CN112632368A - Method for notifying, issuing, personalized recommending and attention reminding of OA (office automation) system of colleges and universities - Google Patents
Method for notifying, issuing, personalized recommending and attention reminding of OA (office automation) system of colleges and universities Download PDFInfo
- Publication number
- CN112632368A CN112632368A CN202011392740.6A CN202011392740A CN112632368A CN 112632368 A CN112632368 A CN 112632368A CN 202011392740 A CN202011392740 A CN 202011392740A CN 112632368 A CN112632368 A CN 112632368A
- Authority
- CN
- China
- Prior art keywords
- notification
- information
- label
- attention
- colleges
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000004364 calculation method Methods 0.000 claims abstract description 27
- 238000000605 extraction Methods 0.000 claims abstract description 14
- 238000002372 labelling Methods 0.000 claims abstract description 3
- 239000003086 colorant Substances 0.000 claims description 10
- 239000000284 extract Substances 0.000 claims description 4
- 238000010586 diagram Methods 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 230000007115 recruitment Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- 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
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9538—Presentation of query results
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Marketing (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Computational Linguistics (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Computational Biology (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a college OA system notification release personalized recommendation and attention reminding method which comprises six steps of basic information input, identity label extraction, notification information subject term extraction, relevance grade setting, relevance calculation and color labeling output of notification information.
Description
Technical Field
The invention relates to modern intelligent office information management, in particular to a method for notifying and issuing personalized recommendation and attention reminding by an OA system of colleges and universities.
Background
Office Automation (OA for short) is a novel Office mode formed by applying modern technologies such as computers and communication to a traditional Office mode, and replaces part of traditional manual or repetitive business activities of Office workers to process Office affairs and business information with high quality and high efficiency, thereby realizing high-efficiency utilization of information resources. However, the existing OA system is not intelligent and humanized enough, massive information is not screened according to importance or relevance, and a user is easy to confuse, omit and forget important notification information under the condition that a lot of complicated information is submerged, so that the working efficiency and the working quality are reduced.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a method for issuing personalized recommendation and attention reminding by an OA system of a college according to the relevance degree of an identity information label and a notification information subject term.
The technical scheme is as follows: the invention discloses a method for notifying and issuing personalized recommendation and attention reminding by an OA system of a college, which comprises the following steps of:
(1) recording basic information of the instructor into an OA system;
(2) the OA system extracts basic information of the teaching staff according to labels, wherein the labels include but are not limited to gender, age, position, title, political face and work type;
(3) the OA system extracts the subject term of the notification information issued by the school mobile terminal;
(4) setting grades in a percentage mode according to a calculation criterion of the correlation degree, and labeling by using different colors;
(5) performing matching calculation by using a similarity recommendation method of relevance calculation;
(6) and (4) matching the calculation result and the grade setting standard according to the correlation degree, and outputting information of different colors, so that the information is more visual and clear.
The step (1) comprises the following steps: and inputting basic information of the instructor into the OA system.
The step (2) comprises the following steps: based on the input basic information of the instructor, the OA system automatically completes the label extraction of the basic information of the instructor.
The step (3) comprises the following steps: according to the notification information issued by the school mobile terminal, the OA system automatically completes the extraction of the subject term of the notification information issued by the school mobile terminal.
The step (4) comprises the following steps: and setting the grade in a percentage mode according to the calculation criterion of the correlation degree, and marking by using different colors.
The step (5) comprises: and performing matching calculation by using a similarity recommendation method of relevance calculation based on the extracted basic information labels and notification information subject terms of the teaching staff.
The matching calculation is mainly divided into two types of single label and multi-label, and the calculation formula is as follows:
single label
Wherein P isojA label for indicating basic information of extracted teaching staff; pijA topic word label for indicating the extraction of the notification information; when P is presentoj＝PijThen, the output S1i1, indicates correlation, with focus; when P is presentoj≠PijThen, the output S1i0, meaning irrelevant, without concern;
multi-label
Wherein WjA label for indicating basic information of extracted teaching staff; sjA topic word label for indicating the extraction of the notification information; calculating the weight according to a formulaAnd the attention is judged.
