CN116489047A - Intelligent communication management system and method based on edge calculation - Google Patents
Intelligent communication management system and method based on edge calculation Download PDFInfo
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Abstract
The invention discloses an intelligent communication management system and method based on edge calculation, which relate to the technical field of communication management and comprise the following steps: s1: acquiring communication history data of a user, processing the acquired data and storing the data in a database; s2: analyzing the communication object of the user, and classifying the label according to the analysis result; s3: monitoring the real-time communication behavior of the user, and triggering a communication management system to monitor the communication operation of the user in the whole course when the communication intention of the user is detected; s4: analyzing the monitoring data and early warning the improper communication operation of the user; the invention supports a plurality of communication modes based on edge calculation, including short messages, mails and the like, can meet the demands of different users, and provides real-time intelligent communication management service for the users through real-time monitoring and data analysis, thereby meeting the demands of enterprises or individuals on communication management.
Description
Technical Field
The invention relates to the technical field of communication management, in particular to an intelligent communication management system and method based on edge calculation.
Background
The edge computing can enable computing, storing and network resources to be as close to a user side, an Internet of things equipment side or a data source side as possible, so that user requests can be responded more quickly, service quality and data security are improved, and data transmission and storage cost is reduced. Edge computation can greatly improve network response efficiency and response speed. Communication has wide application in various fields, and is performed in a wireless and wired mode, including a local area network, a wide area network, the Internet and the like; data is transferred between computers over a network, transferring information from one place to another. However, in the daily communication operation, the communication content may be sent to the wrong receiving party due to the misoperation of the user, and the privacy is leaked, and even more, various losses may be caused. Therefore, an intelligent communication management system and method based on edge computing are needed to solve the above problems.
Disclosure of Invention
The invention aims to provide an intelligent communication management system and method based on edge calculation, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an intelligent communication management method based on edge calculation comprises the following steps:
s1: acquiring communication history data of a user, including a communication list, a communication history and the like; processing the acquired data, including data cleaning, de-duplication, integration and the like; and stored in a database;
s2: analyzing the communication object of the user, and classifying the label according to the analysis result;
s3: monitoring the real-time communication behavior of the user, and triggering a communication management system to monitor the communication operation of the user in the whole course when the communication intention of the user is detected;
s4: analyzing the monitoring data, early warning the improper communication operation of the user, and providing communication advice for the user through local calling; the dependence on the cloud is reduced;
further, the step S1 includes:
step S1-1: acquiring access rights of the edge equipment, sending a data acquisition request to a communication account of a user, and acquiring operation rights to the user account;
step S1-2: collecting historical communication data in a user communication account, wherein the historical communication data comprises a communication object, communication time and communication historical content; so as to analyze each communication object and obtain a class label which accords with the characteristics of each communication object;
step S1-3: performing data deduplication, data specification and data format conversion on all the acquired original data; combining the same type of data from different data sources, and integrating the data to form a more complete and comprehensive data set; the method is convenient for processing the problems of errors, missing, repetition, invalidation and the like in the original data, so that the data is more accurate, complete and usable, the quality and the reliability of the data are improved, and a reliable data base is provided for subsequent data analysis;
step S1-4: and storing the processed data items into a database. And correspondingly storing the processed data so as to facilitate the subsequent data call.
Further, the step S2 is used for analyzing the communication object of the user and classifying the label according to the analysis result; the method comprises the following steps:
step S2-1: receiving the user communication history data acquired in the step S1;
step S2-2: each communication object in the communication record is marked as a node, and all communication object nodes of the user A are marked as { a } 1 ,a 2 ,...,a n And }, wherein a 1 、a 2 、...、a n Each of the n communication object nodes indicates the 1 st, 2 nd; if user A and communication object a i Each communication of the user is recorded as one edge, each communication object node is respectively carded according to the communication record to obtain an edge set containing each communication object node, and a communication network is constructed through a graph theory algorithm;
step S2-3: for the constructed communication network, extracting the communication characteristics of the user for each communication object, dividing each communication object by using a clustering algorithm, and carrying out label description on each communication object according to the category characteristics of each communication object;
step S2-4: as for the classification result, it is evaluated by using a cross-validation method, and the communication object to which the class label is added is stored in the communication label database.
