CN117171023A - Java code-based machine quality inspection method and system - Google Patents
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Abstract
The invention discloses a machine quality inspection method based on Java codes, which specifically comprises the following steps: data preprocessing, data packaging, data transmission, data verification and generation of an analysis tree, wherein the analysis tree is used for segmenting transmission data to be detected, setting the transmission data to be detected as a single task, transmitting the single task to an execution engine for detection, and marking the transmission data in detection as in-detection; the execution engine detects the transmission data in a medium sequence traversing mode, outputs a detection result and marks the detected transmission data as to-be-rechecked; and storing the detection result in a database, and rechecking the detection result to finish data inspection. The invention solves the problem that massive customer service data cannot be completely detected, thereby improving the working efficiency, improving the service quality, simplifying the working flow and improving the service efficiency.
Description
Technical Field
The invention belongs to the technical field of networks, and particularly relates to a Java code-based machine quality inspection method and system.
Background
With the development of network technology and business needs, more and more enterprises establish own customer service systems to provide services such as consultation and complaint, but often customer service quality is difficult to control, and problems such as nonstandard customer service, untimely service, emotional service and the like occur, so that the enterprises are difficult to provide high-quality external services. Under the condition, more quality inspection personnel still need to be employed to control the service quality, but screening inspection on all data still cannot be achieved, and the problem of abnormal service is easily omitted, so that enterprises need to have a system for inspecting all service data in a full quantity to standardize external service of the enterprises, improve the service quality, simplify the working flow and improve the service efficiency.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a Java code-based machine quality inspection method and system, which solve the problem that massive customer service data cannot be inspected completely, thereby improving the working efficiency, improving the service quality, simplifying the working flow and improving the service efficiency.
In order to achieve the above object, the present invention provides the following technical solutions:
a machine quality inspection method based on Java codes specifically comprises the following steps:
s1, preprocessing data, and extracting features of session data, wherein the feature extraction of the session data comprises session time, session participants, session satisfaction, message content, message roles, message intervals, silence time and co-operation frequency;
s2, packaging data, converting session data into transmission data in json format, generating a use signature for the transmission data, generating a task number, storing the task number in a database, and marking the transmission data as a state to be transmitted;
s3, data transmission, namely transmitting the data to be transmitted stored in the database to a quality inspection server;
s4, checking the received transmission data by the quality inspection server, storing the transmission data in a database, and marking the checked data as to-be-detected;
s5, generating an analysis tree, segmenting the transmission data to be detected by using the analysis tree, setting the segmentation tree as a single task, transmitting the single task to an execution engine for detection, and marking the transmission data in detection as in detection;
s6, the execution engine detects the transmission data in a medium sequence traversing mode, outputs a detection result and marks the detected transmission data as to-be-rechecked;
and S7, storing the detection result in a database, and rechecking the detection result to finish data inspection.
Further, the data transmitted to the quality inspection server in S3 further includes transmission data that fails to be transmitted to the quality inspection server, and when the transmission data fails to be transmitted to the quality inspection server, the transmission is performed again when the next data transmission is performed.
Further, the specific step of verifying the transmission data in S4 is: the quality inspection server generates a signature for the received transmission data, and compares the generated signature with the signature of the corresponding data to be transmitted in the database; when the signature comparison is the same, the received data to be transmitted is stored in a database through verification; and when the signature comparison is different, discarding the transmission data and returning the signature comparison and carrying out error prompt.
Further, the specific step of generating the parse tree in S5 is as follows:
s51, scanning part of speech of each word in the rule text of the specific keyword through a text scanner to generate a rule model, and storing the rule model into a database;
s52, obtaining a rule model from the database, checking the rule model to generate a Token list, pressing the contents in the Token list into a stack one by one, and forming an analysis tree according to a specific operator.
Further, the Token list is formed by sequentially splitting rule models stored in a database into identifiable phrases.
Further, the specific operator comprises a logic operator, a keyword expression, a relational operator expression and a special operator expression, the analysis tree is in a binary tree structure, a root node in the analysis tree is a logic operator, a leaf node in the analysis tree is an expression, and the expression comprises the keyword expression, the relational operator expression and the special operator expression.
