CN115334024A - Instant response system and instant response method - Google Patents
Instant response system and instant response method Download PDFInfo
- Publication number
- CN115334024A CN115334024A CN202210915647.1A CN202210915647A CN115334024A CN 115334024 A CN115334024 A CN 115334024A CN 202210915647 A CN202210915647 A CN 202210915647A CN 115334024 A CN115334024 A CN 115334024A
- Authority
- CN
- China
- Prior art keywords
- module
- data
- difference value
- estimation module
- response
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000004044 response Effects 0.000 title claims abstract description 95
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000007405 data analysis Methods 0.000 claims abstract description 43
- 238000003860 storage Methods 0.000 claims abstract description 14
- 238000011010 flushing procedure Methods 0.000 claims description 26
- 238000009825 accumulation Methods 0.000 claims description 16
- 238000012502 risk assessment Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 description 16
- 238000009826 distribution Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 230000001360 synchronised effect Effects 0.000 description 5
- 230000008901 benefit Effects 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000011156 evaluation Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/04—Real-time or near real-time messaging, e.g. instant messaging [IM]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/22—Parsing or analysis of headers
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computer Security & Cryptography (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Acyclic And Carbocyclic Compounds In Medicinal Compositions (AREA)
- Debugging And Monitoring (AREA)
- Hardware Redundancy (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides an instant response system and an instant response method. The instant response system comprises a storage device and a processor. The storage device stores a response module, a data analysis module, a risk estimation module, and a resource estimation module. The processor executes the data analysis module, so that the data analysis module performs data analysis on the request data and obtains characteristic data. The data analysis module generates return data according to the characteristic data and the initial data template, and inputs the return data to the response module and the risk estimation module. The processor executes the response module to output the return data. The processor executes the risk estimation module to calculate a difference value according to the request data and the return data. The instant response system of the invention adjusts the initial data template or the next returned data according to the difference value.
Description
Technical Field
The present invention relates to a service quick response technology, and more particularly, to an instant response system and an instant response method.
Background
In a communication mode in a network environment, there are a requester (client, device) of data and a provider (server) of data to perform data processing of data or request instructions. The data processing/data transmission is performed through the communication architecture of synchronous processing, and the data provider must wait for the completion of the complete data operation to perform the data return or subsequent processing, which increases the time of the whole process and may cause the occurrence of time-out and process interruption due to the fact that the set time of the data request end is exceeded when the data is returned.
Disclosure of Invention
The invention aims at an instant response system and an instant response method, which can quickly and automatically respond to the information of request data and output return data.
According to an embodiment of the present invention, an instant response system of the present invention includes a storage device and a processor. The storage device stores a plurality of modules, the plurality of modules including: the system comprises a response module, a data analysis module, a risk estimation module and a resource estimation module. The processor is coupled to the storage device. The processor executes the data analysis module to cause the data analysis module to perform data analysis on the request data and to retrieve the characteristic data. The data analysis module generates return data according to the characteristic data and the initial data template, and inputs the return data to the response module and the risk estimation module. The processor executes the response module to output the return data. The processor executes the risk estimation module to calculate a difference value according to the request data and the returned data based on a logic rule, and when the processor judges that the difference value is larger than a threshold value, the processor executes the resource estimation module to adjust the initial data template according to the difference value.
According to an embodiment of the present invention, the instant response method of the present invention includes the steps of: through the data analysis module, the data analysis module performs data analysis on the request data and obtains characteristic data; and generating return data according to the characteristic data and the initial data template through a data analysis module, and outputting the return data through a response module. And calculating a difference value according to the request data and the return data through a risk estimation module, and adjusting the initial data template/the next return data according to the difference value.
Based on the above, the instant response system and the instant response method of the present invention can automatically analyze the request data to automatically determine whether the request data conforms to the default value, and correspondingly adjust the initial data template/the next returned data according to the difference value, so as to maintain the instant response system with a small number of interfaces and achieve instant response at the same time
In order to make the aforementioned and other features and advantages of the invention more comprehensible, embodiments accompanied with figures are described in detail below.