Further, in the step S3, the real-time communication behavior of the user is monitored, and when the communication intention of the user is detected, the communication management system is triggered to monitor the communication operation of the user in the whole course; the communication precursor operation is marked by analyzing the operation of a user on the terminal equipment through big data, the precursor operation is set as a trigger point, and whether the communication intention of the user occurs or not is judged by detecting the trigger state of the trigger point, so that the communication management system is started in advance, and the system operation efficiency is improved.
Further, in step S4, the monitoring data is analyzed, an improper communication operation of the user is pre-warned, and a communication suggestion is provided for the user through local call; the dependence on the cloud is reduced;
the method specifically comprises the following steps:
s4-1: monitoring communication operation of a user side to obtain communication request data, communication objects and communication contents of the user;
s4-2: judging the data type of the current communication content; the monitored communication content belonging to the text class is disassembled, the single sentence of the communication content is divided, stop words, punctuation marks and the like are removed, a word segmentation device is used for dividing the communication content into word combinations, and for each word, a word part marker can be used for marking the part of speech of the word; identifying nouns in the communication content; obtaining a disassembled communication semantic unit set { y } according to the word segmentation result, the part-of-speech tagging result and the noun recognition result 1 ,y 2 ,...,y m -wherein y 1 、y 2 、...、y m Respectively representing the 1 st, 2 nd, m th semantic units within user a; so as to facilitate the subsequent operations of data analysis, label identification and the like;
s4-3: carrying out category analysis on the disassembled communication content, and judging whether the current communication content accords with a category label to which the communication object belongs according to the acquired communication request data, the communication object and the data type of the communication content; the method comprises the following steps:
s4-3-1: extracting the communication characteristics of the user for the communication object from the class label to which the communication object belongs;
s4-3-2: comparing the extracted communication characteristics with the current communication operation, if the communication characteristics are successfully matched, classifying the communication contents into the category, and executing the step S4-4; if the communication characteristics are not successfully matched, the current communication operation of the user is considered to be abnormal, and an early warning prompt is sent to the user;
s4-4: the method for analyzing the disassembled communication content according with the communication operation of the class label of the communication object comprises the following steps:
s4-4-1: performing dimension conversion on the disassembled communication content; representing the communication semantic unit set as a vector set, wherein each element in the vector set represents the mapping of each semantic unit in a vector dimension;
s4-4-2: extracting the historical communication data of the communication object in the communication tag database, comparing the mapped vector set with the historical communication data of the communication object, calculating a distribution difference value K (Y L) of a distribution vector Y mapped by the semantic unit and a distribution vector L mapped by the historical communication data of the communication object, and calculating according to the following formula:
K(Y||L)＝∑P(Y h )log[P(Y h )/P(L)]；
wherein P (Y) h ) The h element representing the distribution vector Y is mapped to the probability value in the word stock in the vector dimension, and P (L) represents the probability value of the distribution vector L mapped to the word stock in the vector dimension; log represents natural logarithm; the larger the value of K (Y L) the larger the distribution difference, i.e. the more dissimilar the two distributions; if the distribution difference value of the two is smaller than beta, classifying the communication content into the category; if the communication content is judged not to belong to the communication operation of the class label user, the current communication operation of the user is considered to be abnormal, and an early warning prompt is sent to the user. The final result can be used to evaluate the correlation between the communication content and the communication object class label, thereby improving the communication efficiency and accuracySex.