The step (6) comprises: outputting information personalized display of different colors according to the correlation matching calculation result and the grade setting standard; green indicates that the notification does not need attention, orange indicates that the notification needs to be focused on, and yellow indicates that the notification has content related to the notification and needs attention.
Has the advantages that: compared with the prior art, the invention has the following advantages: 1. according to the relevance of the information labels of the teaching staff and the notification information subject words, the receiver is automatically reminded to look up and pay attention to the information after the information is published accurately, so that the omission of important information is reduced, and the working efficiency is improved; 2. different colors are marked according to the relevance of the notification information for distinguishing, so that the notification information is visual and clear, and the quality and efficiency of issuing and processing the notification information are effectively improved.
Drawings
FIG. 1 is a flow chart of the steps of the present invention;
FIG. 2 is a diagram illustrating a personalized notification alert according to the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in fig. 1, the steps of the present invention are as follows:
step 1: firstly, basic information of teaching workers is input into an OA system, wherein the input information of the teaching workers in the embodiment is Zhang III, teacher, Party, professor, economic and management college and the like;
step 2: based on the input basic information of the teaching staff, the OA system automatically completes the extraction of basic information labels (identity, position, political face, work type and the like) of the teaching staff, and the extracted labels in the embodiment are professor, party member, economy and management college and the like;
and step 3: according to the notification information issued by the school mobile terminal, the OA system automatically completes the extraction of the notification information subject term, in the embodiment, 3 notifications are issued, the notification 1 is the notification about holding the 2020 annual teacher fishing group competition, and the key subject term 'teacher' is extracted; the notification 2 is a notification about the fact that 2020 annual school recruitment and secondary professor recommendation selection work is done, and key subject words such as 'school recruitment', 'professor', 'secondary professor' and the like are extracted; the notice 3 is a notice about the special supervision of the development epidemic prevention and control work, and key subject words of epidemic prevention and control, supervision and the like are extracted;
and 4, step 4: setting grades in a percentage mode according to the calculation criterion of the correlation degree, and marking by different colors; in this embodiment, when S belongs to [0.7,1), the degree of association between the notification information and the information receiver is set to be one level, and the color of the output information is orange; when S belongs to [0.3,0.7), the degree of association between the notification information and the information receiver is of two levels, and the color of the output information is yellow; when S belongs to [0,0.3), the degree of association between the notification information and the information receiver is three-level, and the color of the output information is green; the classification of the degree of association of the notification information and the color of the label are shown in table 1:
TABLE 1 Notification information relevance ranking
And 5: based on the extracted basic information labels and notification information subject terms of the teaching staff, matching calculation is carried out by using a similarity recommendation method of relevance calculation, the similarity recommendation method is mainly divided into two types of single labels and multi-labels, and the calculation formula is as follows:
single label
Wherein P isojA label for indicating basic information of extracted teaching staff; pijA topic word label for indicating the extraction of the notification information; when P is presentoj＝PijThen, the output S1i1, indicates correlation, with focus; when P is presentoj≠PijThen, the output S1i0, meaning irrelevant, without concern;
multi-label
Wherein WjA label for indicating basic information of extracted teaching staff; sjA topic word label for indicating the extraction of the notification information; and (4) calculating the weight weighting number according to a formula so as to judge the attention degree.
And (3) calculating by adopting a single label method for the notice 1 and the notice 3 and calculating by adopting a multi-label method for the notice 2 through a relevance calculation method based on the basic information labels and the notice information subject words of the teaching staff extracted in the step 2 and the step 3.
