CN112488736A - Method and system for analyzing government affair hotline work order data in field of residential construction - Google Patents
Method and system for analyzing government affair hotline work order data in field of residential construction Download PDFInfo
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- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
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- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
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- G—PHYSICS
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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
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Abstract
The invention provides a method and a system for analyzing government affair hotline work order data in the field of civil construction, wherein a hotline telephone is obtained, voice information is recorded, and the voice data is converted into text information to form a work order; preprocessing the work order data, and describing the time trend change of each work order according to the acceptance time of the work order; extracting data of a work order related area in the work order, and determining the position of a problem related to the work order; constructing a building field professional word bank, segmenting words of work order contents, and constructing a document entry matrix based on a word segmentation result; acquiring a document entry matrix of each work order, identifying text topics, and taking keywords with frequencies higher than a set value under different topics as topic keywords; and generating a work order data analysis report based on the time trend change, the position of the related problem and the topic keyword. The invention can realize time trend analysis, spatial distribution analysis and topic mining of the demand work order, and solves the problem of data analysis in the field of building, especially the analysis of big data.
Description
Technical Field
The invention belongs to the technical field of work order data processing, and particularly relates to a government affair hotline work order data analysis method and system in the field of civil construction.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Along with the improvement of living standard of people, people have higher and higher requirements on the living quality and the living comfort, and more telephones are used for complaints, consultation and the like of the departments of living and building. However, compared with the increasing work order quantity, the analysis of the current work order data is very delayed, valuable information is difficult to extract for department decision, and the data analysis only stays in simple statistical analysis.
Disclosure of Invention
The invention provides a method and a system for analyzing government affair hotline work order data in the field of civil construction, and aims to solve the problems.
According to some embodiments, the invention adopts the following technical scheme:
a method for analyzing work order data of government affairs hotlines in the field of civil construction comprises the following steps:
acquiring a hotline telephone, recording voice information, and converting voice data into text information to form a work order;
preprocessing the work order data, and describing the time trend change of each work order according to the acceptance time of the work order;
extracting data of a work order related area in the work order, and determining the position of a problem related to the work order;
constructing a building field professional word bank, segmenting words of work order contents, and constructing a document entry matrix based on a word segmentation result;
acquiring a document entry matrix of each work order, identifying text topics, and taking keywords with frequencies higher than a set value under different topics as topic keywords;
and generating a work order data analysis report based on the time trend change, the position of the related problem and the topic keyword.
As an alternative embodiment, the specific process of preprocessing the work order data includes: and constructing a noise database, and eliminating data belonging to the noise database in the work order.
As an alternative embodiment, the acceptance time in the work order is extracted, the year, month, week and specific time are determined, and the time trend is analyzed.
As an alternative implementation, a building field professional word bank is constructed, and the specific process of segmenting the work order content includes: constructing a professional word bank in the field of building, wherein the professional word bank comprises a user-defined professional word bank and a stop word bank; the custom professional lexicon refers to words appearing as a whole, and the disabled lexicon refers to nonsense mood auxiliary words.
As an alternative embodiment, the words in the professional wordbase of the building field are stored in rows, each word occupying one row.
As an alternative embodiment, based on the word segmentation result, the specific process of constructing the document entry matrix includes: each participle is used as a single column, and each row represents the work order content and is arranged according to the occurrence times of the participle.
As an alternative embodiment, the specific process of performing text topic identification includes: and (3) obtaining the theme of the work order by using an LDA algorithm, classifying the theme by using an unsupervised machine learning method, and summarizing the theme according to a plurality of key words with the frequency exceeding a set value under each theme.
A data analysis system for a government hot line work order in the field of civil construction comprises:
the work order conversion module is configured to acquire a hotline telephone, record voice information and convert voice data into text information to form a work order;
the time trend analysis module is configured to depict the time trend change of each work order according to the acceptance time of the work orders;
the space analysis module is configured to extract the data of the area related to the work order in the work order and determine the position of the problem related to the work order;
the topic analysis module is configured to construct a field building professional word bank, segment the work order content, construct a document entry matrix based on a segmentation result, acquire the document entry matrix of each work order, identify text topics, and take keywords with frequencies higher than a set value under different topics as topic keywords;
and the analysis report generation module is configured to generate a work order data analysis report based on the time trend change, the position of the related problem and the topic key words.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute the steps of the method for analyzing work order data of a civil field government affairs hotline.