An intelligent communications management system based on edge computing, the system comprising: the system comprises a data acquisition module, a data analysis module, a data monitoring module and an intelligent communication management module;
the data acquisition module is used for acquiring communication history data of a user;
the data analysis module is used for analyzing the received data and outputting an analysis result;
the data monitoring module is used for monitoring the real-time communication behavior of the user, and triggering the communication management system to monitor the communication operation of the user in the whole course when the communication intention of the user is detected;
the intelligent communication management module is used for carrying out early warning on improper communication operation of a user according to an analysis result of the monitoring data;
the output ends of the data acquisition module and the data monitoring module are connected with the input end of the data analysis module, and the output end of the data analysis module is connected with the input end of the intelligent communication management module.
Further, the data acquisition module comprises a permission acquisition unit, a communication record acquisition unit, a data processing unit and a data storage unit;
the right acquisition unit is used for acquiring the operation right for data acquisition of the user account; the safety privacy of the user can be ensured by acquiring the operation authority;
the communication record acquisition unit is used for acquiring the historical communication record of the user; so as to analyze each communication object and obtain a class label which accords with the characteristics of each communication object;
the data processing unit is used for processing each item of acquired data and storing the processed data into the database; the data processing comprises data cleaning and data integration;
the data storage unit is used for correspondingly storing the processed data so as to facilitate the subsequent data call.
Further, the data analysis module comprises a data receiving unit, a communication category analysis unit, a monitoring data analysis unit and a data transmission unit;
the data receiving unit is used for receiving each item of data transmitted to the data analysis module and receiving the data to the corresponding data analysis unit according to the data source;
the communication category analysis unit is used for classifying communication objects of users, adding labels to the communication objects, and storing results in the communication label database;
the monitoring data analysis unit is used for analyzing the monitored user communication data;
the data transmission unit is used for transmitting the data analysis result, transmitting the analysis result of the communication type analysis unit to the database for storage, and transmitting the analysis result of the monitoring data analysis unit to the intelligent communication management module for discrimination.
Further, the data monitoring module comprises a communication operation monitoring unit and a communication content analyzing unit;
the communication operation monitoring module is used for monitoring the communication operation of the user side and obtaining communication request data, communication objects and communication contents of the user;
the communication content analysis unit is used for disassembling the monitored communication content and transmitting the disassembled communication content to the data analysis module for analysis.
Further, the intelligent communication management module comprises a communication abnormality judging unit, an early warning prompting unit and a data updating unit;
the communication abnormality judging unit is used for receiving the analysis result of the monitoring data analysis unit and judging whether the real-time communication operation of the user is abnormal or not;
the communication early warning unit is used for receiving the judging result of the communication abnormality judging unit, and sending an early warning prompt to the user when judging that the current communication operation of the user is abnormal;
the data updating unit is used for receiving a processing result of the early warning prompt by a user, storing the communication record when the user considers that the current communication operation does not belong to the abnormal operation, judging whether to update the class label of the communication object through the communication class analysis unit, and updating corresponding data in the communication label database if the label update exists.
Compared with the prior art, the invention has the following beneficial effects:
the invention is based on edge calculation, and the communication history data of the user is acquired through a data acquisition module; analyzing the received data through a data analysis module, and outputting an analysis result; the method comprises the steps that the real-time communication behavior of a user is monitored through a data monitoring module, and when the communication intention of the user is detected, a communication management system is triggered to monitor the communication operation of the user in the whole course; the intelligent communication management module is used for carrying out early warning on improper communication operation of a user according to an analysis result of the monitoring data; the system supports various communication modes, including short messages, mails, other social software and the like, can meet the demands of different users, provides real-time intelligent communication management services for the users through real-time monitoring and data analysis, meets the demands of enterprises and individuals on communication management, provides a more efficient solution to the communication problem, and has wide application prospects.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic block diagram of an intelligent communication management system and method based on edge computation according to the present invention;
FIG. 2 is a flow chart of a method of the intelligent communication management system and method based on edge computing according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is further described with reference to fig. 1, 2 and embodiments.