Drawings
FIG. 1 is a schematic diagram of an instant response system in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of an instant response method of an embodiment of the present invention;
FIG. 3 is a schematic diagram of a plurality of modules of an embodiment of the present invention.
Description of the reference numerals
100: an instant response system;
110: a processor;
120: a storage device;
121: a response module;
122: a data analysis module;
123: a risk estimation module;
124: a resource estimation module;
125: a difference accumulation module;
126: a back flushing module;
s210 to S240: and (5) carrying out the following steps.
Detailed Description
Reference will now be made in detail to exemplary embodiments of the invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the description to refer to the same or like parts.
Fig. 1 is a schematic diagram of an instant response system according to an embodiment of the present invention. Referring to fig. 1, the instant response system 100 includes a processor 110 and a storage device 120. The processor 110 is coupled to a storage device 120. Storage 120 may store a plurality of modules. In this embodiment, the plurality of modules includes a response module 121, a data analysis module 122, a risk estimation module 123, and a resource estimation module 124. Processor 110 may access storage 120 to execute response module 121, data analysis module 122, risk assessment module 123, and resource assessment module 124. In another embodiment, the plurality of modules further includes a difference accumulation module and a back flushing module. In one embodiment, the processor 110 may also be coupled to an external or internal database to read/write data templates, standard templates, judgment templates and initial data in the database. In another embodiment, a human may enter or be automatically read by the processor 110 from a pre-stored initial data template. Next, the instant response system 100 may further include a transceiver to receive/transmit the request data transmitted by the device side/data request side. The data analysis module 122 may perform data analysis on the requested data to generate feature data. The data analysis module 122 generates the feedback data according to the feature data in the request data and the initial data template, and inputs the feedback data to the response module 121. Then, the response module 121 outputs the returned data to the sender of the requested data or the receiver of the next process. In the present invention, the risk estimation module 123 can calculate the difference between the returned data and the operation result according to the request data and the returned data based on the logic rule. It should be noted that the instant response system 100 of the present invention can adjust the initial data template/the next returned data according to the difference value. Specifically, when the difference value is greater than the threshold value, the risk estimation module 123 activates/triggers the resource estimation module 124, so that the resource estimation module 124 adjusts the initial data template according to the difference value. When the difference value is less than or equal to the threshold, the risk estimation module 123 inputs the difference value to the back-flushing module, so that the back-flushing module accumulates the difference value in the difference accumulation module and adjusts the next returned data according to the difference value. Thus, the instant response system 100 of the present invention can respond to the request data of the device end in real time, and adjust the subsequent/next returned data according to the difference between the returned data outputted by the instant response system 100 and the operation result, so as to have the advantages of data synchronous processing and data asynchronous processing.
In the present embodiment, the Processor 110 may include, for example, a Central Processing Unit (CPU), or other Programmable general purpose or special purpose Microprocessor (Microprocessor), digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), programmable Logic Device (PLD), other similar Processing Circuits, or a combination thereof. The storage device 120 may include a Memory (Memory) and/or a database (database), wherein the Memory may be, for example, a Non-Volatile Memory (NVM). The storage device 120 may store the relevant programs, modules, systems or algorithms for implementing the embodiments of the present invention, so as to be accessed and executed by the processor 110 to implement the relevant functions and operations described in the embodiments of the present invention. In the embodiment, the response module 121, the data analysis module 122, the risk estimation module 123, the resource estimation module 124, the variance accumulation module, and the rollback module may be implemented in a program Language such as JSON (JavaScript Object notification), extensible Markup Language (XML), YAML, or the like, but the invention is not limited thereto. In the embodiment, the instant response system 100 may be implemented in a Personal Computer (PC), a Server (Server), or a cloud Server, but the invention is not limited thereto. In one embodiment, the instant response system 100 may also be integrated into an Enterprise Resource Planning (ERP) system to provide real-time and automatic request response service.