A terminal device comprising a processor and a computer readable storage medium, the processor being configured to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the steps in the method for analyzing the data of the government hot line work order of the civil engineering field.
Compared with the prior art, the invention has the beneficial effects that:
the method and the device can realize time trend analysis of the appeal work orders. The work order quantity change trends of year, month and week are included; meanwhile, detailing the time variation trend to each moment, and depicting the work order quantity variation trend at different moments;
the method can draw the number of the work orders processed in a specific urban area, and is beneficial to later-stage area management and area analysis;
the invention can mine the subject of the appeal work order, realize the automatic clustering of the work order content, contribute to clustering of the same work order, find common problems, or remove repeated work orders.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
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.
FIGS. 1(a) - (c) are schematic diagrams of several time trend analyses in this example;
FIG. 2 is a schematic view of urban distribution in this embodiment;
FIG. 3 is a schematic diagram of the work order topic mining process in this embodiment;
FIG. 4 is a schematic process diagram of the present embodiment.
The specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
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, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
A method for analyzing work order data of government affairs hotlines in the field of civil construction is applied to the government affairs hotlines in the field of civil construction, and firstly, the hotline processing flow is briefly explained, namely: based on the application scene (namely the civil field government affair hotline) of the embodiment, the citizen dials 12345 to express the appeal, the citizen hotline converts the citizen appeal into work order text information and transfers the work order text information to the civil field government affair hotline platform, and the basic hotline processing flow is as follows:
the staff provides manual service, answers the call and records the user requirement information.
The existing voice recognition technology is popular, can communicate with a user through an intelligent customer service, records the voice of the user, and converts voice data into text information through a certain voice recognition framework.
And the staff of the 12345 citizen hotline can form the recorded citizen appeal into a work order and distribute the work order to related units, wherein the work order comprises a house and a digital center for urban and rural construction and is responsible for processing the work order in the field of residential construction.
As shown in fig. 4, the method for analyzing work order data of government affairs hotline in the civil engineering field of the embodiment specifically includes the following steps:
(1) data collection: based on the hotline process flow, the work order data comes from 12345 transfer work orders.
(2) Data processing:
(i) processing of time variables: in the work order data, there are acceptance time variables of the work order in the format of year-month-day: dividing into: and (e.g. 2019-12-3100: 00: 00), the year, month, week and specific time of the work order acceptance time can be extracted, so that the time trend can be analyzed.
(ii) Processing of spatial variables: in the work order data, a list of variables is the urban area where the citizen reflects the problem
(iii) Processing the work order content: the method comprises the steps of constructing a building field professional word bank, segmenting words and constructing a document entry matrix.
In the present embodiment, a work order of a homemade business in Jinan, Shandong province is taken as an example for explanation.
12345 the converted work order has a specific format, which is divided into the following cases:
the first format is as follows: "12345 Hanqing transfer, caller reflects: the owners of Baoli Huafu 2 areas in the shade area of Chinese scholartree, the whole area of the district are handed over to the house in the near future, the natural gas alarms are installed in succession, but the operators charge 270 yuan (each family) for the alarms, and consult whether the 270 yuan for the alarms needs to be paid, hope that relevant units implement treatment and request treatment. (Jihua gas, workers of Huatong project department, installation telephone 15168813826)12345 recording time of 2018-06-2821: 27:53 transfer time of 2018-07-0109: 17:07 "
In general, the contents of "12345 XX transfer", "caller id reaction", "wish related units to implement processing, please process" and "12345 time entered, transfer time" appear in the work order contents, and the contents are not valuable for determining the work order responsibility unit and belong to data noise, so that the contents are rejected.
Besides, as shown in format two, there are "XX feedback" and "XX backspacing" contents in part of the work order, and this part also has no practical meaning. And then the samples are removed.