Example 1: as shown in fig. 1, the present embodiment provides an intelligent communication management system based on edge computing, where the system includes: the system comprises a data acquisition module, a data analysis module, a data monitoring module and an intelligent communication management module; the output end of the data acquisition module and the output end of the data monitoring module are connected with the input end of the data analysis module, and the output end of the data analysis module is connected with the input end of the intelligent communication management module.
The data acquisition module is used for acquiring communication history data of a user;
the data acquisition module comprises a permission acquisition unit, a communication record acquisition unit, a data processing unit and a data storage unit;
the right acquisition unit is used for acquiring the operation right for data acquisition of the user account; the safety privacy of the user can be ensured by acquiring the operation authority;
the communication record acquisition unit is used for acquiring the historical communication record of the user; so as to analyze each communication object and obtain a class label which accords with the characteristics of each communication object;
the data processing unit is used for processing each item of acquired data and storing the processed data into the database; the data processing comprises data cleaning and data integration;
the data storage unit is used for correspondingly storing the processed data so as to facilitate the subsequent data call.
The data analysis module is used for analyzing the received data and outputting an analysis result;
the data analysis module comprises a data receiving unit, a communication category analysis unit, a monitoring data analysis unit and a data transmission unit;
the data receiving unit is used for receiving each item of data transmitted to the data analysis module and receiving the data to the corresponding data analysis unit according to the data source;
the communication category analysis unit is used for classifying communication objects of users, adding labels to the communication objects, and storing results into the communication label database;
the monitoring data analysis unit is used for analyzing the monitored user communication data;
the data transmission unit is used for transmitting the data analysis result, transmitting the analysis result of the communication type analysis unit to the database for storage, and transmitting the analysis result of the monitoring data analysis unit to the intelligent communication management module for discrimination.
The data monitoring module is used for monitoring the real-time communication behavior of the user, and triggering the communication management system to monitor the communication operation of the user in the whole course when the communication intention of the user is detected;
the data monitoring module comprises a communication operation monitoring unit and a communication content analyzing unit;
the communication operation monitoring module is used for monitoring the communication operation of the user side and acquiring communication request data, communication objects and communication contents of the user;
the communication content analysis unit is used for disassembling the monitored communication content and transmitting the disassembled communication content to the data analysis module for analysis.
The intelligent communication management module is used for carrying out early warning on improper communication operation of a user according to an analysis result of the monitoring data;
the intelligent communication management module comprises a communication abnormality judging unit, an early warning prompting unit and a data updating unit;
the communication abnormality judging unit is used for receiving the analysis result of the monitoring data analyzing unit and judging whether the real-time communication operation of the user is abnormal or not;
the communication early warning unit is used for receiving the judging result of the communication abnormality judging unit, and sending an early warning prompt to the user when judging that the current communication operation of the user is abnormal;
the data updating unit is used for receiving a processing result of the early warning prompt by a user, storing the communication record when the user considers that the current communication operation does not belong to the abnormal operation, judging whether to update the class label of the communication object through the communication class analysis unit, and updating corresponding data in the communication label database if the label update exists.
Example 2: as shown in fig. 2, the present embodiment provides an intelligent communication management method based on edge computing, which is implemented based on an intelligent communication management system based on edge computing in the embodiment, and specifically includes the following steps:
s1: acquiring communication history data of a user, including a communication list, a communication history and the like; processing the acquired data, including data cleaning, de-duplication, integration and the like; and stored in a database;
the step S1 comprises the following steps:
step S1-1: acquiring access rights of the edge equipment, sending a data acquisition request to a communication account of a user, and acquiring operation rights to the user account;
step S1-2: collecting historical communication data in a user communication account, wherein the historical communication data comprises a communication object, communication time and communication historical content; so as to analyze each communication object and obtain a class label which accords with the characteristics of each communication object;
step S1-3: performing data deduplication, data specification and data format conversion on all the acquired original data; combining the same type of data from different data sources, and integrating the data to form a more complete and comprehensive data set; the method is convenient for processing the problems of errors, missing, repetition, invalidation and the like in the original data, so that the data is more accurate, complete and usable, the quality and the reliability of the data are improved, and a reliable data base is provided for subsequent data analysis;
step S1-4: and storing the processed data items into a database. And correspondingly storing the processed data so as to facilitate the subsequent data call.
