# US 2021/0240928 A1 · Mapping feedback to a process > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0240928 A1 - Document ID: US20210240928A1 - Status: Published application - Kind: A1 - Application number: 16/782,356 - Filed: 2020-02-05 - Published: 2021-08-05 - Earliest claimed: 2020-02-05 - Assignees: Sap SE - Applicants: Sap SE - Inventors: Vishal Sharma; Manu Sinha - Web page: https://patentgrep.com/patent/US20210240928A1 ## CPC - G06F 40/247: Thesauruses; Synonyms - G06F 16/22: Indexing; Data structures therefor; Storage structures - G06F 16/353: into predefined classes - G06F 40/279: Recognition of textual entities - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Provided are systems and methods for mapping customer feedback to one or more processes. In one example, the method may include receiving text content that includes feedback, mapping, via execution of a mapping algorithm, the text content to a plurality of processes based on a synonym graph, generating mapping values for the plurality of processes, where a mapping value for a process is generated based on distance within the synonym graph of a mapping between a word in the text content and a word identifying the process, an determining a process among the plurality of processes that is most correlated to the feedback based on the generated mapping values. ## Claims ### Claim 1 A computing system comprising: a network interface configured to receive text content that includes feedback; and a processor configured to: map, via execution of a mapping algorithm, the text content to a plurality of processes based on a synonym graph, generate mapping values for the plurality of processes, where a mapping value for a process is generated based on distance within the synonym graph of a mapping between a word in the text content and a word identifying the process, and determine a process among the plurality of processes that is most correlated to the feedback based on the generated mapping values. ### Claim 2 (depends on 1) The computing system of claim 1, wherein the processor is configured to identify a feedback keyword from the text content and an activity keyword from the process, and generate a path within the synonym graph between the feedback keyword to the activity keyword. ### Claim 3 (depends on 2) The computing system of claim 2, wherein the processor is configured to determine the mapping value for the process based on a number of nodes on the synonym graph between a node representing the feedback keyword and a node representing the activity keyword. ### Claim 4 (depends on 1) The computing system of claim 1, wherein the processor is further configured to retrieve, via an application programming interface, the feedback including the text content from a social networking site. ### Claim 5 (depends on 1) The computing system of claim 1, wherein the synonym graph comprises a plurality of nodes representing a plurality of words, and links between the plurality of nodes identify synonym relationships between the corresponding plurality of words. ### Claim 6 (depends on 1) The computing system of claim 1, wherein the processor is configured to respectively map a plurality keywords from the text content to the word identifying the process, within the synonym graph. ### Claim 7 (depends on 6) The computing system of claim 6, wherein the processor is configured to generate sub-values for each of the plurality of keywords based on distances within the synonym graph of mappings between the plurality of keywords and the word identifying the process, and combine the sub-values to generate a mapping value of the process. ### Claim 8 (depends on 1) The computing system of claim 1, wherein the processor is further configured to output, via a user interface, the text content, an identifier of a social networking site where the text content was extracted from, and the plurality of mapping values for the plurality of processes. ### Claim 9 A method comprising: receiving text content that includes feedback; mapping, via execution of a mapping algorithm, the text content to a plurality of processes based on a synonym graph; generating mapping values for the plurality of processes, where a mapping value for a process is generated based on distance within the synonym graph of a mapping between a word in the text content and a word identifying the process; and determining a process among the plurality of processes that is most correlated to the feedback based on the generated mapping values. ### Claim 10 (depends on 9) The method of claim 9, wherein the mapping comprises identifying a feedback keyword from the text content and an activity keyword from the process, and generating a path within the synonym graph between the feedback keyword to the activity keyword. ### Claim 11 (depends on 10) The method of claim 10, wherein the generating comprises determining the mapping value for the process based on a number of nodes on the synonym graph between a node representing the feedback keyword and a node representing the activity keyword. ### Claim 12 (depends on 9) The method of claim 9, further comprising retrieving, via an application programming interface, the feedback including the text content from a social networking site. ### Claim 13 (depends on 9) The method of claim 9, wherein the synonym graph comprises a plurality of nodes representing a plurality of words, and links between the plurality of nodes identify synonym relationships between the corresponding plurality of words. ### Claim 14 (depends on 9) The method of claim 9, wherein the mapping comprises respectively mapping a plurality keywords from the text content to the word identifying the process, within the synonym graph. ### Claim 15 (depends on 14) The method of claim 14, wherein the generating the mapping values comprises generating sub-values for each of the plurality of keywords based on distances within the synonym graph between mappings of the plurality of keywords and the word identifying the process, and combining the sub-values to generate a mapping value of the process. ### Claim 16 (depends on 9) The method of claim 9, further comprising outputting, via a user interface, the text content, an identifier of a social networking site where the text content was extracted from, and the plurality of mapping values for the plurality of processes. ### Claim 17 A non-transitory computer-readable medium comprising instructions which when executed by a processor cause a computer to perform a method comprising: receiving text content that includes feedback; mapping, via execution of a mapping algorithm, the text content to a plurality of processes based on a synonym graph; generating mapping values for the plurality of processes, where a mapping value for a process is generated based on distance within the synonym graph of a mapping between a word in the text content and a word identifying the process; and determining a process among the plurality of processes that is most correlated to the feedback based on the generated mapping values. ### Claim 18 (depends on 17) The non-transitory computer-readable medium of claim 17, wherein the mapping comprises identifying a feedback keyword from the text content and an activity keyword from the process, and generating a path within the synonym graph between the feedback keyword to the activity keyword. ### Claim 19 (depends on 18) The non-transitory computer-readable medium of claim 18, wherein the generating comprises determining the mapping value for the process based on a number of nodes on the synonym graph between a node representing the feedback keyword and a node representing the activity keyword. ### Claim 20 (depends on 17) The non-transitory computer-readable medium of claim 17, wherein the synonym graph comprises a plurality of nodes representing a plurality of words, and links between the plurality of nodes identify synonym relationships between the corresponding plurality of words.