# US 2021/0240774 A1 · System and method for prioritization of support requests > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0240774 A1 - Document ID: US20210240774A1 - Status: Published application - Kind: A1 - Application number: 16/778,013 - Filed: 2020-01-31 - Published: 2021-08-05 - Earliest claimed: 2020-01-31 - Assignees: Dell Products L. P. - Applicants: Dell Products L. P. - Inventors: Sathish Kumar Bikumala; Marcio Fragoso Stumpf Lena; Deepak Nagarajegowda - Web page: https://patentgrep.com/patent/US20210240774A1 ## CPC - G06F 16/90332: {Natural language query formulation or dialogue systems} - G06F 9/453: {Help systems} - G06N 3/0442: characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - G06N 20/00: Machine learning - H04L 41/16: using machine learning or artificial intelligence - H04L 41/5074: Handling of user complaints or trouble tickets - G06N 3/044: Recurrent networks, e.g. Hopfield networks - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract Methods, information handling systems and computer readable media are disclosed for determining a priority score for a pending support request document. According to one embodiment, a method includes receiving current support request information from within a pending support request document and accessing current additional information associated with the pending support request document. The method further includes associating a set of parameter values with the pending support request document, wherein the values within the set of parameter values are based on information within one or both of the current support request information or the current additional information. The method continues with determining a priority score corresponding to the set of parameter values, where determining the priority score comprises applying a machine learning model developed using previous support request information and previous additional information associated with previously-resolved support request documents, and assigning the priority score to the pending support request document. ## Claims ### Claim 1 A method, comprising receiving current support request information, where the current support request information is contained within a pending support request document; accessing current additional information associated with the pending support request document; associating a set of parameter values with the pending support request document, wherein the parameter values in the set of parameter values are based on information within one or both of the current support request information or the current additional information; determining a priority score corresponding to the set of parameter values, wherein determining the priority score comprises applying a machine learning model developed using previous support request information and previous additional information associated with previously-resolved support request documents; and assigning the priority score to the pending support request document. ### Claim 2 (depends on 1) The method of claim 1, further comprising: comparing the priority score to additional priority scores assigned to respective additional pending support request documents; based on a result of the comparing, establishing a priority sequence for response to the pending support request document and the additional pending support request documents; and sending the pending support request document and the additional pending support request documents to one or more client information handling systems for response, according to the priority sequence. ### Claim 3 (depends on 1) The method of claim 1, wherein the set of parameter values comprises a hybrid parameter value; and associating the set of parameter values comprises accessing results of a clustering algorithm to obtain the hybrid parameter value. ### Claim 4 (depends on 1) The method of claim 1, wherein the set of parameter values comprises a sentiment value for the pending support request document; and associating the set of parameter values comprises applying natural language processing to a text string within the pending support request document. ### Claim 5 (depends on 4) The method of claim 4, wherein associating the set of parameter values further comprises applying a machine learning classification model to a result of the natural language processing. ### Claim 6 (depends on 1) The method of claim 1, wherein the machine learning model comprises a neural network. ### Claim 7 (depends on 1) The method of claim 1, wherein the current additional information comprises information retrieved from one or more data stores during an update of the machine learning model. ### Claim 8 An information handling system, comprising: one or more processors; one or more non-transitory computer-readable storage media coupled to the one or more processors; and a plurality of instructions, encoded in the one or more computer-readable storage media and configured to cause the one or more processors to receive current support request information, where the current support request information is contained within a pending support request document; access current additional information associated with the pending support request document; associate a set of parameter values with the pending support request document, wherein the parameter values in the set of parameter values are based on information within one or both of the current support request information or the current additional information; determine a priority score corresponding to the set of parameter values, including applying a machine learning model developed using previous support request information and previous additional information associated with previously-resolved support request documents; and assign the priority score to the support request document. ### Claim 9 (depends on 8) The information handling system of claim 8, wherein the plurality of instructions is further configured to cause the one or more processors to: compare the priority score to additional priority scores assigned to respective additional pending support request documents; based on a result of the comparing, establish a priority sequence for response to the pending support request document and the additional pending support request documents; and send the pending support request document and the additional pending support request documents to one or more client information handling systems for response, according to the priority sequence. ### Claim 10 (depends on 8) The information handling system of claim 8, wherein the set of parameter values comprises a hybrid parameter value; and the plurality of instructions is further configured to cause the one or more processors to access results of a clustering algorithm to obtain the hybrid parameter value, as a part of associating the set of parameter values with the pending support request document. ### Claim 11 (depends on 8) The information handling system of claim 8, wherein the set of parameter values comprises a sentiment value for the pending support request document; and the plurality of instructions is further configured to cause the one or more processors to apply natural language processing to a text string within the pending support request document, as a part of associating the set of parameter values with the pending support request document. ### Claim 12 (depends on 11) The information handling system of claim 11, wherein the plurality of instructions is further configured to cause the one or more processors to apply a machine learning classification model to a result of the natural language processing, as a part of associating the set of parameter values with the pending support request document. ### Claim 13 (depends on 8) The information handling system of claim 8, wherein the machine learning model comprises a neural network. ### Claim 14 (depends on 8) The information handling system of claim 8, wherein the current additional information comprises information retrieved from one or more data stores during an update of the machine learning model. ### Claim 15 A non-transitory computer readable storage medium having program instructions encoded therein, wherein the program instructions are executable to: receive current support request information, where the current support request information is contained within a pending support request document; access current additional information associated with the pending support request document; associate a set of parameter values with the pending support request document, wherein the parameter values in the set of parameter values are based on information within one or both of the current support request information or the current additional information; determine a priority score corresponding to the set of parameter values, including applying a machine learning model developed using previous support request information and previous additional information associated with previously-resolved support request documents; and assign the priority score to the support request document. ### Claim 16 (depends on 15) The computer readable storage medium of claim 15, wherein the program instructions are further executable to: compare the priority score to additional priority scores assigned to respective additional pending support request documents; based on a result of the comparing, establish a priority sequence for response to the pending support request document and the additional pending support request documents; and send the pending support request document and the additional pending support request documents to one or more client information handling systems for response, according to the priority sequence. ### Claim 17 (depends on 15) The computer readable storage medium of claim 15, wherein the set of parameter values comprises a hybrid parameter value; and the instructions are further executable to access results of a clustering algorithm to obtain the hybrid parameter value, as a part of associating the set of parameter values with the pending support request document. ### Claim 18 (depends on 15) The computer readable storage medium of claim 15, wherein the set of parameter values comprises a sentiment value for the pending support request document; and the instructions are further executable to apply natural language processing to a text string within the pending support request document, as a part of associating the set of parameter values with the pending support request document. ### Claim 19 (depends on 15) The computer readable storage medium of claim 15, wherein the program instructions are further executable to apply a machine learning classification model to a result of the natural language processing, as a part of associating the set of parameter values with the pending support request document. ### Claim 20 (depends on 15) The computer readable storage medium of claim 15, wherein the current additional information comprises information retrieved from one or more data stores during an update of the machine learning model.