S2: analyzing the communication object of the user, and classifying the label according to the analysis result;
s2, analyzing the communication object of the user, and classifying the label according to the analysis result; the method comprises the following steps:
step S2-1: receiving the user communication history data acquired in the step S1, wherein the user communication history data comprises short messages, telephones, mails, social software records and the like;
step S2-2: each communication object in the communication record is marked as a node, and all communication object nodes of the user A are marked as { a } 1 ,a 2 ,...,a n And }, wherein a 1 、a 2 、...、a n Each of the n communication object nodes indicates the 1 st, 2 nd; if user A and communication object a i Each communication of the user is recorded as one edge, each communication object node is respectively carded according to the communication record to obtain an edge set containing each communication object node, and a communication network is constructed through a graph theory algorithm;
step S2-3: for the constructed communication network, extracting the communication characteristics of the user for each communication object, such as communication time, communication density, communication connectivity and the like; dividing each communication object by using a clustering algorithm such as a K-means algorithm, a hierarchical clustering algorithm and the like, and performing label description on each communication object according to the category characteristics of each communication object;
step S2-4: for the classification result, the classification result is evaluated by using a cross-validation method, so that the accuracy and the reliability of classification are ensured; and storing the communication object added with the category label into a communication label database.
S3: monitoring the real-time communication behavior of the user, and triggering a communication management system to monitor the communication operation of the user in the whole course when the communication intention of the user is detected;
in step S3, monitoring the real-time communication behavior of the user, and triggering the communication management system to monitor the communication operation of the user in the whole course when detecting that the user has communication intention; the communication precursor operation is marked by analyzing the operation of a user on the terminal equipment through big data, the precursor operation is set as a trigger point, and whether the communication intention of the user occurs or not is judged by detecting the trigger state of the trigger point, so that the communication management system is started in advance, and the system operation efficiency is improved.
S4: analyzing the monitoring data, early warning the improper communication operation of the user, and providing communication advice for the user through local calling; the dependence on the cloud is reduced; in step S4, analyzing the monitoring data, carrying out early warning on improper communication operation of the user, and providing communication advice for the user through local calling; the dependence on the cloud is reduced;
the method specifically comprises the following steps:
s4-1: monitoring communication operation of a user side to obtain communication request data, communication objects and communication contents of the user;
s4-2: judging the data type of the current communication content; the monitored communication content belonging to the text class is disassembled, the single sentence of the communication content is divided, stop words, punctuation marks and the like are removed, a word segmentation device is used for dividing the communication content into word combinations, and for each word, the part of speech of the word can be marked by a part of speech marking device, such as nouns, verbs, adjectives and the like; identifying nouns in the communication content, such as a person name, a place name, an organization name and other entities; obtaining a disassembled communication semantic unit set { y } according to the word segmentation result, the part-of-speech tagging result and the noun recognition result 1 ,y 2 ,...,y m -wherein y 1 、y 2 、...、y m Respectively representing the 1 st, 2 nd, m th semantic units within user a; so as to facilitate the subsequent operations of data analysis, label identification and the like; the semantic unit refers to the smallest meaningful unit in the language, has independent and unique semantic content, can be independently applied to sentences, and can convey specific semantic information.