Fig. 2 is a flowchart of an instant response method according to an embodiment of the present invention. Referring to fig. 1 and fig. 2, the immediate response system 100 of the present embodiment may perform the following steps S210 to S240 to output the returned data in response to the request data. In this embodiment, the processor 110 may execute the response module 121, the data analysis module 122, the risk estimation module 123, and the resource estimation module 124. The processor 110 receives the request data and performs step S210. In step S210, the data analysis module 122 performs data analysis on the request data to obtain feature data/feature values.
For example, the feature data may be data related to a number of a requested item, a factory number of a requested data output terminal, and/or a requested quantity in the request data. Then, the data analysis module 122 generates the feedback data according to the feature data and the initial data template, and outputs the feedback data through the response module 121. The initial data template may be a default data parameter table for a user or system. In one embodiment, the initial data template records the data of the factory, the project, the material number and the quantity of each request. Thus, the data analysis module 122 generates the returned data according to the normal distribution or the default allowable value according to the data of the feature data corresponding to the requested data in the initial data template. For example, if the requested amount of data for a specific material is 48 (feature data), and the corresponding amount in the initial data template is 50 and the predetermined tolerance is 5%, the data analysis module 122 uses the requested amount of data 48 as the return data. Then, the data analysis module 122 inputs the returned data to the response module 121. The processor 110 executes the response module 121 to output the return data. In one embodiment, the response module 121 outputs the returned data to the external corresponding receiving port. For example, plant A issues a material request to the instant response system 100. The instant response system 100 then generates a return transmission based on the initial data template and the requested data. Moreover, according to the characteristic data of the material request, the data analysis module 122 of the instant response system 100 may analyze that the returned data is to be returned to the original a factory or another receiving end.
The data analysis module 122 inputs the returned data and the requested data into the risk estimation module 123. Next, the processor 110 executes step S230. In step S230, the risk estimation module 123 calculates a difference value according to the request data and the feedback data. Specifically, the risk estimation module 123 may calculate the difference value by performing operations on the request data and the returned data based on logic rules. The logic rules may be, for example, actual inventory quantities of materials, actual project flows, historical flow data, quantity of items required or yield values of each plant, etc. more real-time and detailed related data and default judgment rules. For example, if the returned data generated by comparing the initial data templates is 50 materials a, the risk estimation module 123 compares the corresponding logic rules, and then the factory yield value corresponding to the requested data is generated as the operation result. For example, since the factory yield is 9, the calculation result is 55 pieces of material a. Thus, the difference value was 5 materials a. Then, the processor 110 adjusts the initial data template/next returned data according to the difference value. Specifically, the risk estimation module 123 compares the difference value with a preset threshold to adjust the initial data template or the next returned data. When the FENG \38570. As such, the instant response system 100 of the present embodiment can efficiently and real-timely respond to the service request, and adjust the subsequent returned data according to the detailed operation result to ensure the correctness of the data.
FIG. 3 is a schematic diagram of a plurality of modules of an embodiment of the present invention. Referring to fig. 1 and fig. 3, in the present embodiment, the modules further include a difference accumulation module 125 and a back flushing module 126. When the risk evaluation module 123 determines that the difference value is less than or equal to the threshold value, the processor 110 executes the risk evaluation module 123 to input the difference value to the back flushing module 126. For example, if the difference is 5 and the threshold is preset to 10, the risk estimation module 123 inputs the difference of 5 to the back flushing module 126. Then, the back flushing module 126 inputs the difference value to the difference accumulation module 125, so that the difference accumulation module 125 accumulates the difference value 5 of this time and the subsequently received difference value to obtain the current total difference value.
