International Business Machines Corporation

Daniel Weber

Nathaniel E Rykal

David Alan Christenson

William Craig Rapp

A computer system includes a natural language processing (NLP) unit, a storage unit, a user interface and a search engine. The NLP unit analyzes a content source to identify one or more sections containing searchable content and generate section metadata respective to each identified section included in the content source. The storage unit stores the section metadata and the user interface receives a section-scoped query aimed at searching an identified section corresponding to the at least one first section metadata stored in the storage unit without searching an identified section corresponding to at least one second section metadata stored in the storage unit. Based on the section-scoped query, the search engine analyzes the at least one first section metadata stored in the storage unit without analyzing the at least one second section metadata.

Selectively targeting content section for cognitive analytics and search

A mechanism is provided in a data processing system to implement a medical concept searching engine for improving searches of medical concepts based on an index model. The mechanism generates a concept index model data structure that records medical concepts and corresponding numbers of instances of the medical concepts in the corpus of documents. Responsive to receiving a search request from a user, the medical concept searching engine identifies at least one medical concept in the search request and one or more related medical concepts that are related to the at least one medical concept based on an ontology data structure. The medical concept searching engine generates a bubble graph user interface comprising a plurality of bubbles corresponding to the at least one medical concept and the one or more related medical concepts.

Learning interpretable strategies in the presence of existing domain knowledge

A mechanism is provided to implement an analytic inference engine for inferring cognitive capabilities across multiple cognitive analytics applied to literature. The analytic inference engine receives cognitive analytic output generated by multiple cognitive analytics applied to a portion of content. Response to the analytic inference engine finding a first offset in a first cognitive analytic output matching a second offset in a second cognitive analytic output, the analytic inference engine identifies unique features in the first cognitive analytic output and the second cognitive analytic output with respect to the matching offset. The analytic inference engine generates a composite analytic output comprising the unique features with respect to the matching offset.

Inferring cognitive capabilities across multiple cognitive analytics applied to literature

An automated concept-based autosuggest mechanism is provided for automatically tailoring autosuggestions in a search engine to particular medical concepts being searched. The mechanism identifies a concept-based text pattern dictionary data structure associated with text being dynamically entered by a user based on a previously identified item. The mechanism dynamically matches a set of text patterns in the concept-based text pattern dictionary data structure with a portion of text being dynamically entered by the user into a field of the user interface. The mechanism generates a user selectable output in the user interface specifying the matching set of text patterns from the concept-based text pattern dictionary data structure. The mechanism automatically populates the field of the user interface with a selected text pattern from the set of matching text patterns in response to user selection of the selectable text patter in the user selectable output in the user interface.

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Oronoco, MN, United States of America

Daniel Weber