CN112215260B - Power grid training resource classification updating method and system - Google Patents
Power grid training resource classification updating method and system Download PDFInfo
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- G06F18/20—Analysing
- G06F18/24—Classification techniques
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
- G06F16/9014—Indexing; Data structures therefor; Storage structures hash tables
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/906—Clustering; Classification
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention discloses a method and a system for classified updating of power grid training resources, wherein the method comprises the following steps: classifying the power grid training resources by combining a middle graph classification method according to training professional subjects to which the power grid training resources belong; obtaining a retrieval result set of the power grid training resources in the current classification result according to the resource retrieval words, and calculating a ranking coefficient of each retrieval result; performing Hash operation on the resource search word and the search result set to obtain a comparison value of the resource search word and the search result; and obtaining the association degree of the power grid training resources and the class according to the sorting coefficient and the comparison value, and updating the current classification result according to the comparison with the association degree threshold value. By evaluating and judging the resource retrieval frequency, the resource sequencing and the accuracy of the resource classification, the resource classification is optimized, and the classification catalog is adjusted in time for the resources and the classifications with low relevance, so that the resource classification precision and the resource utilization rate are improved.
Description
Technical Field
The invention relates to the technical field of resource classification, in particular to a power grid training resource classification updating method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The training of the technical skills of the employees is usually carried out in a mode of combining offline and online, the technical skill level of the employees in actual work is enhanced through organization concentration or practice training of special technical skills in the offline aspect, and the theoretical knowledge of the technical skills is learned online in the online aspect by means of a PC or a mobile application platform. The electric wire netting is as technology intensive trade, and each link such as transformer, transmission of electricity, distribution all needs the operation workman to have comparatively skilled operating capability, has higher requirement to workman's theoretical knowledge, real operating capability, and the violation of rules and regulations leads to equipment to damage, causes the casualties, electric wire netting power failure scheduling problem to the great extent, and therefore, in the electric wire netting enterprise, it is especially important to develop professional theoretical study and technical skill training towards worker organization.
In the aspect of education resources, along with the development of information technology, the types and forms of the education information resources are increasingly abundant, and the education information resources include but are not limited to courseware, unit teaching design, videos, case libraries and the like; meanwhile, with the generalization and the usability of the educational information resource making technology, the number of teaching information resources is increased in a large amount, so that the problem of how to efficiently and scientifically manage the resources exists.
The traditional education information resource management mode is distributed management, and takes individual persons or small groups of teachers and trainers or teaching and research groups as units to carry out resource development, arrangement, iteration, management and other work in a small range.
The information resources of the power grid industry are different from other industries, the resources of the power grid industry mainly aim at actual power production and mainly aim at practical technical skill operation, and the traditional industry resources mainly aim at theory and basic knowledge; in the existing resource classification methods, such as a Chinese chart classification method, a subject classification method and the like, basic knowledge classification is mainly used, so that the practical attribute of the resource cannot be well embodied, and the classification requirement of training resources in the power grid industry cannot be met; in addition, aiming at the problem of poor classification precision of training resources in the power grid industry, if the resource classification is not clear or the classification is not accurate, the resource utilization rate is not high, the resource retrieval accuracy rate is low, and resources are wasted in an idle mode.
Disclosure of Invention
In order to solve the problems, the invention provides a power grid training resource classification updating method and a power grid training resource classification updating system.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides a power grid training resource classification updating method, which includes:
classifying the power grid training resources by combining a middle graph classification method according to training professional subjects to which the power grid training resources belong;
obtaining a retrieval result set of the power grid training resources in the current classification result according to the resource retrieval words, and calculating a ranking coefficient of each retrieval result;
performing Hash operation on the resource search word and the search result set to obtain a comparison value of the resource search word and the search result;
and obtaining the association degree of the power grid training resources and the class according to the sorting coefficient and the comparison value, and updating the current classification result according to the comparison with the association degree threshold value.
In a second aspect, the present invention provides a power grid training resource classification updating system, including:
the classification module is used for classifying the power grid training resources by combining a middle map classification method according to training professional subjects to which the power grid training resources belong;
the sorting module is used for obtaining a retrieval result set of the power grid training resources in the current classification result according to the resource retrieval words and calculating a sorting coefficient of each retrieval result;
the comparison module is used for carrying out Hash operation on the resource search word and the search result set to obtain a comparison value of the resource search word and the search result;
and the updating module is used for obtaining the association degree of the power grid training resources and the class of the power grid training resources according to the sorting coefficient and the comparison value, and updating the current classification result according to the comparison with the association degree threshold value.