Further, the logical operators comprise AND, OR and negation, wherein the AND indicates that the situation that both the left subtree and the right subtree output True is hit; "OR" indicates that any one of the left and right subtrees outputs True as hit; "inverting" means on an and or basis, and (3) performing operation of taking the result as the opposite result.
Further, the keyword expression is used for detecting whether the detection data comprises a set keyword or not; the relational operator expressions are descriptors of "greater than," equal to, "" less than, "" greater than or equal to, "" less than or equal to, "" not equal to, "" most recent, "and" during.
Further, the execution engine in S6 includes a logical operator execution engine, a keyword execution engine, a relational operator execution engine and a special operator execution engine, where the logical operator execution engine processes the transmission data through a logical operator, the keyword execution engine detects whether the transmission data contains keywords described by leaf nodes through a keyword expression, if yes, true is output, otherwise False, the relational operator execution engine processes a root node through a relational operator expression, a left leaf node of the root node is fixed to a field name to be compared, a right leaf node is fixed to a field value to be compared, and the special operator execution engine detects whether the keywords having a proximity relation in the transmission data meet requirements through a special operator expression.
Further, the specific steps of the execution engine for detecting in a medium sequence traversal mode are as follows: the execution engine starts traversing the left subtree from the root node of the binary tree, if the node is an AND operator and the left subtree outputs True, the right subtree needs to be checked to be True/False, and if the left subtree and the right subtree are both True, the node is hit; if any subtree is False, the node has no hit; if the node is an or operator and the left subtree outputs False, the right subtree needs to be checked to be True/False, if both the left subtree and the right subtree are False, the node is hit, and if any subtree is True, the node is hit.
Further, the specific step of rechecking the detected transmission data in S7 is as follows: and (3) performing manual rechecking on the data with unqualified detection results, and when the manual rechecking results are different from the detection results of the execution engine, performing complaint on the manual rechecking results to modify the detection results of the execution engine, and marking the modified transmission data as rechecked.
The system comprises a data processing module, a data detection module, a data rechecking module and a database module;
the data processing module is used for carrying out format conversion on the transmission data to be detected, marking the transmission data and then transmitting the transmission data to the data detection module;
the data detection module is used for receiving the transmission data to be detected and checking, and detecting the transmission data through the execution engine by generating an analysis tree and the execution engine;
the data rechecking module is used for manually rechecking the data with unqualified detection results, comparing the rechecking results with the detection results in the data detection module, determining the detection results of the transmission data, and storing the detection results;
the database module is used for storing transmission data to be detected, checked data and transmission data detection results.
Based on the technical scheme, the Java code-based machine quality inspection method and system have the following technical advantages through practical application:
1. the Java code-based machine quality inspection method solves the problem that massive customer service data cannot be inspected completely, so that the working efficiency is improved, the service quality is improved, the working flow is simplified, and the service efficiency is improved.
2. The method for machine quality inspection based on Java codes realizes the detection of whether the keywords with the proximity relation meet the regulations or not by arranging the special operator execution engine in the execution engine, improves the detection effect and improves the standardization of customer service.
Drawings
Fig. 1 is a flow chart of quality inspection of transmission data in a machine quality inspection method based on Java code according to the present invention.
Fig. 2 is a diagram of an analysis tree structure in a method for machine quality inspection based on Java code according to the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention is described below by way of specific examples shown in the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present invention.
As shown in fig. 1-2, the invention belongs to a machine quality inspection method based on Java code, which specifically comprises the following steps:
s1, preprocessing data, and extracting features of session data, wherein the feature extraction of the session data comprises session time, session participants, session satisfaction, message content, message roles, message intervals, silence time and co-operation frequency;
s2, packaging data, converting session data into transmission data in json format, generating a use signature for the transmission data, generating a task number, storing the task number in a database, and marking the transmission data as a state to be transmitted;
s3, data transmission, namely transmitting the data to be transmitted stored in the database to a quality inspection server;
s4, checking the received transmission data by the quality inspection server, storing the transmission data in a database, and marking the checked data as to-be-detected;
s5, generating an analysis tree, segmenting the transmission data to be detected by using the analysis tree, setting the segmentation tree as a single task, transmitting the single task to an execution engine for detection, and marking the transmission data in detection as in detection;
s6, the execution engine detects the transmission data in a medium sequence traversing mode, outputs a detection result and marks the detected transmission data as to-be-rechecked;
and S7, storing the detection result in a database, and rechecking the detection result to finish data inspection.