And a second format: "12345 jia hongwei transfer" jia woman incoming call reflection: in the district release route 77 yuan, building a unit 2903 alone in building 11 th building of the national platform district, the main lying bay window leaks rain, requires maintenance as soon as possible, and hopes that relevant units are implemented and processed. Government hotline feedback on the calendar: back of the housing guarantee management office under the calendar: in the fifteenth property, the "management method of properties in Jinan City" implemented 2/1 in 2015, quality defects appear in the warranty period, and real estate development enterprises are responsible for warranty. 12345 recording time 2018-06-2519: 14:55 conversion time 2018-07-0109: 57:17 "
The following are the detailed steps of the work order content processing:
(a) the establishment of an effective word bank is the first premise for realizing reasonable word segmentation. The patent constructs a professional word bank in the field of building and construction, and the professional word bank comprises a user-defined professional word bank and a stop word bank. The user-defined professional word bank means that some words appear as a whole, such as a cell name and a road name, and item words reflecting specific problems, such as heat resistance of a heater; disabling the thesaurus refers to removing meaningless words, such as "the", "o", etc.
The construction method of the word stock adopts a back-to-back artificial coding method. And inviting professionals in the building field to read a large number of 12345 work orders respectively and perform artificial word segmentation. After word segmentation, the word segmentation results of each person are compared, and word segmentation results which are agreed by everyone are sorted out through negotiation.
The specific form of the thesaurus is to form a txt document in which each word occupies a line.
The method has the advantages that the method has a professional word bank in the field of building, so that accurate word segmentation can be realized, and a foundation is laid for later model training.
(b) The work order content word segmentation is carried out, and the field applied by the patent is the living building field, so the patent uses a professional word bank in the living building field to carry out scientific and reasonable word segmentation.
The word segmentation is as follows:
original work orders: and 12345 Jia ambitious transfer, namely the incoming call of the Jia women reflects: in the district release route 77 yuan, building a unit 2903 alone in building 11 th building of the national platform district, the main lying bay window leaks rain, requires maintenance as soon as possible, and hopes that relevant units are implemented and processed. Government hotline feedback on the calendar: back of the housing guarantee management office under the calendar: in the fifteenth property, the "management method of properties in Jinan City" implemented 2/1 in 2015, quality defects appear in the warranty period, and real estate development enterprises are responsible for warranty. 12345 recording time of 2018-06-2519: 14:55 transferring time of 2018-07-0109: 57:17
Work order after word segmentation: the single unit 2903 of the building in No. 11 building in No. 77 Yuan of the Ji Xitai district under the calendar requires maintenance as soon as possible
(c) Constructing a document entry matrix
After the work order content is divided into words, the words are embodied in the form of words, and then a document entry matrix can be constructed, wherein each word is used as a single column, and each row represents the work order content and appears in the form of the occurrence times of the words.
(3) Work order data analysis (the result takes 2019 data as an example and is explained)
A time trend analysis
According to the time dimension extracted in the data: and describing the time trend change of the work order by year, month, week and time.
B space trend analysis
And drawing the urban distribution of the work orders according to the urban variables in the data, as shown in FIG. 2.
C work order topic mining
The method comprises the steps of using LDA (latent Dirichlet allocation) to identify text topics, and dividing mass work order data into several classes or dozens of classes by an unsupervised machine learning method. In fig. 3, in this embodiment, each topic corresponds to the 7 keywords with the highest frequency of occurrence, and according to the keywords, the subject of the topic can be summarized.
The LDA algorithm mentioned, LDA, is based on a bag-of-words model, i.e. taking into account the number of times a word occurs, and not the order of occurrence. The basic algorithm is as follows: assuming that there are M articles in the corpus, the topic distribution under each article is a Multinomial distribution sampled from a Dirichlet (Dirichlet) prior distribution with a parameter, and the word distribution under each topic is a Multinomial distribution sampled from a Dirichlet (Dirichlet) prior distribution with a parameter. For the nth word in an article, a topic is selected or sampled from the Multinomial distribution (topic distribution) of each topic appearing in the article, and then a word is selected or sampled from the Multinomial distribution (word distribution) of the word corresponding to the topic. The random generation process is repeated continuously until all the M articles are generated, and a theme and keyword matrix is formed.
So far, the data analysis of the government hot line in the civil construction field can generate work order reports of the month, the quarter and the year, and the report contents comprise time trend analysis, space pattern analysis and hot topic identification.
