Abstract:
Mechanisms are provided for generating a dictionary data structure for analytical operations. A source terminology resource is ingested to generate a hierarchical representation of the source terminology resource comprising nodes for terms related to concepts in the source terminology resource. For a node of the nodes in the hierarchical representation of the source terminology resource, a permutation of a corresponding term associated with the node is generated. An expanded hierarchical representation of the source terminology resource is generated based on the generated permutation. An enhanced dictionary data structure is generated based on the expanded hierarchical representation and output to an analytics engine to perform analysis of a corpus of information using the enhanced dictionary data structure.
Abstract:
A data processing system includes an on-line, interactive, intelligent help system which provides suggestions as to actions a user can take after entry into the system of an erroneous command or a question. The system also responds with explanations of why the suggestions were made and how they work. The system includes a natural language analyzer for converting the questions into goals. A knowledge base and an inference engine further analyze the goals and provide one or more suggestions on how to achieve such goals. An explanation generator uses such analysis to dynamically generate the explanations which are tailored to the user's goal.
Abstract:
Topically relevant objects in an object database are first identified using any generally known methods to obtain a set of topically relevant objects (topically relevant set). Parents, and in alternative embodiments other ancestors, of one or more of the topically relevant objects are identified according to directional structural relationships that the parents have with respect to the topically relevant objects. These objects form a set of structurally relevant objects (structurally relevant set). In some embodiments, the user query identifies one or more of these structural relationships. The topically relevant objects are then organized under one or more of their respective parents to form a hierarchy level of both (topically relevant and structurally relevant) sets of objects. In some preferred embodiments, the process can iterate to create more than one hierarchy level.
Abstract:
Topically relevant objects in an object database are first identified using any generally known methods to obtain a set of topically relevant objects (topically relevant set). Parents, and in alternative embodiments other ancestors, of one or more of the topically relevant objects are identified according to directional structural relationships that the parents have with respect to the topically relevant objects. These objects form a set of structurally relevant objects (structurally relevant set). In some embodiments, the user query identifies one or more of these structural relationships. The topically relevant objects are then organized under one or more of their respective parents to form a hierarchy level of both (topically relevant and structurally relevant) sets of objects. In some preferred embodiments, the process can iterate to create more than one hierarchy level.
Abstract:
A data processing system includes an on-line, interactive, intelligent help system which provides suggestions as to actions a user can take after entry into the system of an erroneous command or a question. The system also responds with explanations of why the suggestions were made and how they work. The system includes a natural language analyzer for converting the questions into goals. A knowledge base and an inference engine further analyze the goals and provide one or more suggestions on how to achieve such goals. An explanation generator uses such analysis to dynamically generate the explanations which are tailored to the user's goal.