Abstract: This invention relates generally to classification systems. More particularly this invention relates to a system, method, and computer program to dynamically generate a domain of information synthesized by a classification system or semantic network. The invention discloses a method, system, and computer program providing a means by which an information store comprised of knowledge representations, such as a web site comprised of a plurality of web pages or a database comprised of a plurality of data instances, may be optimally organized and accessed based on relational links between ideas defined by one or more thoughts identified by an agent and one or more ideas embodied by the data instances. Such means is hereinafter referred to as a “thought network”.

Abstract: This invention relates generally to classification systems. More particularly this invention relates to a system, method, and computer program to dynamically generate a domain of information synthesized by a classification system or semantic network. The invention discloses a method, system, and computer program providing a means by which an information store comprised of knowledge representations, such as a web site comprised of a plurality of web pages or a database comprised of a plurality of data instances, may be optimally organized and accessed based on relational links between ideas defined by one or more thoughts identified by an agent and one or more ideas embodied by the data instances. Such means is hereinafter referred to as a “thought network”.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Systems and methods for processing changes to travel itineraries are provided. A system can comprise a database, a scheduler, and an optimizer. The database stores travel itineraries, traveler preferences, and itinerary change parameters. The scheduler exchanges information with travel supply networks and is operable to receive a travel itinerary, receive related travel itineraries, and optionally search the database for the related travel itineraries. The optimizer is operable to evaluate travel itinerary change tolerance parameters associated with the travel itinerary based on the traveler preferences, the itinerary change parameters, and the related travel itineraries; generate an optimized set of itinerary change tolerance parameters based on the evaluated itinerary change tolerance parameters and an optimization goal; and store the optimized set of itinerary change tolerance parameters for updating the travel itinerary.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Various approaches for allocating resources to multiple virtual machines include identifying multiple reserved instances, each specifying a quantity of one or more computational resources compatible with the feasible resource template for the VMs; computationally generating, for each of the VMs, an instance-ranking list indicating a ranking order of the reserved instances having templates feasible for the VM; computationally generating, for each of the reserved instances, a VM-ranking list indicating a ranking order of the VMs to which the resources specified by the reserved instance may be allocated; and based at least in part on the instance-ranking list and the VM-ranking list, computationally mapping each of the VMs to one of the reserved instances.

Abstract: Disclosed is a system and method for enhancing value for advertisers by helping them select and initiate the purchase of an advertisement associated with an advertising (ad) words or phrases that have strong semantic relationships to a given context, but which are not necessarily the most popular ad words or phrases with the highest costs. Advertisements associated with ad words or phrases that have strong semantic relationships to a given context, and yet are still cost effective in that their calculated value exceeds the costs of purchasing the ad keywords, are bid for and bought. In an embodiment, the system and method may be adapted to automatically purchase advertisements associated with ad words or phrases when the ad words or phrases fall within a desired price range based on their calculated value.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Various approaches for allocating resources to multiple virtual machines include identifying multiple reserved instances, each specifying a quantity of one or more computational resources compatible with the feasible resource template for the VMs; computationally generating, for each of the VMs, an instance-ranking list indicating a ranking order of the reserved instances having templates feasible for the VM; computationally generating, for each of the reserved instances, a VM-ranking list indicating a ranking order of the VMs to which the resources specified by the reserved instance may be allocated; and based at least in part on the instance-ranking list and the VM-ranking list, computationally mapping each of the VMs to one of the reserved instances.

Abstract: Disclosed is a system and method for enhancing value for advertisers by helping them select and initiate the purchase of an advertisement associated with an advertising (ad) words or phrases that have strong semantic relationships to a given context, but which are not necessarily the most popular ad words or phrases with the highest costs. Advertisements associated with ad words or phrases that have strong semantic relationships to a given context, and yet are still cost effective in that their calculated value exceeds the costs of purchasing the ad keywords, are bid for and bought. In an embodiment, the system and method may be adapted to automatically purchase advertisements associated with ad words or phrases when the ad words or phrases fall within a desired price range based on their calculated value.

Abstract: There is disclosed a system and method for using a knowledge representation to provide relevant information based on environmental inputs. In an embodiment, the system and method considers environmental information from members in a crowd to generate a pool of interests based on the semantic relevance concepts associated with those interests. The most prominent concepts of interest may then be the basis for presenting content to the crowd as a whole. In another embodiment, environmental inputs and other surrounding inputs are considered as a user context. The concepts may be identified as relevant from the environmental context and used to present information relevant to the user given his or her surroundings.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing complex KRs from the elemental data structure may depend on user models, context information, preference information, and/or preference models.

Abstract: Disclosed is a system and method for performing a semantic operation on a social network. In an embodiment, the method comprises receiving a social network user context associated with a user of the social network; generating, through a semantic operation, an interest network based on the user context information; and filtering, ranking or augmenting, using at least one processor executing stored program instructions, a retrieval of information related to the social network based on the interest network; wherein the interest network comprises concepts represented by a data structure associated with the concepts in the interest network. In another embodiment, the method further comprises representing the interest network as an interest graph. In yet another embodiment, the semantic operation is a synthesis operation or retrieval operation performed on a knowledge representation.

Abstract: Techniques are described for performing synthesis of relationships between a plurality of concept definitions automatically derived from a faceted domain of information. Some embodiments involve identifying at least one facet attribute in an active concept definition specified by user input. In response to determining that at least one explicit relationship and/or at least one implicit relationship exist(s) between the active concept definition and a first concept definition of the plurality of concept definitions, a relationship is synthesized between the active concept definition and the first concept definition.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing complex KRs from the elemental data structure may depend on user models, context information, preference information, and/or preference models.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Computer-implemented systems find methods for synthesis of concept definitions and concept relationships from a domain of data, utilizing different semantic processing protocols such formal concept analysis and faceted classification synthesis from existing domain concepts that have a confidence gradient built into them. A cognitive or an input agent provides an input of an active concept which is matched against existing domain concepts. The resultant pool of relevant domain concepts is then used to derive virtual concept definitions using a semantic processing protocol. The derivation is then overlaid with a concept of relative proximity of an attribute from another within an attribute set. An additional layer of coherence is given by the relative proximity measure. The end result is a pool of related virtual concept definitions in a tree structure.

Abstract: Computer-implemented systems and methods for synthesis of concept definitions and concept relationships from a domain of data, utilizing different semantic processing protocols such as formal concept analysis and faceted classification synthesis from existing domain concepts that have a confidence gradient built into them. A cognitive or an input agent provides an input of an active concept which is matched against existing domain concepts. The resultant pool of relevant domain concepts is then used to derive virtual concept definitions using a semantic processing protocol. The derivation is then overlaid with a concept of relative proximity of an attribute from another within an attribute set. An additional layer of coherence is given by the relative proximity measure. The end result is a pool of related virtual concept definitions in a tree structure.