Through the scheme of the embodiment, the time trend analysis of the appeal work order can be realized. The work order quantity change trends of year, month and week are included; meanwhile, the time variation trend is detailed to 24 moments of the day, and the work order quantity variation trend at 24 moments is depicted.
Spatial distribution of the appeal work order may also be achieved. The number of work orders processed for a particular urban area is depicted.
And the theme mining of the appeal work order can be realized, and the automatic clustering of the work order content is realized.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by 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 (10)
1. A method for analyzing government affair hotline work order data in the field of civil construction is characterized by comprising the following steps: the method comprises the following steps:
acquiring a hotline telephone, recording voice information, and converting voice data into text information to form a work order;
preprocessing the work order data, and describing the time trend change of each work order according to the acceptance time of the work order;
extracting data of a work order related area in the work order, and determining the position of a problem related to the work order;
constructing a building field professional word bank, segmenting words of work order contents, and constructing a document entry matrix based on a word segmentation result;
acquiring a document entry matrix of each work order, identifying text topics, and taking keywords with frequencies higher than a set value under different topics as topic keywords;
and generating a work order data analysis report based on the time trend change, the position of the related problem and the topic keyword.
2. The method for analyzing the data of the government affair hotline work order of the civil area as claimed in claim 1, wherein: the specific process for preprocessing the work order data comprises the following steps: and constructing a noise database, and eliminating data belonging to the noise database in the work order.
3. The method for analyzing the data of the government affair hotline work order of the civil area as claimed in claim 1, wherein: and extracting the acceptance time in the work order, determining the year, month, week and specific time, and analyzing the time trend.
4. The method for analyzing the data of the government affair hotline work order of the civil area as claimed in claim 1, wherein: the method comprises the following specific processes of constructing a professional word bank in the building field and segmenting work order contents, wherein the specific processes comprise the following steps: constructing a professional word bank in the field of building, wherein the professional word bank comprises a user-defined professional word bank and a stop word bank; the custom professional lexicon refers to words appearing as a whole, and the disabled lexicon refers to nonsense mood auxiliary words.
5. The method for analyzing the data of the civil field government hot line work order as claimed in claim 4, wherein: and the words in the professional word library in the civil construction field are stored in rows, and each word occupies one row.
6. The method for analyzing the data of the government affair hotline work order of the civil area as claimed in claim 1, wherein: based on the word segmentation result, the specific process of constructing the document entry matrix comprises the following steps: each participle is used as a single column, and each row represents the work order content and is arranged according to the occurrence times of the participle.
7. The method for analyzing the data of the government affair hotline work order of the civil area as claimed in claim 1, wherein: the specific process of identifying the text theme comprises the following steps: and (3) obtaining the theme of the work order by using an LDA algorithm, classifying the theme by using an unsupervised machine learning method, and summarizing the theme according to a plurality of key words with the frequency exceeding a set value under each theme.
8. The utility model provides a building field government affair hotline work order data analysis system which characterized by: the method comprises the following steps:
the work order conversion module is configured to acquire a hotline telephone, record voice information and convert voice data into text information to form a work order;
the time trend analysis module is configured to depict the time trend change of each work order according to the acceptance time of the work orders;
the space analysis module is configured to extract the data of the area related to the work order in the work order and determine the position of the problem related to the work order;
the topic analysis module is configured to construct a field building professional word bank, segment the work order content, construct a document entry matrix based on a segmentation result, acquire the document entry matrix of each work order, identify text topics, and take keywords with frequencies higher than a set value under different topics as topic keywords;
and the analysis report generation module is configured to generate a work order data analysis report based on the time trend change, the position of the related problem and the topic key words.
9. A computer-readable storage medium characterized by: a plurality of instructions stored therein, the instructions adapted to be loaded by a processor of a terminal device and to perform the steps of a method for data analysis of a civil field government hot-line work order according to any one of claims 1 to 7.