S4-3: carrying out category analysis on the disassembled communication content, and judging whether the current communication content accords with a category label to which the communication object belongs according to the acquired communication request data, the communication object and the data type of the communication content; the method comprises the following steps:
s4-3-1: extracting the communication characteristics of the user for the communication object from the class label to which the communication object belongs;
s4-3-2: comparing the extracted communication characteristics with the current communication operation, if the communication characteristics are successfully matched, classifying the communication contents into the category, and executing the step S4-4; if the communication characteristics are not successfully matched, the current communication operation of the user is considered to be abnormal, and an early warning prompt is sent to the user;
s4-4: the method for analyzing the disassembled communication content according with the communication operation of the class label of the communication object comprises the following steps:
s4-4-1: performing dimension conversion on the disassembled communication content; representing the communication semantic unit set as a vector set, wherein each element in the vector set represents the mapping of each semantic unit in a vector dimension; wherein the vector dimension may be multidimensional;
s4-4-2: extracting the historical communication data of the communication object in the communication tag database, comparing the mapped vector set with the historical communication data of the communication object, calculating a distribution difference value K (Y L) of a distribution vector Y mapped by the semantic unit and a distribution vector L mapped by the historical communication data of the communication object, and calculating according to the following formula:
K(Y||L)＝∑P(Y h )log[P(Y h )/P(L)]；
wherein P (Y) h ) The h element representing the distribution vector Y is mapped to the probability value in the word stock in the vector dimension, and P (L) represents the probability value of the distribution vector L mapped to the word stock in the vector dimension; log represents natural logarithm; the larger the value of K (Y L) the larger the distribution difference, i.e. the more dissimilar the two distributions; if the distribution difference value of the two is smaller than beta, classifying the communication content into the category; if the communication content is judged not to belong to the communication operation of the class label user, the current communication operation of the user is considered to be abnormal, and an early warning prompt is sent to the user. The final result can be used for evaluating the correlation between the communication content and the communication object type label, thereby improving the communication efficiency and accuracy.
For example, coordinate axes are set in vector dimensions according to parts of speech, semantic features and the like, all historical communication data of a user are mapped to obtain distribution conditions of total word quantity in a word stock in a dimension space, a distribution probability value of a distribution vector L of the historical communication data of a user for a communication object in the word stock is obtained through calculation, meanwhile, a distribution probability value of each element in a semantic unit set obtained through disassembly of the current communication content of the user in the word stock is obtained through calculation, and therefore distribution difference values of the two elements are calculated, and therefore the similarity degree of the current communication content and the historical communication content of the communication object is judged, and whether the current communication content can be sent to the communication object is judged.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An intelligent communication management method based on edge calculation is characterized in that: the method comprises the following steps:
s1: acquiring communication history data of a user, processing the acquired data and storing the data in a database;
s2: analyzing the communication object of the user, and classifying the label according to the analysis result;
s3: monitoring the real-time communication behavior of the user, and triggering a communication management system to monitor the communication operation of the user in the whole course when the communication intention of the user is detected;
s4: and analyzing the monitoring data and early warning the improper communication operation of the user.
2. The intelligent communication management method based on edge calculation according to claim 1, wherein: the step S1 includes:
step S1-1: acquiring access rights of the edge equipment, sending a data acquisition request to a communication account of a user, and acquiring operation rights to the user account;
step S1-2: collecting historical communication data in a user communication account, wherein the historical communication data comprises a communication object, communication time and communication historical content;
step S1-3: performing data deduplication, data specification and data format conversion on all the acquired original data; combining the same type of data from different data sources, and integrating the data to form a more complete and comprehensive data set;
step S1-4: and storing the processed data items into a database.
3. The intelligent communication management method based on edge calculation according to claim 1, wherein: s2, analyzing the communication object of the user, and classifying the label according to the analysis result; the method comprises the following steps:
step S2-1: receiving the user communication history data acquired in the step S1;
step S2-2: each communication object in the communication record is marked as a node, and all communication object nodes of the user A are marked as { a } 1 ,a 2 ,...,a n And }, wherein a 1 、a 2 、...、a n Each of the n communication object nodes indicates the 1 st, 2 nd; if user A and communication object a i Communication exists between the nodes, each communication of the user is recorded as one edge, each communication object node is respectively carded according to the communication record to obtain an edge set containing each communication object node, and the edge set is used for processing the graphConstructing a communication network by using a theoretical algorithm;
step S2-3: for the constructed communication network, extracting the communication characteristics of the user for each communication object, dividing each communication object by using a clustering algorithm, and carrying out label description on each communication object according to the category characteristics of each communication object;
step S2-4: and for the classification result, the classification result is evaluated by using a cross-validation method, and the communication object added with the class label and related data thereof are stored in a communication label database.