The data transmitted to the quality inspection server in S3 further includes transmission data which fails to be transmitted to the quality inspection server, and when the transmission data fails to be transmitted to the quality inspection server, the transmission is performed again when the next data transmission is performed.
The specific step of verifying the transmission data in S4 is as follows: the quality inspection server generates a signature for the received transmission data, and compares the generated signature with the signature of the corresponding data to be transmitted in the database; when the signature comparison is the same, the received data to be transmitted is stored in a database through verification; and when the signature comparison is different, discarding the transmission data and returning the signature comparison and carrying out error prompt.
The specific step of generating the parse tree in the step S5 is as follows:
s51, scanning part of speech of each word in a rule text of a specific keyword through a text scanner to generate a rule model, checking that the rule text meets the system requirement, and storing the rule model into a database;
the regular text of the specific keyword is a regular text composed of keywords and system reserved words (AND, OR, NOT, NEAR, AFTER, FREQ, OFFSET, > =, <=, <);
the system reserved word is an AND system reserved word which represents an AND relationship AND can be matched with a text of which two business keywords or submodel expressions exist at the same time; the "OR" system reserved word represents the relationship of "OR", which can be matched to the text of at least one business keyword OR submodel expression about the existence of the system reserved word;
the relation that the 'NOT' system reserved word represents 'NOT' can be matched with the fact that no business keyword or sub-expression on the right side of the system reserved word exists;
the "NEAR" system reserved word represents a relationship of "close to", and can be matched with the service keywords of which the left and right sides of the reserved word exist and the distance between the two service keywords is within N words;
the 'AFTER' system reserved word indicates that the relation of the sequence 'approaching' exists, and the relation can be matched with the business keywords on the left side of the reserved word of the system, and the business keywords on the right side of the reserved word of the system exist in the N words;
the "AFTER" system retains words supporting 3 AFTER, e.g., A AFTER B AFTER C, where A, B, C represents the business keyword;
the NEAR/AFTER system keeps 1-3 words supported before and AFTER the words, and the words are separated by commas; the system of "A-", and "B-" retains the role of words representing business keywords, the business keywords of the corresponding roles can be matched with any default roles;
"FREQ" for specifying the frequency of occurrence of a business keyword in the format of "W FREQ n" or "WFREQ n, m", W representing the business keyword, n, m representing the range of times W occurs in the text, n, m must be natural numbers, and n < = m;
"OFFSET" for specifying a position where a business keyword appears, the format being "W OFFSET n, m", W representing the business keyword, n, m representing a range of positions where the occurrence in text occurs, n, m having to be a natural number, and n < = m;
"()" represents a submodel expression, the above system can be used in brackets to preserve the word definition model and increase the matching priority of the submodel, including re-nesting the submodel;
the 'adding' can add the current business keywords into the model text;
the added relational terms, double click can realize the switch between AND AND OR OR NEAR AND AFTER;
a NEAR/AFTER-n B, a AFTER-n B AFTER-n C, a, B, C NEAR/AFTER-nD, E, F, n represent the matching distance of a single NEAR or AFTER rule, n must be an integer of > = 0 and < = 500;
s52, obtaining a rule model from the database, checking the rule model to generate a Token list, pressing the contents in the Token list into a stack one by one, and forming an analysis tree according to a specific operator.
The Token list is formed by sequentially splitting rule models stored in a database into identifiable phrases; the rule model is split in sequence, and the rule model is split into phrases which can be recognized by a system, for example: "hello AND" is in the same time "will be split into 3 Token, namely" hello "," AND "is in the same time", AND these phrases will be called Token list.
The specific operator comprises a logic operator, a keyword expression, a relational operator expression and a special operator expression, the analysis tree is of a binary tree structure, a root node in the analysis tree is the logic operator, a leaf node in the analysis tree is the expression, and the expression comprises the keyword expression, the relational operator expression and the special operator expression.
The logical operators comprise AND, OR and negation, wherein the AND indicates that the situation that both the left subtree and the right subtree output True is hit; "OR" indicates that any one of the left and right subtrees outputs True as hit; "inverting" means on an and or basis, and (3) performing operation of taking the result as the opposite result.