10. A terminal device is characterized in that: the system comprises a processor and a computer readable storage medium, wherein the processor is used for realizing instructions; the computer readable storage medium is used for storing a plurality of instructions adapted to be loaded by a processor and to execute the steps of a method for data analysis of a civil field government hot-line work order according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114510566A (en) * | 2021-11-29 | 2022-05-17 | 上海市黄浦区城市运行管理中心(上海市黄浦区城市网格化综合管理中心、上海市黄浦区大数据中心) | Hot word mining, classifying and analyzing method and system based on work order |
| CN115687577A (en) * | 2023-01-04 | 2023-02-03 | 交通运输部公路科学研究所 | Road transportation normalized problem appeal discovery method and system |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140278769A1 (en) * | 2013-03-12 | 2014-09-18 | Oracle International Corporation | Method and system for performing trend analysis of themes in social data |
| CN107729919A (en) * | 2017-09-15 | 2018-02-23 | 国网山东省电力公司电力科学研究院 | In-depth based on big data technology is complained and penetrates analysis method |
| CN107908716A (en) * | 2017-11-10 | 2018-04-13 | 国网山东省电力公司电力科学研究院 | 95598 work order text mining method and apparatus of word-based vector model |
| CN108470282A (en) * | 2018-03-26 | 2018-08-31 | 国家电网公司客户服务中心 | Work order intelligent method for classifying is complained by Customer Service Center |
| CN109389418A (en) * | 2018-08-17 | 2019-02-26 | 国家电网有限公司客户服务中心 | Electric service client's demand recognition methods based on LDA model |
| CN110032643A (en) * | 2019-04-02 | 2019-07-19 | 上海建工四建集团有限公司 | A kind of building maintenance work order analysis method, device, storage medium and client |
| CN110955777A (en) * | 2019-12-11 | 2020-04-03 | 国网河北省电力有限公司电力科学研究院 | Method for improving customer service quality based on 95598 work order |
| CN111355849A (en) * | 2018-12-24 | 2020-06-30 | 北京国双科技有限公司 | Telephone traffic work order processing method and device |
| CN111783438A (en) * | 2020-05-22 | 2020-10-16 | 贵州电网有限责任公司 | Hot word detection method for realizing work order analysis |
-
2020
- 2020-12-15 CN CN202011474965.6A patent/CN112488736A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140278769A1 (en) * | 2013-03-12 | 2014-09-18 | Oracle International Corporation | Method and system for performing trend analysis of themes in social data |
| CN107729919A (en) * | 2017-09-15 | 2018-02-23 | 国网山东省电力公司电力科学研究院 | In-depth based on big data technology is complained and penetrates analysis method |
| CN107908716A (en) * | 2017-11-10 | 2018-04-13 | 国网山东省电力公司电力科学研究院 | 95598 work order text mining method and apparatus of word-based vector model |
| CN108470282A (en) * | 2018-03-26 | 2018-08-31 | 国家电网公司客户服务中心 | Work order intelligent method for classifying is complained by Customer Service Center |
| CN109389418A (en) * | 2018-08-17 | 2019-02-26 | 国家电网有限公司客户服务中心 | Electric service client's demand recognition methods based on LDA model |
| CN111355849A (en) * | 2018-12-24 | 2020-06-30 | 北京国双科技有限公司 | Telephone traffic work order processing method and device |
| CN110032643A (en) * | 2019-04-02 | 2019-07-19 | 上海建工四建集团有限公司 | A kind of building maintenance work order analysis method, device, storage medium and client |
| CN110955777A (en) * | 2019-12-11 | 2020-04-03 | 国网河北省电力有限公司电力科学研究院 | Method for improving customer service quality based on 95598 work order |
| CN111783438A (en) * | 2020-05-22 | 2020-10-16 | 贵州电网有限责任公司 | Hot word detection method for realizing work order analysis |
Non-Patent Citations (2)
| Title |
|---|
| 郭小冰等: "大数据在95598故障报修工单分析中的应用", 《电力需求侧管理》 * |
| 陈阳等: "投诉数据智能挖掘分类管理系统", 《数字技术与应用》 * |
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| CN114510566A (en) * | 2021-11-29 | 2022-05-17 | 上海市黄浦区城市运行管理中心(上海市黄浦区城市网格化综合管理中心、上海市黄浦区大数据中心) | Hot word mining, classifying and analyzing method and system based on work order |
| CN115687577A (en) * | 2023-01-04 | 2023-02-03 | 交通运输部公路科学研究所 | Road transportation normalized problem appeal discovery method and system |
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