Abstract: This invention relates to Tribal Abstraction Networks (TAN), a new type of Abstraction Network designed for hierarchies that do not have attribute relationships, assuming only the existence of multiple parents. A Tribal Association network can summarize the content and structure of terminology hierarchies and support their Quality Assurance (QA) by identifying concepts with a higher likelihood of incorrect or missing IS-A relationships.

Abstract: Methods and apparatus for providing suggested completions to search results are disclosed which employ locating nodes in a stored ontology, wherein nodes consist of classes or instances of information, that correspond to the at least one search term, retrieving neighbors of located nodes in the stored ontology, and generating suggested completions in a format which separates homonymic terms. Methods and apparatus are disclosed for building ontologies and dynamically expanding ontologies.

Abstract: A disjoint partial-area taxonomy abstraction network and methods of producing same for a hierarchy, which partitions overlapping concepts into singly-rooted disjoint groups that are more manageable to work with and comprehend. This provides abstract models for summarizing overlapping concepts which permit enhanced, high-level display for users at a user interface.

Abstract: Methods and apparatus for providing suggested completions to search results are disclosed which employ locating nodes in a stored ontology, wherein nodes consist of classes or instances of information, that correspond to the at least one search term, retrieving neighbors of located nodes in the stored ontology, and generating suggested completions in a format which separates homonymic terms. Methods and apparatus are disclosed for building ontologies and dynamically expanding ontologies.

Abstract: Techniques are described that generally relate to systems, methods, and devices designed to facilitate the auditing of ontologies. Example methods may be designed so that the neighborhood concepts for a selected focus concept may be automatically displayed in a hybrid display that efficiently uses display area, while the concepts may be generally presented in an easy-to-comprehend format.

Abstract: A disjoint partial-area taxonomy abstraction network and methods of producing same for a hierarchy, which partitions overlapping concepts into singly-rooted disjoint groups that are more manageable to work with and comprehend. This provides abstract models for summarizing overlapping concepts which permit enhanced, high-level display for users at a user interface.

Abstract: Methods and apparatus for providing suggested completions to search results are disclosed which employ locating nodes in a stored ontology, wherein nodes consist of classes or instances of information, that correspond to the at least one search term, retrieving neighbors of located nodes in the stored ontology, and generating suggested completions in a format which separates homonymic terms. Methods and apparatus are disclosed for building ontologies and dynamically expanding ontologies.

Abstract: Techniques are described that generally relate to systems, methods, and devices designed to facilitate the auditing of ontologies. Example methods may be designed so that the neighborhood concepts for a selected focus concept may be automatically displayed in a hybrid display that efficiently uses display area, while the concepts may be generally presented in an easy-to-comprehend format.

Abstract: An intersection ontology may comprise a root node, representing an entire data set, and a second “layer” of nodes, groups of which may be used to represent different types of classifications of the data set. The intersection ontology may then contain one or more layers of nodes that may be represented by intersections of two or more of the second-layer nodes, as may be needed according to a desired application (that is, the intersections may be formed, essentially, on demand). There may be a single layer of intersection nodes, or there may be multiple layers of intersection nodes. In a multiple layer embodiment, each intersection node may be represented as an intersection of second-layer nodes and/or intersection nodes.

Abstract: An intersection ontology may comprise a root node, representing an entire data set, and a second “layer” of nodes, groups of which may be used to represent different types of classifications of the data set. The intersection ontology may then contain one or more layers of nodes that may be represented by intersections of two or more of the second-layer nodes, as may be needed according to a desired application (that is, the intersections may be formed, essentially, on demand). There may be a single layer of intersection nodes, or there may be multiple layers of intersection nodes. In a multiple layer embodiment, each intersection node may be represented as an intersection of second-layer nodes and/or intersection nodes.