The keyword expression is used for detecting whether the detection data comprise set keywords or not; the relational operator expressions are descriptors of "greater than," equal to, "" less than, "" greater than or equal to, "" less than or equal to, "" not equal to, "" most recent, "and" during.
The execution engine in the S6 comprises a logical operator execution engine, a keyword execution engine, a relational operator execution engine and a special operator execution engine, wherein the logical operator execution engine processes transmission data through a logical operator, the keyword execution engine is used for detecting whether the transmission data contains keywords described by leaf nodes through a keyword expression, if yes, true is output, otherwise False, the relational operator execution engine processes root nodes through a relational operator expression, the left leaf nodes of the root nodes are fixed to field names needing to be compared, the right leaf nodes are fixed to field values needing to be compared, and the special operator execution engine is used for detecting whether the keywords with adjacent relations in the transmission data meet requirements through a special operator expression;
for example: the keywords A and B need to be arranged after 10 words are separated, and the keywords C need to be arranged after 15 words are separated, and a special operator execution engine is used for detecting whether the keywords in the data meet the specified keyword sequence requirements.
The specific steps of the execution engine for detection in a medium sequence traversal mode are as follows: the execution engine starts traversing the left subtree from the root node of the binary tree, if the node is an AND operator and the left subtree outputs True, the right subtree needs to be checked to be True/False, and if the left subtree and the right subtree are both True, the node is hit; if any subtree is False, the node has no hit; if the node is an or operator and the left subtree outputs False, the right subtree needs to be checked to be True/False, if both the left subtree and the right subtree are False, the node is hit, and if any subtree is True, the node is hit.
The specific step of rechecking the detected transmission data in S7 is as follows: and (3) performing manual rechecking on the data with unqualified detection results, and when the manual rechecking results are different from the detection results of the execution engine, performing complaint on the manual rechecking results to modify the detection results of the execution engine, and marking the modified transmission data as rechecked.
The system comprises a data processing module, a data detection module, a data rechecking module and a database module;
the data processing module is used for carrying out format conversion on the transmission data to be detected, marking the transmission data and then transmitting the transmission data to the data detection module;
the data detection module is used for receiving the transmission data to be detected and checking, and detecting the transmission data through the execution engine by generating an analysis tree and the execution engine;
the data rechecking module is used for manually rechecking the data with unqualified detection results, comparing the rechecking results with the detection results in the data detection module, determining the detection results of the transmission data, and storing the detection results;
the database module is used for storing transmission data to be detected, checked data and transmission data detection results.
The quality inspection system provided by the invention avoids the situation that an administrator can only perform selective inspection on part of the sessions every day and cannot check each communication session, so that missed inspection can occur; and each communication session is automatically checked according to the rule model, so that personnel intervention is not required, and the efficiency is improved.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same; while the invention has been described in detail with reference to the preferred embodiments, those skilled in the art will appreciate that; modifications may be made to the specific embodiments of the invention or equivalents may be substituted for part of the technical features thereof; without departing from the spirit of the invention, it is intended to cover the scope of the invention as claimed.
Claims (12)
1. A method for machine quality inspection based on Java code, characterized in that the method specifically comprises the following steps:
s1, preprocessing data, and extracting features of session data, wherein the feature extraction of the session data comprises session time, session participants, session satisfaction, message content, message roles, message intervals, silence time and co-operation frequency;
s2, packaging data, converting session data into transmission data in json format, generating a use signature for the transmission data, generating a task number, storing the task number in a database, and marking the transmission data as a state to be transmitted;
s3, data transmission, namely transmitting the data to be transmitted stored in the database to a quality inspection server;
s4, checking the received transmission data by the quality inspection server, storing the transmission data in a database, and marking the checked data as to-be-detected;
s5, generating an analysis tree, segmenting the transmission data to be detected by using the analysis tree, setting the segmentation tree as a single task, transmitting the single task to an execution engine for detection, and marking the transmission data in detection as in detection;
s6, the execution engine detects the transmission data in a medium sequence traversing mode, outputs a detection result and marks the detected transmission data as to-be-rechecked;
and S7, storing the detection result in a database, and rechecking the detection result to finish data inspection.