Step 6: after the third basic information label and the notification information label are subjected to relevance calculation, the fact that the output color of the notification 1 is yellow and the relevance grade is two-level is obtained, and the fact that the notification contains relevant content and needs attention is shown; the output color of the notice 2 is orange, the level of the degree of association is first grade, which shows that the notice content is related to the notice and needs to pay attention to the notice; the output color of the notice 3 is green, and the relevance grade is three levels, which shows that the notice content is basically irrelevant to the notice, and attention is not needed.
Fig. 2 is a schematic diagram of the personalized notification reminder according to this embodiment.
Claims (8)
1. A college OA system notification issuing personalized recommendation and attention reminding method is characterized by comprising the following steps:
(1) recording basic information of the instructor into an OA system;
(2) the OA system extracts the labels of the basic information of the teaching staff;
(3) the OA system extracts the subject term of the notification information issued by the school mobile terminal;
(4) setting grades in a percentage mode according to a calculation criterion of the correlation degree, and labeling by using different colors;
(5) performing matching calculation by using a similarity recommendation method of relevance calculation;
(6) and outputting information of different colors according to the correlation matching calculation result and the grade setting standard.
2. The OA system notification issuing personalized recommendation and attention reminding method for colleges and universities according to claim 1, wherein the step (1) comprises: and inputting basic information of the instructor into the OA system.
3. The OA system notification issuing personalized recommendation and attention reminding method for colleges and universities according to claim 1, wherein the step (2) comprises: based on the input basic information of the instructor, the OA system automatically completes the label extraction of the basic information of the instructor.
4. The OA system notification issuing personalized recommendation and attention reminding method for colleges and universities according to claim 1, wherein the step (3) comprises: according to the notification information issued by the school mobile terminal, the OA system automatically completes the extraction of the subject term of the notification information issued by the school mobile terminal.
5. The OA system notification issuing personalized recommendation and attention reminding method for colleges and universities according to claim 1, wherein the step (4) comprises: and setting the grade in a percentage mode according to the calculation criterion of the correlation degree, and marking by using different colors.
6. The OA system notification issue personalized recommendation and attention reminding method for colleges and universities according to claim 1, wherein the step (5) comprises: and performing matching calculation by using a similarity recommendation method of relevance calculation based on the extracted basic information labels and notification information subject terms of the teaching staff.
7. The OA system notice issuance personalized recommendation and attention reminding method for colleges and universities according to claim 6, wherein the matching calculation is mainly divided into two types of single label and multi-label, and the calculation formula is as follows:
single label
Wherein P isojA label for indicating basic information of extracted teaching staff; pijA topic word label for indicating the extraction of the notification information; when P is presentoj＝PijThen, the output S1i1, indicates correlation, with focus; when P is presentoj≠PijThen, the output S1i0, meaning irrelevant, without concern;
multi-label
Wherein WjA label for indicating basic information of extracted teaching staff; sjA topic word label for indicating the extraction of the notification information; and (4) calculating the weight weighting number according to a formula so as to judge the attention degree.