In the present invention, when the current total difference value is greater than the difference threshold, the difference accumulation module 125 inputs the current total difference value to the resource estimation module 124, so that the resource estimation module 124 adjusts the initial data template according to the current total difference value. For example, if the user presets the difference threshold to be 20, when the current total difference value is accumulated to be above 21, the difference accumulation module 125 inputs the current total difference value 21 to the resource estimation module 124, so that the resource estimation module 124 adjusts the initial data template according to the current total difference value 21. In this example, adjusting the initial data template may be, for example, the resource estimation module 124 subtracting the current total difference value 21 from the corresponding data in the initial data template, so that the data analysis module 122 generates the subsequent feedback data according to the adjusted initial data template (the initial data template of which 21 is subtracted).
In one embodiment, when the risk evaluation module 123 determines that the difference value is less than or equal to the threshold value, the processor 110 executes the risk evaluation module 123 to input the difference value to the back flushing module 126. Then, the back flushing module 126 inputs the difference value to the response module 121, so that the response module 121 adjusts the next returned data according to the difference value. For example, if the difference value is 5 and the threshold value is 10, the risk estimation module 123 inputs the difference value 5 to the response module 121 through the back flushing module 126, so that the response module 121 subtracts/adds the difference value 5 from/to the next returned data, so as to make the parameters of the multiple returned data conform to the default logic rule/algorithm of the user.
In one embodiment, the step of the processor 110 executing the resource estimation module 124 to adjust the initial data template according to the difference value further includes the resource estimation module 124 adjusting the initial data template stored in the data analysis module 122 according to the difference value, and the rollback module 126 inputting the adjusted initial data template to the response module 121, so that the response module 121 adjusts the next backhaul data according to the adjusted initial data template. For example, the back flushing module 126 may actively communicate with the response module 121 to adjust the calibrated regression interface in the response module 121 based on the data/initial data template provided by the data analysis module 122. Thus, the response module 121 can correspondingly adjust the next corresponding returned data.
In one embodiment, the processor 110 may adjust the initial data template based on a plurality of historical data. That is, the instant response system 100 of the present invention can adjust the initial data template according to the multiple request data, the feedback data, the inventory data and the difference value, so that the initial data template gradually fits to and conforms to the actual data and the actual operation result.
The risk estimation module 123 may also calculate a difference value based on the history request data and/or the trend of the history data according to the request data and the returned data. In an embodiment, the risk estimation module 123 may determine whether the difference between the current request data and the normal distribution data is smaller than a threshold according to the normal distribution of the history data. For example, when the value in the normal distribution map of the history data corresponding to the feature data is 70 to 80 (plus or minus 1 standard deviation value), and the value of the returned data is 65, the risk estimation module 123 calculates the difference value to be 5 (70 minus 65). In the present invention, the normal distribution map may have several standard deviation ranges preset by the user, and the present application should not be limited thereto.
In this embodiment, the step of adjusting the initial data template according to the difference value further includes the resource estimation module 124 scaling up or scaling down the initial data template according to the feature data and the difference value. And, the resource estimation module 124 adjusts the value of the scaled initial data template according to the difference value. For example, the number of manufactured materials a in the initial data template corresponding to the requested data is 1000. Including manufacturing yield considerations, the amount of raw data template required to be prepared is roughly 1100. The characteristic data in the request data is 100 manufacturing numbers, 120 request numbers, 120 return data numbers, and 110 operation results obtained by the resource estimation module 124. Therefore, the resource estimation module 124 scales the data of the initial data template to the manufacturing number of 100 according to the characteristic data (manufacturing number of 100) and the data of the initial data template (manufacturing number of 1000), and the number of the prepared data is 110. Then, the resource estimation module 124 adjusts the difference value of 10 (120 pieces of the returned data minus the result data of 110) of the current time to the value in the scaled initial data template (the amount required to be prepared is adjusted from 110 to 100), so as to subtract the more authorized/output materials of the current returned data. Thus, the instant response system 100 and the instant response method of the present invention can correspondingly adjust the ratio of the parameter and the data in the initial data template according to the characteristic data of the request data, and simultaneously adjust the parameter of the initial data template according to the difference value, thereby timely adjusting the subsequent returned data according to the previous request data and the returned data to improve the accuracy of the operation.