4. The intelligent communication management method based on edge calculation according to claim 1, wherein: in the step S3, the real-time communication behavior of the user is monitored, and when the communication intention of the user is detected, the communication management system is triggered to monitor the communication operation of the user in the whole course; the communication precursor operation is marked by analyzing the operation of a user on the terminal equipment through big data, the precursor operation is set as a trigger point, and whether the communication intention of the user occurs is judged by detecting the trigger state of the trigger point.
5. The intelligent communication management method based on edge calculation according to claim 1, wherein: in step S4, the method specifically includes the following steps:
s4-1: monitoring communication operation of a user side to obtain communication request data, communication objects and communication contents of the user;
s4-2: judging the data type of the current communication content; disassembling the monitored communication content belonging to the text class, dividing the single sentence of the communication content, dividing the communication content into word combinations by using a word segmentation device, and labeling the part of speech of each word; identifying nouns in the communication content; obtaining a disassembled communication semantic unit set { y } according to the word segmentation result, the part-of-speech tagging result and the noun recognition result 1 ,y 2 ,...,y m -wherein y 1 、y 2 、...、y m Respectively representing the 1 st, 2 nd, m th semantic units within user a;
s4-3: carrying out category analysis on the disassembled communication content, and judging whether the current communication content accords with a category label to which the communication object belongs according to the acquired communication request data, the communication object and the data type of the communication content; the method comprises the following steps:
s4-3-1: extracting the communication characteristics of the user for the communication object from the class label to which the communication object belongs;
s4-3-2: comparing the extracted communication characteristics with the current communication operation, if the communication characteristics are successfully matched, classifying the communication contents into the category, and executing the step S4-4; if the communication characteristics are not successfully matched, the current communication operation of the user is considered to be abnormal, and an early warning prompt is sent to the user;
s4-4: the method for analyzing the disassembled communication content according with the communication operation of the class label of the communication object comprises the following steps:
s4-4-1: performing dimension conversion on the disassembled communication content; representing the communication semantic unit set as a vector set, wherein each element in the vector set represents the mapping of each semantic unit in a vector dimension;
s4-4-2: extracting the historical communication data of the communication object in the communication tag database, comparing the mapped vector set with the historical communication data of the communication object, calculating a distribution difference value K (Y L) of a distribution vector Y mapped by the semantic unit and a distribution vector L mapped by the historical communication data of the communication object, and calculating according to the following formula:
K(Y||L)＝∑P(Y h )log[P(Y h )/P(L)]；
wherein P (Y) h ) The h element representing the distribution vector Y is mapped to the probability value in the word stock in the vector dimension, and P (L) represents the probability value of the distribution vector L mapped to the word stock in the vector dimension; log represents natural logarithm; the larger the value of K (Y L) the larger the distribution difference, i.e. the more dissimilar the two distributions; if the distribution difference value of the two is smaller than beta, classifying the communication content into the category; if the communication content is judged not to belong to the communication operation of the class label user, the user is considered to be the current communication operationIf the abnormality exists, an early warning prompt is sent to the user.
6. An intelligent communication management system based on edge calculation is characterized in that: the system comprises: the system comprises a data acquisition module, a data analysis module, a data monitoring module and an intelligent communication management module;
the data acquisition module is used for acquiring communication history data of a user;
the data analysis module is used for analyzing the received data and outputting an analysis result;
the data monitoring module is used for monitoring the real-time communication behavior of the user, and triggering the communication management system to monitor the communication operation of the user in the whole course when the communication intention of the user is detected;
the intelligent communication management module is used for carrying out early warning on improper communication operation of a user according to an analysis result of the monitoring data;
the output ends of the data acquisition module and the data monitoring module are connected with the input end of the data analysis module, and the output end of the data analysis module is connected with the input end of the intelligent communication management module.