8. The OA system notification issue personalized recommendation and attention reminding method for colleges and universities according to claim 1, wherein the step (5) comprises: outputting information personalized display of different colors according to the correlation matching calculation result and the grade setting standard; green indicates that the notification does not need attention, orange indicates that the notification needs to be focused on, and yellow indicates that the notification has content related to the notification and needs attention.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011392740.6A CN112632368A (en) | 2020-12-02 | 2020-12-02 | Method for notifying, issuing, personalized recommending and attention reminding of OA (office automation) system of colleges and universities |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011392740.6A CN112632368A (en) | 2020-12-02 | 2020-12-02 | Method for notifying, issuing, personalized recommending and attention reminding of OA (office automation) system of colleges and universities |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112632368A true CN112632368A (en) | 2021-04-09 |
Family
ID=75307487
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011392740.6A Pending CN112632368A (en) | 2020-12-02 | 2020-12-02 | Method for notifying, issuing, personalized recommending and attention reminding of OA (office automation) system of colleges and universities |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112632368A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112651703A (en) * | 2020-12-02 | 2021-04-13 | 淮阴工学院 | Dynamic reminding method for informing item processing deadline of OA (office automation) system of colleges and universities |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106991447A (en) * | 2017-04-06 | 2017-07-28 | 哈尔滨理工大学 | A kind of embedded multi-class attribute tags dynamic feature selection algorithm |
| CN110545232A (en) * | 2018-05-29 | 2019-12-06 | 阿里巴巴集团控股有限公司 | group message prompting method, group message prompting device, data processing method, data processing device, electronic equipment and storage equipment |
-
2020
- 2020-12-02 CN CN202011392740.6A patent/CN112632368A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106991447A (en) * | 2017-04-06 | 2017-07-28 | 哈尔滨理工大学 | A kind of embedded multi-class attribute tags dynamic feature selection algorithm |
| CN110545232A (en) * | 2018-05-29 | 2019-12-06 | 阿里巴巴集团控股有限公司 | group message prompting method, group message prompting device, data processing method, data processing device, electronic equipment and storage equipment |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112651703A (en) * | 2020-12-02 | 2021-04-13 | 淮阴工学院 | Dynamic reminding method for informing item processing deadline of OA (office automation) system of colleges and universities |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Mansourian et al. | Forest landscape restoration: increasing the positive impacts of forest restoration or simply the area under tree cover? | |
| Marcin | Intellectual capital as a key factor of socio-economic development of regions and countries | |
| Culloty et al. | Researching visual representations of climate change | |
| Walters | Ethnicity, race and education: An introduction | |
| Pandey et al. | Impact of skill India training programme among the youth | |
| CN112632368A (en) | Method for notifying, issuing, personalized recommending and attention reminding of OA (office automation) system of colleges and universities | |
| CN109657096A (en) | A kind of ancillary statistics report-generating method based on teaching of low school age audio-video | |
| CN110287305B (en) | Intelligent question-answering management system based on natural language processing | |
| CN113742453A (en) | Artificial intelligence wrong question correlation method and system | |
| Ren et al. | Development, hotspots and trend directions of marine ecological compensation in China: A bibliometric-based assessment | |
| Arnott et al. | Education policy and social justice | |
| Wu et al. | [Retracted] Analysis of College Students’ Mental Health Education Model Based on Media Integration | |
| CN112651703A (en) | Dynamic reminding method for informing item processing deadline of OA (office automation) system of colleges and universities | |
| CN111444678B (en) | Appeal information extraction method and system based on machine reading understanding | |
| McInerney et al. | Teacher Attitudes to, and Beliefs about, Multicultural Education: Have There Been Changes over the Last Twenty Years?. | |
| Tian | Thai ethnic Chinese people’s attitudes toward Mandarin Chinese: A pilot study | |
| Dündar | Brian Silverstein, The Social Lives of Numbers Statistics: Reform and the Remaking of Rural Life in Turkey. Singapore: Palgrave Macmillan, 2020. viii+ 121 | |
| Newlin et al. | EMERGING RESEARCHERS IN EMERGING UNIVERSITIES: LIVED EXPERIENCES (UNDERSTANDING CHALLENGES FACED) | |
| Chandio et al. | AGE OF ARTIFICIAL INTELLIGENCE IN PAKISTANI MEDIA LANDSCAPE: CHALLENGES AND OPPORTUNITIES | |
| Omar et al. | The Role of Intention (Niyyah) In Islamic Work Ethics | |
| Alajmi | Kuwait’s readiness for the knowledge-based economy: an exploratory study | |
| Ulmann et al. | Can SMS, IVR and apps enhance organic farming practices in Africa? | |
| Van et al. | Education research from Vietnam as seen from ISI WoS between 1990 and 2018: some preliminary results. RCISS-0919-03 | |
| Bi | The Optimization of Legal Curriculum System in Higher Vocational Colleges under “Intelligent Campus” | |
| Tekic et al. | Market-first or technology-first? Exploring unicorns’ pathways to extreme valuations |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |