests, emotions and affinities to goods and services, wherein the information is stored with the user's profile, the user's list of items to trade, and the user's past transaction history, and a trade matching component that uses the user's profile and produces a ranked list of other users with items to trade, or intermediary trade steps, when another user initiates a new trading transaction.

Abstract: In reply to a requester's credit request, a plurality of the requester's debtors are selected, each of which has a payment due to the requester during the repayment period. Repayment information for is retrieved for each debtor as is the requester's cash flow. A repayment probability score per debtor is computed based on the debtor's repayment history and the debtors are ranked based on the repayment probability score and an amount of the debtor's payments due. Debtors are further selected in order of rank until a total of their payment amounts at least equals a payment amount per installment. The computed repayment probability scores of the further selected debtors are aggregated into a bundle score, and a new credit score is computer for the credit request based on at least the bundle score, without reliance on information that may be used to identify any of the debtors.

Abstract: In a method for storing and recalling stored data, data to be stored is received and a first brain activity information from a user is received. The first brain activity is hashed to generate a first brain activity information hash value. The data is stored within a database and indexed. The indexing is done according to the first brain activity information hash value. The stored data is recalled when a request to recall the stored data is received along with a second brain activity information from a user. The received second brain activity is hashed to generate a second brain activity information hash value. The second brain activity information hash value is used to identify a location of the stored data, within the database, based on the indexing, by matching the second brain activity information hash value to the first brain activity information hash value. The stored data is then retrieved based on the identified location.

Abstract: A method of managing digital promises includes receiving transaction information and a request for a digital promise ranking. The transaction information includes identifying information of a first party and/or a second party. Each digital promise belongs to the first party and has a corresponding owner. A relationship score is calculated between the corresponding owner of each digital promise and the second party. An affinity score is calculated between the corresponding owner of each digital promise and the second party. A reputation score is calculated for the owner of each digital promise. A final score of each digital promise is calculated based on the relationship score, the affinity score and the reputation score. The digital promise rank is generated based on the final score of each digital promise.

Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: A method for processing an attempted payment made using a mobile device includes receiving information about the attempted payment, receiving data indicative of a behavior of a user of the mobile device at the time of the attempted payment, computing a likelihood that the attempted payment is fraudulent, based on a comparison of the behavior of the user to an historical behavior pattern of the user, and sending an instruction indicating how to proceed with the attempted payment, based on the likelihood.