In a third aspect, the present invention provides an electronic device comprising a memory and a processor, and computer instructions stored on the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method of the first aspect is performed.
In a fourth aspect, the present invention provides a computer readable storage medium for storing computer instructions which, when executed by a processor, perform the method of the first aspect.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, a mode of combining a traditional classification method and power grid resource characteristics is adopted according to the power grid enterprise training characteristics, a classification method meeting power grid training resources is provided in a targeted mode, the problems of low resource utilization rate, value waste, management confusion and the like caused by extensive resource management and non-uniform classification standards in the process of power grid enterprise staff training resource management are solved, the special requirements of the power grid industry are met, the resource classification precision is improved, the resource utilization rate is improved, and the resource value is excavated.
The invention adopts a front-end and back-end classification method to classify the power grid resources according to the professional categories, fully embodies post professional resource classification and resource content classification by combining a middle graph classification method, shows the relationship of different subject classifications by the front end, ensures scientific classification of the resource content by the back end, and improves the resource retrieval accuracy.
According to the invention, by evaluating and judging the resource retrieval frequency, the resource sequencing and the accuracy of resource classification, a dynamic analysis algorithm is provided, so that the resource classification is optimized, the classification catalogue is adjusted in time for the resources and the classifications with low relevance, and the problems of low resource utilization rate, low resource retrieval accuracy and resource vacancy waste caused by unclear resource classification or inaccurate classification are solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a flowchart of a classification updating method for power grid training resources according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of classification of power grid training resources provided in embodiment 1 of the present invention.
The specific implementation mode is as follows:
the invention is further explained by the following embodiments in conjunction with the drawings.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and it should be understood that the terms "comprises" and "comprising", and any variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiments and features of the embodiments of the invention may be combined with each other without conflict.
Example 1
As shown in fig. 1, the present embodiment provides a method for updating power grid training resource classification, including:
s1: classifying the power grid training resources by combining a middle graph classification method according to training professional subjects to which the power grid training resources belong;
s2: obtaining a retrieval result set of the power grid training resources in the current classification result according to the resource retrieval words, and calculating a ranking coefficient of each retrieval result;
s3: performing Hash operation on the resource search word and the search result set to obtain a comparison value of the resource search word and the search result;
s4: and obtaining the association degree of the power grid training resources and the class according to the sorting coefficient and the comparison value, and updating the current classification result according to the comparison with the association degree threshold value.
In step S1, a front-end-back-end classification method is adopted in this embodiment, as shown in fig. 2, the front end is divided according to the power grid posts related to the power grid training resources, and is used to display a resource classification system, the system displays the relationships of different subject classifications, the classification names are clear and easy to understand, the systematicness is strong, and the method is helpful for uploading and managing resources, and performing statistics and analysis; the method is suitable for determining the resource attribution type when a resource uploader uploads the resources;
in this embodiment, the front-end classification includes power grid scheduling and automation, power transformation operation and maintenance, converter station operation and maintenance, power transformation overhaul and test, relay protection, intelligent distribution network operation and maintenance, power marketing, power transmission line operation and maintenance, power transmission line engineering, hydropower operation and maintenance, thermal power operation and maintenance, communication operation and maintenance, information system overhaul and maintenance, and the like.
The back end adopts a middle map classification method which is mainly applied to the classification of paper book resources in a library and is a general book classification tool, mainly determines a classification system according to the characteristics of book data and general to specific compiling principles from general to classification, classifies categories by a knowledge system and a subject system, classifies books and documents from a macroscopic view and is used for meeting the requirements of various book information mechanisms on sequencing and searching of the books and the documents;
the middle graph classification method focuses on more detailed resource classification, the resource classification level reaches 5 layers, and relates to specific content and classification granularity of resources, when the middle graph classification method is used for classification, the classification system of the resources is not obvious, but the classification of the content is more specific, so that the method is suitable for resource management responsibility to perform specific resource management, ensures that the resources can perform scientific classification on the content in the background, and improves the accuracy of resource retrieval;
due to the fact that the classification of the middle graph classification method is relatively detailed, the granularity is small, the quantity is large, the side key points of training resources of power grid enterprise workers are different, the industrial characteristics are fully considered when the rear-end middle graph classification method is designed, all classification levels are reserved for several categories with high use frequency, such as TK energy and power engineering, TM electrical technology, TN electronic technology, communication technology, TP automation technology, computer technology and the like in the middle graph classification method, and only two classification levels are reserved for other categories, such as B philosophy religion, C social science general theory and the like.