7. The intelligent communication management system based on edge computing of claim 6, wherein: the data acquisition module comprises an authority acquisition unit, a communication record acquisition unit, a data processing unit and a data storage unit;
the right acquisition unit is used for acquiring the operation right for data acquisition of the user account; the communication record acquisition unit is used for acquiring the historical communication record of the user; the data processing unit is used for processing each item of acquired data and storing the processed data into the database; the data storage unit is used for correspondingly storing the processed various data.
8. The intelligent communication management system based on edge computing of claim 6, wherein: the data analysis module comprises a data receiving unit, a communication category analysis unit, a monitoring data analysis unit and a data transmission unit;
the data receiving unit is used for receiving each item of data transmitted to the data analysis module and receiving the data to the corresponding data analysis unit according to the data source;
the communication category analysis unit is used for classifying communication objects of users, adding labels to the communication objects, and storing results in the communication label database;
the monitoring data analysis unit is used for analyzing the monitored user communication data;
the data transmission unit is used for transmitting the data analysis result, transmitting the analysis result of the communication type analysis unit to the database for storage, and transmitting the analysis result of the monitoring data analysis unit to the intelligent communication management module for discrimination.
9. The intelligent communication management system based on edge computing of claim 6, wherein: the data monitoring module comprises a communication operation monitoring unit and a communication content analyzing unit;
the communication operation monitoring module is used for monitoring the communication operation of the user side and obtaining communication request data, communication objects and communication contents of the user;
the communication content analysis unit is used for disassembling the monitored communication content and transmitting the disassembled communication content to the data analysis module for analysis.
10. The intelligent communication management system based on edge computing of claim 6, wherein: the intelligent communication management module comprises a communication abnormality judging unit, an early warning prompting unit and a data updating unit;
the communication abnormality judging unit is used for receiving the analysis result of the monitoring data analysis unit and judging whether the real-time communication operation of the user is abnormal or not;
the communication early warning unit is used for receiving the judging result of the communication abnormality judging unit, and sending an early warning prompt to the user when judging that the current communication operation of the user is abnormal;
the data updating unit is used for receiving a processing result of the early warning prompt by a user, storing the communication record when the user considers that the current communication operation does not belong to the abnormal operation, judging whether to update the class label of the communication object through the communication class analysis unit, and updating corresponding data in the communication label database if the label update exists.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109120498A (en) * | 2017-06-22 | 2019-01-01 | 北京小米移动软件有限公司 | Send the method and device of information |
| CN113988086A (en) * | 2021-09-29 | 2022-01-28 | 阿里巴巴达摩院(杭州)科技有限公司 | Conversation processing method and device |
| CN115206524A (en) * | 2021-04-13 | 2022-10-18 | 复旦大学 | State monitoring system for team cooperation |
| CN115643159A (en) * | 2022-11-18 | 2023-01-24 | 奇点创新(江苏)智能科技有限公司 | Equipment abnormity early warning method and system based on edge calculation |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109120498A (en) * | 2017-06-22 | 2019-01-01 | 北京小米移动软件有限公司 | Send the method and device of information |
| CN115206524A (en) * | 2021-04-13 | 2022-10-18 | 复旦大学 | State monitoring system for team cooperation |
| CN113988086A (en) * | 2021-09-29 | 2022-01-28 | 阿里巴巴达摩院(杭州)科技有限公司 | Conversation processing method and device |
| CN115643159A (en) * | 2022-11-18 | 2023-01-24 | 奇点创新(江苏)智能科技有限公司 | Equipment abnormity early warning method and system based on edge calculation |
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