Bmc Software, Inc.

Sun Chun Chu

Troy Cline

Nilesh Avinash Phadke

Thomas L Adrian

Cedric Young

Jonathan William Hall

Mark G Thompson

Steve Wong

Artemios Tavoularis

Jek-Sun Wong

Sameer Mardhekar

Dinesh Elaprolu

Peter Adams

Brian Zaik

Jek Wong

Described is a method for work assignment queue elimination. The method includes maintaining at least one data structure including an ordered list of ticket assignment rules and assignment result metrics, receiving a ticket indicating a system problem, assigning the ticket based on the ordered list of ticket assignment rules, the system problem and the assignment result metrics, collecting metrics based on the ticket assignment, and revising the assignment result metrics based on the collected metrics.

Work assignment queue elimination

A view generator receives support text characterizing a support requirement for available information technology (IT) support, the support text being received in sentence form via a graphical user interface (GUI). A text analyzer performs natural language processing on the support text and thereby identifies at least one sentence part and at least one named entity within the support text. A support record generator relates each of the at least one sentence part and the at least one named entity to a support record type, and generates a support data record for the support requirement, including filling individual fields of the support data record using the at least one sentence part and the at least one named entity.

Generation of support data records using natural language processing

In a general aspect, a system can include a user interface with at least one input field for receiving input associated with an information technology (IT) customer service issue and a response area for displaying results in response to the input. The system can further include a context generation engine that receives the input associated with the IT customer service issue from the user interface and determines, based on the input, a multi-factor context. The system can also include a relevance-based search engine configured to search, based on the multi-factor context, a plurality of resources; assign, based on the multi-factor context, a respective relevancy score to each of the plurality of resources; and provide, to the user interface for display in the results area, a ranked list of a subset of the plurality of resources that is ordered based on the respective relevancy scores of the subset of the resources.

Using multi-factor context for resolving customer service issues

Growing community of inventors

Richmond Hill, Canada

Sun Chun Chu