2. A method for machine quality inspection based on Java code according to claim 1, wherein the data transmitted to the quality inspection server in S3 further includes transmission data failed to be transmitted to the quality inspection server, and when transmission data fails to be transmitted to the quality inspection server, the transmission is performed again at the next data transmission.
3. The method for machine quality inspection based on Java code according to claim 1, wherein the specific steps of verifying the transmission data in S4 are: the quality inspection server generates a signature for the received transmission data, and compares the generated signature with the signature of the corresponding data to be transmitted in the database; when the signature comparison is the same, the received data to be transmitted is stored in a database through verification; and when the signature comparison is different, discarding the transmission data and returning the signature comparison and carrying out error prompt.
4. The method for machine quality inspection based on Java code according to claim 1, wherein the specific step of parsing tree generation in S5 is as follows:
s51, scanning part of speech of each word in the rule text of the specific keyword through a text scanner to generate a rule model, and storing the rule model into a database;
s52, obtaining a rule model from the database, checking the rule model to generate a Token list, pressing the contents in the Token list into a stack one by one, and forming an analysis tree according to a specific operator.
5. The method of claim 4, wherein the Token list is a list of rules stored in a database that are sequentially split into recognizable phrases.
6. The method of claim 4, wherein the specific operator comprises a logical operator, a keyword expression, a relational operator expression, and a special operator expression, the parse tree is in a binary tree structure, a root node in the parse tree is a logical operator, and leaf nodes in the parse tree are expressions, the expressions comprising a keyword expression, a relational operator expression, and a special operator expression.
7. The method of claim 6, wherein the logical operator includes "and", "or" and "negation", and "indicates that there is a hit in the case where both the left and right subtrees output True; "OR" indicates that any one of the left and right subtrees outputs True as hit; "inverting" means on an and or basis, and (3) performing operation of taking the result as the opposite result.
8. The method of claim 6, wherein the keyword expression is to detect whether the detection data includes a set keyword; the relational operator expressions are descriptors of "greater than," equal to, "" less than, "" greater than or equal to, "" less than or equal to, "" not equal to, "" most recent, "and" during.
9. The method of claim 1, wherein the execution engine in S6 includes a logic operator execution engine, a keyword execution engine, a relation operator execution engine and a special operator execution engine, the logic operator execution engine processes the transmission data through a logic operator, the keyword execution engine detects whether the transmission data contains keywords described by leaf nodes through a keyword expression, if yes, true is output, otherwise False, the relation operator execution engine processes a root node through a relation operator expression, a left leaf node of the root node is fixed to a field name to be compared, a right leaf node is fixed to a field value to be compared, and the special operator execution engine detects whether the keywords with an adjacency relation in the transmission data meet requirements through a special operator expression.
10. The method for machine quality inspection based on Java code according to claim 9, wherein the specific steps of detecting by the execution engine through a medium-order traversal method are as follows: the execution engine starts traversing the left subtree from the root node of the binary tree, if the node is an AND operator and the left subtree outputs True, the right subtree needs to be checked to be True/False, and if the left subtree and the right subtree are both True, the node is hit; if any subtree is False, the node has no hit; if the node is an or operator and the left subtree outputs False, the right subtree needs to be checked to be True/False, if both the left subtree and the right subtree are False, the node is hit, and if any subtree is True, the node is hit.
11. The method for machine quality inspection based on Java code according to claim 1, wherein the specific steps of rechecking the detected transmission data in S7 are as follows: and (3) performing manual rechecking on the data with unqualified detection results, and when the manual rechecking results are different from the detection results of the execution engine, performing complaint on the manual rechecking results to modify the detection results of the execution engine, and marking the modified transmission data as rechecked.
12. The system is characterized by comprising a data processing module, a data detection module, a data rechecking module and a database module;
the data processing module is used for carrying out format conversion on the transmission data to be detected, marking the transmission data and then transmitting the transmission data to the data detection module;
the data detection module is used for receiving the transmission data to be detected and checking, and detecting the transmission data through the execution engine by generating an analysis tree and the execution engine;
the data rechecking module is used for manually rechecking the data with unqualified detection results, comparing the rechecking results with the detection results in the data detection module, determining the detection results of the transmission data, and storing the detection results;
the database module is used for storing transmission data to be detected, checked data and transmission data detection results.
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