In summary, the instant response system 100 and the instant response method of the present invention can effectively improve the data/service processing efficiency, and can generate the return data (return information) responding to the request data (request information) of the requesting end (client) in real time and quickly. The instant response system 100 and the instant response method of the present invention can quickly return information to the requesting end or the next processing port according to the default flow to overcome the tedious defect of the conventional synchronous processing. And, adjust the initial data template/data of next time of back transmission according to this back transmission data and follow-up actual operation result, and then have the advantage of fast response while managing stock/data according to operation result concurrently. The request end can receive response quickly, so as to avoid the condition that the setting of the receiving end needs to be adjusted again or the receiving end can not receive information due to overlong response time or more additional receiving ends need to be established in the conventional asynchronous processing. By the features of the instant response system 100 and the instant response method of the present invention, the user does not need to greatly adjust the architecture of the responding end, for example, the synchronous processing architecture is changed into the asynchronous processing architecture, and the instant response system 100 and the method having both the advantages of synchronous processing and asynchronous processing can be achieved.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and these modifications or substitutions do not depart from the spirit of the corresponding technical solutions of the embodiments of the present invention.
Claims (14)
1. An instant response system, comprising:
a storage device storing an initial data template and a plurality of modules, wherein the plurality of modules includes a response module, a data analysis module, a risk estimation module, and a resource estimation module; and
a processor coupled to the storage device,
wherein the processor executes the data analysis module to enable the data analysis module to perform data analysis on the request data and obtain the feature data, the data analysis module generates the return data according to the feature data and the initial data template, and inputs the return data to the response module and the risk estimation module,
wherein the processor executes the response module to output the backhaul data,
wherein the processor executes the risk estimation module to calculate a difference value based on a logical rule based on the request data and the return data,
when the risk estimation module judges that the difference value is larger than a threshold value, the processor executes the resource estimation module to adjust the initial data template according to the difference value.
2. The instant response system of claim 1 wherein the plurality of modules further comprises a variance accumulation module and a back-flushing module,
wherein when the risk estimation module determines that the difference value is less than or equal to a threshold, the processor executes the risk estimation module to input the difference value to the back flushing module, and the back flushing module inputs the difference value to the difference accumulation module, so that the difference accumulation module accumulates the difference values each time to obtain a current total difference value,
when the current total difference value is greater than a difference threshold value, the difference accumulation module inputs the current total difference value to the resource estimation module, so that the resource estimation module adjusts the initial data template according to the current total difference value.
3. The system of claim 1, wherein the plurality of modules further comprises a back-flushing module, wherein the processor executes the risk assessment module to input the discrepancy value to the back-flushing module when the risk assessment module determines that the discrepancy value is less than or equal to a threshold value,
the back flushing module inputs the difference value into the response module so that the response module adjusts the next returned data according to the difference value.
4. The system of claim 1, wherein the plurality of modules further comprises a back-flushing module, wherein the resource estimation module adjusts the initial data template stored in the data analysis module according to the difference value, and the back-flushing module inputs the adjusted initial data template to the response module, so that the response module adjusts the back-flushing data of the next time according to the adjusted initial data template.
5. The immediate response system of claim 1, wherein said processor adjusts said initial data template based on a plurality of historical data.
6. The system of claim 1, wherein the risk assessment module further calculates the discrepancy value based on historical request data and/or historical data trends based on the request data and the backtransmission data.
7. The system of claim 1, wherein the resource estimation module scales up or down the initial data template according to the feature data and the difference value, and adjusts the initial data template according to the difference value.
