International Business Machines Corporation

Ju Y Lee

Feng-wei Chen

Nikhil R Parekh

Margaret H Mago

William Donald Reed

Clyde Lee Cain, Jr

John M Holtman

William R Reed

Embodiments of the present invention provide a novel and non-obvious method, server and computer program product for finding relevant content in a knowledge base. A method for finding items that are related to a user selected item in a knowledge base is provided. The method can include generating a first list of knowledge base items with a defined relationship to the user selected item and generating a second list of knowledge base items that belong to the same category as a category of the user selected item. The method can further include generating a third list of knowledge base items having one or more tags identical to one or more tags of the user selected item and selecting a first set of knowledge base items that are present in the first, second or third lists. The method can further include displaying the first set of knowledge base items as most relevant.

Relevance content searching for knowledge bases

One aspect of the present invention includes dynamically selecting templates through the use of an ontology. In one embodiment, an ontology is defined to structure information system content, and an ontology classification is then assigned when content is provided to the information system. Based on this classification, the most appropriate template classified in the ontology is applied to the content. If a template exists at the content item's ontology level, this template is applied to the content. If no template exists, then the ontology tree is navigated upward to locate a template at the nearest ancestor ontology level. If a template was found by navigating the ontology tree, then this template is applied to the content item.

Dynamic ontology-driven template selection

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Durham, NC, United States of America

Ju Y Lee