In the embodiment, in order to ensure more accurate description of resources and reflect the content attributes and practical values of staff training resources of a power grid enterprise, a tag library with the characteristics of the power grid industry is provided on the basis of traditional tags such as key contents, authors and the like;
the tag libraries are classified into three categories: the first type is a general label, such as a general label of an author, a date and the like, and is used for marking basic attribution information of resources so as to be convenient for a resource searcher to manage;
the second type is a resource type label, which labels the resource type, the common resource type includes unit teaching design, teaching materials (lecture), course standard, courseware, culture/training scheme and operation instruction book, etc, which is convenient for counting and analyzing various resources in the system;
the third type is a practical label, because the classification method can only describe the static attribute of the resource, and more training resources of the staff of the power grid enterprise are focused on the dynamic contents of specific operation and the like in the power grid production process, in order to meet the special requirements of the training resources of the staff of the power grid enterprise, the practical label is designed, such as patrol, inspection, installation and debugging, rescue and treatment, test and test, operation and maintenance, fault treatment, infrastructure construction, marketing service, measurement and accounting, operation and maintenance management, overhaul and management and the like.
The general label library is mainly used for marking basic attributes of resources, and the categories of the general labels are shown in table 1:
TABLE 1 general tag library
In the embodiment, in order to ensure the practicability and accuracy of the classification result and the tag library, the resource classification is optimized and updated by evaluating and judging the resource retrieval frequency, the resource sequencing and the accuracy of the resource classification;
in this embodiment, retrieving resources by using a keyword according to a user, and performing relevance measurement on the current classification of the resources according to a retrieval result specifically includes:
obtaining a keyword S i And its search result set { R };
calculating each retrieval result R in the retrieval result set i Coefficient of corresponding sorting result K i That is, the resource is located at the sequencing position according to each retrieval of the user;
will S i And R i Carrying out Hash operation to obtain a comparison value M of the keyword and the retrieval result i Reflecting the relevance of the keywords and the retrieval result;
accumulating retrieval times i, and calculating the association degree Q of the current resource and the classification;
q is a resource and classification association coefficient and reflects the association tightness of the resource and the classification; k is a resource retrieval result sorting coefficient; m is a retrieval keyword and a result comparison; and i is the accumulated retrieval times of the resource.
And sequentially measuring and calculating the association degree of each resource and each classification, and adjusting and updating the classification catalog for the resources and the classifications with low association degree in real time.
Example 2
The embodiment provides a power grid training resource classification updating system, including:
the classification module is used for classifying the power grid training resources by combining a middle map classification method according to training professional subjects to which the power grid training resources belong;
the sorting module is used for obtaining a retrieval result set of the power grid training resources in the current classification result according to the resource retrieval words and calculating a sorting coefficient of each retrieval result;
the comparison module is used for carrying out Hash operation on the resource search word and the search result set to obtain a comparison value of the resource search word and the search result;
and the updating module is used for obtaining the association degree of the power grid training resources and the class of the power grid training resources according to the sorting coefficient and the comparison value, and updating the current classification result according to the comparison with the association degree threshold value.
It should be noted that the above modules correspond to steps S1 to S4 in embodiment 1, and the above modules are the same as the examples and application scenarios realized by the corresponding steps, but are not limited to the disclosure in embodiment 1. It should be noted that the modules described above as part of a system may be implemented in a computer system such as a set of computer-executable instructions.
In further embodiments, there is also provided:
an electronic device comprising a memory and a processor and computer instructions stored on the memory and executed on the processor, the computer instructions when executed by the processor performing the method of embodiment 1. For brevity, no further description is provided herein.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processor, a digital signal processor DSP, an application specific integrated circuit ASIC, an off-the-shelf programmable gate array FPGA or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include both read-only memory and random access memory and may provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.
A computer readable storage medium storing computer instructions which, when executed by a processor, perform the method of embodiment 1.
The method in embodiment 1 may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, etc. as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and combines hardware thereof to complete the steps of the method. To avoid repetition, it is not described in detail here.