8. An immediate response method, comprising:
performing data analysis on the request data through a data analysis module to obtain characteristic data;
generating return data according to the characteristic data and the initial data template through the data analysis module, and inputting the return data to a response module and a risk estimation module;
wherein the backtransmission data is output by the response module,
wherein a difference value is calculated by a risk estimation module based on logic rules according to the request data and the return data,
when the risk estimation module judges that the difference value is larger than a threshold value, the initial data template is adjusted through the resource estimation module according to the difference value.
9. The method of claim 8, further comprising:
when the risk estimation module judges that the difference value is smaller than or equal to a threshold value, the risk estimation module inputs the difference value to a back flushing module;
inputting the difference value to a difference accumulation module through the backlash module so that the difference accumulation module accumulates the difference value every time to obtain a current total difference value,
when the current total difference value is greater than a difference threshold value, the difference accumulation module inputs the current total difference value to the resource estimation module, so that the resource estimation module adjusts the initial data template according to the current total difference value.
10. The method of claim 8, further comprising:
when the risk estimation module judges that the difference value is less than or equal to a threshold value, the difference value is input to a back flushing module through the risk estimation module,
the back flushing module inputs the difference value into the response module so that the response module adjusts the next returned data according to the difference value.
11. The method of claim 8, wherein the step of the resource estimation module adjusting the initial data template according to the difference value further comprises:
adjusting, by the resource estimation module, the initial data template stored in the data analysis module according to the difference value;
inputting the adjusted initial data template to the response module through a back flushing module, so that the response module adjusts the next back-flushing data according to the adjusted initial data template.
12. The method of claim 8, wherein the processor adjusts the initial data template based on a plurality of historical data.
13. The method according to claim 8, wherein the step of calculating the difference value according to the request data and the feedback data based on the logic rule by the risk estimation module further comprises: the risk estimation module calculates the difference value according to the request data and the return data based on history request data and/or history data trend.
14. The method of claim 8, wherein the step of adjusting the initial data template according to the difference value by the resource estimation module further comprises: the resource estimation module enlarges or reduces the initial data template according to the feature data and the difference value in proportion, and adjusts the initial data template according to the difference value.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210915647.1A CN115334024B (en) | 2022-08-01 | 2022-08-01 | Instant response system and instant response method |
| TW111130945A TWI802487B (en) | 2022-08-01 | 2022-08-17 | Instant response system and instant response method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210915647.1A CN115334024B (en) | 2022-08-01 | 2022-08-01 | Instant response system and instant response method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115334024A true CN115334024A (en) | 2022-11-11 |
| CN115334024B CN115334024B (en) | 2024-07-09 |
Family
ID=83919207
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210915647.1A Active CN115334024B (en) | 2022-08-01 | 2022-08-01 | Instant response system and instant response method |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN115334024B (en) |
| TW (1) | TWI802487B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080005778A1 (en) * | 2006-07-03 | 2008-01-03 | Weifeng Chen | System and method for privacy protection using identifiability risk assessment |
| CN105794154A (en) * | 2013-09-19 | 2016-07-20 | 西斯摩斯公司 | System and method for analyzing and transmitting social communication data |
| CN107710192A (en) * | 2015-05-31 | 2018-02-16 | 微软技术许可有限责任公司 | Measurement for the automatic Evaluation of conversational response |
