# US 12,602,542 B2 · Text analysis system, and characteristic evaluation system for message exchange using the same > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,602,542 B2 - Document ID: US12602542B2 - Status: Granted - Kind: B2 - Application number: 18/189,819 - Filed: 2023-03-24 - Published: 2023-07-27 - Granted: 2026-04-14 - Earliest claimed: 2023-03-24 - Assignees: IMatrix Holdings Corp. - Applicants: IMatrix Holdings Corp. - Inventors: Hibiki Oka; Mitsuo Kojima; Akira Nakahashi - Web page: https://patentgrep.com/patent/US12602542B2 ## CPC - G06F 40/126: Character encoding - G06F 40/205: Parsing - G06F 16/3344: {using natural language analysis} - G06F 40/194: Calculation of difference between files - G06F 40/216: using statistical methods - G06F 40/226: Validation - G06F 40/30: Semantic analysis - G06F 21/50: Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Aspects of this disclosure provide a device, system, and method for analyzing text. In an embodiment, a system is configured to convert characters of the text into a numerical time series signal. The numerical time series signal includes a time series conversion of the characters in numerical format. The system is further configured to generate a waveform with extracted information from the numerical time series signal. The extracted information having features based on politeness in language, a quantifiable use of punctuations, a quantifiable use of conjunctions, use of idioms, or a combination thereof. The system is additionally configured to determine whether the text is written by a specific user based on an analysis of the waveform against a threshold. ## Claims ### Claim 1 A system for analyzing text, the system comprising: a converter circuit for converting characters of the text into a numerical time series signal, wherein the numerical time series signal comprises a time series conversion of the characters in numerical format; a feature extractor circuit for generating a waveform comprising extracted information from the numerical time series signal, wherein the extracted information comprises features based on politeness in language, a quantifiable use of conjunctions, use of idioms, or a combination thereof; a determination circuit for determining whether the text is written by a specific user based on an analysis of the waveform against a threshold; and a detector circuit for detecting anomalous text different from the extracted information based on a determination result from the determination circuit wherein the system is part of a message exchange system, wherein the text is part of a message communicated using the message exchange system, wherein the message exchange system is for halting transmission of the message in response to an anomaly being detected based on an analysis of the waveform against the threshold, and wherein the message exchange system generates a notification message to a user of the message exchange system in response to halting the transmission. ### Claim 2 (depends on 1) The system of claim 1, wherein the feature extractor circuit is for generating the waveform based on a trained neural network, wherein the trained neural network is trained using text previously written by the specific user. ### Claim 3 (depends on 1) The system of claim 1, wherein the system further comprises an acquisition circuit for acquiring the characters of the text. ### Claim 4 (depends on 1) The system of claim 1, wherein the converter circuit is for converting the characters of the text into the numerical time series signal based on a predetermined conversion table or using Unicode. ### Claim 5 (depends on 1) The system of claim 1, wherein the converter circuit is for attenuating a value of the numerical time series signal that is more than a set threshold to normalize the numerical time series signal. ### Claim 6 (depends on 1) The system of claim 1, wherein the feature extractor circuit is for encoding the extracted information using an auto-encoder, and wherein the feature extractor circuit learns to extract the extracted information using a neural network. ### Claim 7 (depends on 1) The system of claim 1, wherein the message exchange system is for determining whether to communicate the message based on the determination as to whether the message is written by the specific user. ### Claim 8 (depends on 1) The system of claim 1, wherein the extracted information further comprises features based on a quantifiable use of punctuations. ### Claim 9 (depends on 1) The system of claim 1, wherein the converter circuit is configured to normalize the numerical time series signal within a range between 0 and 1, inclusive. ### Claim 10 A method for analyzing text, the method comprising: converting characters of the text into a numerical time series signal, wherein the numerical time series signal comprises a time series conversion of the characters in numerical format; generating a waveform comprising extracted information from the numerical time series signal, wherein the extracted information comprises features based on politeness in language, a quantifiable use of conjunctions, use of idioms, or a combination thereof; determining whether the text is written by a specific user based on an analysis of the waveform against a threshold; and detecting anomalous text different from the extracted information based on the determination result, wherein the method is for a message exchange system, wherein the text is part of a message communicated using the message exchange system, wherein the message exchange system is for halting transmission of the message in response to an anomaly being detected based on an analysis of the waveform against the threshold, and wherein the method further comprises generating a notification message to a user of the message exchange system in response to halting the transmission. ### Claim 11 (depends on 10) The method of claim 10, further comprising converting the characters of the text into the numerical time series signal based on a predetermined conversion table or using Unicode. ### Claim 12 (depends on 10) The method of claim 10, wherein the extracted information further comprises features based on a quantifiable use of punctuations. ### Claim 13 (depends on 10) The method of claim 10, further comprising encoding the extracted information using an auto-encoder, and wherein extracting the extracted information is performed using a neural network. ### Claim 14 A device for analyzing text, the device comprising: a non-transitory memory storage comprising instructions; and a processor in communication with the non-transitory memory storage, the instructions, when executed by the processor, cause the processor to: convert characters of the text into a numerical time series signal, wherein the numerical time series signal comprises a time series conversion of the characters in numerical format, generate a waveform comprising extracted information from the numerical time series signal, wherein the extracted information comprises features based on politeness in language, a quantifiable use of punctuations, a quantifiable use of conjunctions, and use of idioms, and determine whether the text is written by a specific user based on an analysis of the waveform against a threshold; and detect anomalous text different from the extracted information based on the determination result, wherein the device is part of a message exchange system, wherein the text is part of a message communicated using the message exchange system, wherein the message exchange system is for halting transmission of the message in response to an anomaly being detected based on an analysis of the waveform against the threshold, and wherein the instructions, when executed by the processor, cause the processor to generate a notification message to a user of the message exchange system in response to halting the transmission. ### Claim 15 (depends on 14) The device of claim 14, wherein the instructions, when executed by the processor, cause the processor to convert the characters of the text into the numerical time series signal based on a predetermined conversion table or using Unicode. ### Claim 16 (depends on 14) The device of claim 14, wherein the extracting of the information is performed by a neural network trained on previous texts generated by the specific user. ### Claim 17 (depends on 14) The device of claim 14, wherein the instructions, when executed by the processor, cause the processor to: detect an anomaly in the text based on a threshold difference in the features of a typical text written by the specific user and the text under analysis, wherein the detection is based on a learning model of a neural network trained using a plurality of previously written text by the specific user; and halt the transmission of the text under analysis based on the detection of an anomaly. ### Claim 18 (depends on 14) The device of claim 14, wherein the waveform includes a classification of the extracted information, and wherein the analysis of the waveform corresponds to an analysis of the waveform to a threshold set using a plurality of previously written text by the specific user. ### Claim 19 (depends on 14) The device of claim 14, wherein the threshold is determined based on a second waveform generated using a plurality of previously written text by the specific user. ### Claim 20 (depends on 14) The device of claim 14, wherein the message exchange system is configured to determine whether to communicate the message based on the determination as to whether the message is written by the specific user.