Those of ordinary skill in the art will appreciate that the various illustrative elements, i.e., algorithm steps, described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (8)
1. A power grid training resource classification updating method is characterized by comprising the following steps:
a front-end-rear-end classification method is adopted, the front end is divided according to the training professional subject to which the power grid training resources belong, and the rear end is used for classifying the power grid training resources by a middle graph classification method;
the method comprises the following steps of classifying power grid training resources for one time according to training professional subjects, and dividing the power grid training resources into power grid scheduling and automation, power transformation operation and maintenance, converter station operation and maintenance, power transformation overhaul and test, relay protection, intelligent distribution network operation and maintenance, power marketing, power transmission line operation and maintenance, power transmission line engineering, water and electricity operation and maintenance, thermal power operation and maintenance, communication operation and maintenance and information system overhaul and maintenance;
reserving all classification levels for the classes with high use frequency in the middle graph classification method, and reserving secondary classification levels for other classes;
obtaining a retrieval result set of the power grid training resources in the current classification result according to the resource retrieval words, and calculating a ranking coefficient of each retrieval result, wherein the ranking coefficient specifically comprises the following steps: calculating each retrieval result R in the retrieval result set i Coefficient K of corresponding sorting result i That is, the resource is located at the sequencing position according to each retrieval of the user;
performing Hash operation on the resource search word and the search result set to obtain a comparison value of the resource search word and the search result;
obtaining the association degree of the power grid training resources and the categories according to the sorting coefficient and the comparison value, wherein the association degree Q is;
wherein K is a ranking coefficient; m is a comparison value of the resource search term and the search result; i is the accumulated retrieval times of the resources;
and updating the current classification result according to the comparison with the relevance threshold.
2. The method as claimed in claim 1, wherein the power grid training resources are classified once according to training professional subjects, and the classification result is associated with the category in the middle graph classification method.
3. The classification updating method for power grid training resources as claimed in claim 1, wherein a tag library is constructed for the power grid training resources, and the tag library comprises a general tag library, a resource type tag library and a utility type tag library.
4. A power grid training resource classification updating method as claimed in claim 3, wherein the general label library comprises author, date, subject, description, format, authority and language;
or the like, or a combination thereof,
the resource type label library comprises unit teaching designs, teaching materials, lectures, course standards, courseware, culture/training schemes and operation instruction books;
or the like, or, alternatively,
the practical label library comprises patrol, overhaul, installation and debugging, rescue and treatment, test, operation and maintenance, fault treatment, capital construction, marketing service, metering accounting, operation and maintenance management and overhaul management.
5. The power grid training resource classification updating method as claimed in claim 1, wherein i searches are performed on each power grid training resource accumulation, and the correlation of the i searches is averaged.
6. A power grid training resource classification updating system is characterized by comprising:
the classification module is used for adopting a front-end-rear-end classification method, the front end is divided according to the training professional subject to which the power grid training resources belong, and the rear end adopts a middle map classification method to classify the power grid training resources;
the method comprises the following steps of classifying power grid training resources at one time according to training professional subjects, and dividing the power grid training resources into power grid scheduling and automation, power transformation operation and maintenance, converter station operation and maintenance, power transformation overhaul and test, relay protection, intelligent distribution network operation and maintenance, electric power marketing, power transmission line operation and maintenance, power transmission line engineering, hydropower operation and maintenance, thermal power operation and maintenance, communication operation and maintenance and information system overhaul and maintenance;
reserving all classification levels for the classes with high use frequency in the middle graph classification method, and reserving secondary classification levels for other classes;
the sorting module is used for obtaining a retrieval result set of the power grid training resources in the current classification result according to the resource retrieval words and calculating a sorting coefficient of each retrieval result, and the sorting module specifically comprises the following steps: calculating each retrieval result R in the retrieval result set i Coefficient of corresponding sorting result K i That is, the resource is located at the sequencing position according to each retrieval of the user;
the comparison module is used for carrying out Hash operation on the resource search word and the search result set to obtain a comparison value of the resource search word and the search result;
the updating module is used for obtaining the association degree of the power grid training resources and the categories of the power grid training resources according to the sequencing coefficient and the comparison value, and the association degree Q is;
wherein K is a ranking coefficient; m is a comparison value of the resource search term and the search result; i is the accumulated retrieval times of the resources;
and updating the current classification result according to the comparison with the relevance threshold.
7. An electronic device comprising a memory and a processor and computer instructions stored on the memory and executed on the processor, the computer instructions when executed by the processor performing the method of any of claims 1-5.
8. A computer-readable storage medium storing computer instructions which, when executed by a processor, perform the method of any one of claims 1 to 5.
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| CN101753445A (en) * | 2009-12-23 | 2010-06-23 | 重庆邮电大学 | Fast flow classification method based on keyword decomposition hash algorithm |
| CN105426529A (en) * | 2015-12-15 | 2016-03-23 | 中南大学 | Image retrieval method and system based on user search intention positioning |
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| CN101753445A (en) * | 2009-12-23 | 2010-06-23 | 重庆邮电大学 | Fast flow classification method based on keyword decomposition hash algorithm |
| CN105426529A (en) * | 2015-12-15 | 2016-03-23 | 中南大学 | Image retrieval method and system based on user search intention positioning |
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