| CN112262381A (en) * | 2018-08-07 | 2021-01-22 | 谷歌有限责任公司 | Assembling and evaluating automated assistant responses to privacy issues |
| CN112383458A (en) * | 2020-10-28 | 2021-02-19 | 交控科技股份有限公司 | Responsive communication method and system |
| US20210082420A1 (en) * | 2019-03-01 | 2021-03-18 | Google Llc | Dynamically adapting assistant responses |
| CN113421597A (en) * | 2021-06-22 | 2021-09-21 | 上海明略人工智能(集团)有限公司 | Monitoring method, monitoring system, electronic equipment and storage medium |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW200814679A (en) * | 2006-06-14 | 2008-03-16 | Divitas Networks Inc | Code-based echo cancellation |
| US8516606B2 (en) * | 2009-03-24 | 2013-08-20 | Aol Inc. | Systems and methods for challenge-response animation and randomization testing |
-
2022
- 2022-08-01 CN CN202210915647.1A patent/CN115334024B/en active Active
- 2022-08-17 TW TW111130945A patent/TWI802487B/en active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080005778A1 (en) * | 2006-07-03 | 2008-01-03 | Weifeng Chen | System and method for privacy protection using identifiability risk assessment |
| CN105794154A (en) * | 2013-09-19 | 2016-07-20 | 西斯摩斯公司 | System and method for analyzing and transmitting social communication data |
| CN107710192A (en) * | 2015-05-31 | 2018-02-16 | 微软技术许可有限责任公司 | Measurement for the automatic Evaluation of conversational response |
| CN112262381A (en) * | 2018-08-07 | 2021-01-22 | 谷歌有限责任公司 | Assembling and evaluating automated assistant responses to privacy issues |
| US20210082420A1 (en) * | 2019-03-01 | 2021-03-18 | Google Llc | Dynamically adapting assistant responses |
| CN112383458A (en) * | 2020-10-28 | 2021-02-19 | 交控科技股份有限公司 | Responsive communication method and system |
| CN113421597A (en) * | 2021-06-22 | 2021-09-21 | 上海明略人工智能(集团)有限公司 | Monitoring method, monitoring system, electronic equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 韩霜;傅惠;: "即时响应式定制公交调度优化", 公路交通科技, no. 06, 15 June 2020 (2020-06-15) * |
Also Published As
| Publication number | Publication date |
|---|---|
| TW202408209A (en) | 2024-02-16 |
| TWI802487B (en) | 2023-05-11 |
| CN115334024B (en) | 2024-07-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11416456B2 (en) | Method, apparatus, and computer program product for data quality analysis | |
| CN112365070B (en) | Power load prediction method, device, equipment and readable storage medium | |
| CN112905323A (en) | Data processing method and device, electronic equipment and storage medium | |
| CN114581210A (en) | Digital management method and system for enterprise finance based on RPA | |
| CN115334024A (en) | Instant response system and instant response method | |
| CN115858306A (en) | Micro-service monitoring method based on event stream, terminal equipment and storage medium | |
| CN115587841A (en) | Prediction data processing system and prediction data processing method | |
| CN116011677A (en) | Time sequence data prediction method and device, electronic equipment and storage medium | |
| CN114757592A (en) | Arrangement method and system for integrating workflow engine and RPA | |
| WO2018192382A1 (en) | Big data management method, terminal and device, and storage medium | |
| CN112988718B (en) | Method and system for automatically monitoring power | |
| CN116308472A (en) | Transaction amount prediction method, device, equipment and storage medium of bank equipment | |
| Houda | Comparison of approximations in stochastic and robust optimization programs | |
| CN113256192A (en) | Warehouse article planning method and device | |
| CN117391598A (en) | BOM plan adjustment method, equipment and medium based on process-level quality inspection sampling | |
| WO2014117139A9 (en) | Reducing product variations via variance partition analysis | |
| CN116233103B (en) | Interface adaptation method, device, communication equipment and storage medium | |
| CN111694717A (en) | Method and device for determining pressure bearing capacity value of system | |
| CN110852684B (en) | Method, device, equipment and storage medium for determining goods source preference | |
| Anyfantaki et al. | Stochastic bounds for portfolio analysis | |
| CN117459469A (en) | Monitoring current limiting system and method thereof | |
| CN115562215A (en) | Prediction data balance system and prediction data balance method | |
| CN116244006A (en) | Data processing method, device, storage medium, electronic equipment and product | |
| CN115268880A (en) | Code generation method and device, electronic equipment and storage medium | |
| CN113761028A (en) | Big data mining method and system based on cloud edge cooperation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |