Abstract: Techniques for computing a solution to a query formulated against a knowledge base (KB) are provided. The techniques include receiving a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto, ignoring each probability value of the one or more axioms and computing a solution to the query, computing each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution, and using each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution.

Abstract: Systems and techniques for generating recommendations for items likely to be of interest to a user. Upon an indication that a recommendation may be needed by a user, a plurality of recommendations from different sources are generated and combined. Suitably, each recommendation includes parameters such as accuracy and confidence parameters. Combining the recommendations comprises adjusting the parameters based on a set of rules established by an operator of a system for combining recommendations. The rules may be adjusted by operator inputs through an interface and may be adjusted, if desired, during generation of a recommendation. At least one of the recommendation sources generates recommendations based on social grouping, wherein social groupings are identified based on connections between members and similarity of purchased between members, and wherein a recommendation for a specific user is generated by identifying groups to which the user belongs and items popular within such groups.

Abstract: The invention includes various systems, architectures, frameworks and methodologies that can securely enforce a privacy policy. A method is included for securely guaranteeing a privacy policy between two enterprises, comprising: creating a message at a first enterprise, wherein the message includes a request for data concerning a third party and a privacy policy of the first enterprise; signing and certifying the message that the first enterprise has a tamper-proof system with a privacy rules engine and that the privacy policy of the first entity will be enforced by the privacy rules engine of the first enterprise; sending the message to a second enterprise; and running a privacy rules engine at the second enterprise to compare the privacy policy of the first enterprise with a set of privacy rules for the third party.

Abstract: The invention includes various systems, architectures, frameworks and methodologies that can securely enforce a privacy policy. A method is included for securely guaranteeing a privacy policy between two enterprises, comprising: creating a message at a first enterprise, wherein the message includes a request for data concerning a third party and a privacy policy of the first enterprise; signing and certifying the message that the first enterprise has a tamper-proof system with a privacy rules engine and that the privacy policy of the first entity will be enforced by the privacy rules engine of the first enterprise; sending the message to a second enterprise; and running a privacy rules engine at the second enterprise to compare the privacy policy of the first enterprise with a set of privacy rules for the third party.

Abstract: Techniques for computing a solution to a query formulated against a knowledge base (KB) are provided. The techniques include receiving a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto, ignoring each probability value of the one or more axioms and computing a solution to the query, computing each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution, and using each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution.

Abstract: An exemplary embodiment of the present invention includes a method to enforce privacy preferences on exchanges of personal data of a data-subject. The method comprises the steps of: specifying data-subject authorization rule sets having subject constraints, receiving a request message from a requester and a requester privacy statement, comparing the requester privacy statement to the subject constraints, and releasing the data-subject data in a response message to the requester only if the subject constraints are satisfied. The requester privacy statement includes purpose, retention, recipient, and access information, wherein the purpose information specifies the purpose for which the requested data is acquired, the retention information specifies a retention policy for the requested data, the recipient information specifies the recipients of the requested data, and the access information specifies whether the requested data should be accessing to the data-subject after the data has been released.

Abstract: The invention includes various systems, architectures, frameworks and methodologies that can securely enforce a privacy policy. A method is included for securely guaranteeing a privacy policy between two enterprises, comprising: creating a message at a first enterprise, wherein the message includes a request for data concerning a third party and a privacy policy of the first enterprise; signing and certifying the message that the first enterprise has a tamper-proof system with a privacy rules engine and that the privacy policy of the first entity will be enforced by the privacy rules engine of the first enterprise; sending the message to a second enterprise; and running a privacy rules engine at the second enterprise to compare the privacy policy of the first enterprise with a set of privacy rules for the third party.

Abstract: The invention includes various systems, architectures, frameworks and methodologies that can securely enforce a privacy policy. A method is include for securely guaranteeing a privacy policy between two enterprises, comprising: creating a message at a first enterprise, wherein the message includes a request for data concerning a third party and a privacy policy of the first enterprise; signing and certifying the message that the first enterprise has a tamper-proof system with a privacy rules engine and that the privacy policy of the first entity will be enforced by the privacy rules engine of the first enterprise; sending the message to a second enterprise; and running a privacy rules engine at the second enterprise to compare the privacy policy of the first enterprise with a set of privacy rules for the third party.

Abstract: The invention includes various systems, architectures, frameworks and methodologies that can securely enforce a privacy policy. A method is include for securely guaranteeing a privacy policy between two enterprises, comprising: creating a message at a first enterprise, wherein the message includes a request for data concerning a third party and a privacy policy of the first enterprise; signing and certifying the message that the first enterprise has a tamper-proof system with a privacy rules engine and that the privacy policy of the first entity will be enforced by the privacy rules engine of the first enterprise; sending the message to a second enterprise; and running a privacy rules engine at the second enterprise to compare the privacy policy of the first enterprise with a set of privacy rules for the third party.

Abstract: The invention includes various systems, architectures, frameworks and methodologies that can securely enforce a privacy policy. A method is include for securely guaranteeing a privacy policy between two enterprises, comprising: creating a message at a first enterprise, wherein the message includes a request for data concerning a third party and a privacy policy of the first enterprise; signing and certifying the message that the first enterprise has a tamper-proof system with a privacy rules engine and that the privacy policy of the first entity will be enforced by the privacy rules engine of the first enterprise; sending the message to a second enterprise; and running a privacy rules engine at the second enterprise to compare the privacy policy of the first enterprise with a set of privacy rules for the third party.

Abstract: The invention includes various systems, architectures, frameworks and methodologies that can securely enforce a privacy policy. A method is include for securely guaranteeing a privacy policy between two enterprises, comprising: creating a message at a first enterprise, wherein the message includes a request for data concerning a third party and a privacy policy of the first enterprise; signing and certifying the message that the first enterprise has a tamper-proof system with a privacy rules engine and that the privacy policy of the first entity will be enforced by the privacy rules engine of the first enterprise; sending the message to a second enterprise; and running a privacy rules engine at the second enterprise to compare the privacy policy of the first enterprise with a set of privacy rules for the third party.

Abstract: A system, method, and business method is used to enforce privacy preferences on exchanges of personal data over a computer network. There are one or more data-subject (subject) rule sets that have one or more subject constraints on one or more private, subject data releases. A receiving process receives a request message from a data-requester (requester) over a network interfaces. The request message has one or more requests for one or more of the private, subject data releases pertaining to a subject, and a requester privacy statement for each of the respective private data. A release process compares the requester privacy statement to the subject constraints (authorization rules) and releases the private, subject data release in a response message to the requester only if the subject constraints are satisfied.