CN117556146B - Network data information processing system, method, equipment and medium - Google Patents
Network data information processing system, method, equipment and medium Download PDFInfo
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- 238000012549 training Methods 0.000 claims abstract description 17
- 239000000463 material Substances 0.000 claims abstract description 13
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- 238000004590 computer program Methods 0.000 claims description 4
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- 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
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G06F16/3331—Query processing
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Abstract
The invention discloses a network data information processing system, a method, equipment and a medium, wherein the method comprises the following steps: user comment data and user ID of unit materials in a network environment are obtained at fixed time; formulating a keyword library, and training AI to screen keywords and fuzzy words; intelligently screening user comment data through AI, selecting abnormal comment data, marking a single comment, secondarily screening marked comments, judging the occurrence times of keywords and fuzzy words, checking the belonged user ID according to the occurrence times, and marking the user ID; and (5) carrying out key screening on the marked user IDs and controlling the exposure degree of the abnormal comment data. The invention identifies users maliciously polluting network environment by multi-level screening of comment data of network users, and pertinently warns and comment shielding, thereby ensuring benign development of network data information.
Description
Technical Field
The invention relates to the technical field of network data processing, in particular to a network data information processing system, a method, equipment and a medium.
Background
The network group event, which is simply referred to as a web group event, refers to an event that occurs on the internet and has more netizens involved in discussion. Network swarm events are characterized by severe effects in a short period of time.
Network group events narrowly refer in particular to group abnormal events that are formed in a social context, such as tandem, organization, call, or even may or may have affected political stability, by utilizing a network for common interests or other related purposes.
Disclosure of Invention
The invention aims to provide a network data information processing system, a method, equipment and a medium, so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: a network data information processing method, comprising the steps of:
user comment data and user ID of unit materials in a network environment are obtained at fixed time;
formulating a keyword library, and training AI to screen keywords and fuzzy words;
intelligently screening user comment data through AI, selecting abnormal comment data, and marking a single comment;
secondarily screening marked comments, judging the occurrence times of keywords and fuzzy words, checking the ID of the user according to the occurrence times, and marking the ID of the user;
and (5) carrying out key screening on the marked user IDs and controlling the exposure degree of the abnormal comment data.
Preferably, the step of periodically obtaining the user comment data and the user ID of the unit material in the network environment includes:
user comment data and user ID of the unit materials are read at regular time, and uploaded to a database;
marking the user comment data through the time stamp, and skipping over repeated comment data of the same user ID in the same time stamp, and only adding the newly-appearing user comment data.
Preferably, the preparing a keyword library, and screening keywords and fuzzy words through AI training includes:
formulating a keyword library, inputting keywords, and setting a fuzzy word rule;
and inputting user comment data, and training AI through the keyword and fuzzy word rules to screen the keyword and the fuzzy word.
Preferably, the intelligent screening of the user comment data through AI, selecting abnormal comment data, and marking a single comment includes:
intelligently screening user comment data through AI, screening comments with keywords and/or fuzzy words, and selecting the comments as abnormal comment data;
and carrying out single comment abnormality marking on the selected abnormality comment data one by one.
Preferably, the second screening of the marked comments, judging the occurrence times of the keywords and the ambiguous words, checking the user ID according to the occurrence times, and marking the user ID, including:
presetting a malicious comment judgment value, judging through the occurrence times of keywords and fuzzy words, and setting a judgment threshold;
secondarily screening marked comments, and judging the occurrence times of keywords and fuzzy words;
if the occurrence times of the keywords and the fuzzy words exceed the judgment threshold, judging that the comment is a malicious comment, otherwise, still judging that the comment is an abnormal comment;
the user ID of the malicious comment is marked.
Preferably, the performing a key filtering on the marked user ID and controlling the exposure of the abnormal comment data thereof includes:
selecting all comments of a user ID marked by the malicious comments to perform key screening, checking the proportion of all comments of the malicious comments in the ID, and if the proportion exceeds a threshold value, controlling the exposure of abnormal comment data and automatically shielding the abnormal comments.
Preferably, the step of performing key screening on the marked user ID and controlling the exposure of the abnormal comment data further includes:
presetting a proportion threshold value of malicious comments of a user ID in all comments in the ID, wherein the threshold value comprises a warning threshold value and a shielding threshold value;
the proportional value of the warning threshold is smaller than the proportional value of the shielding threshold;
after the marked user IDs are subjected to key screening, judging whether the proportion of all comments in the marked user IDs exceeds a warning threshold and a shielding threshold, if so, directly sending out warning to the user IDs, and if so, automatically shielding abnormal comments of the user after sending out warning.
The invention also provides a network data information processing system, which comprises:
the data acquisition module is used for acquiring user comment data and user ID of the unit materials in the network environment at fixed time;
the data training module is used for making a keyword library and training AI to carry out keyword and fuzzy word screening;
the data screening module is used for intelligently screening the comment data of the user through AI, selecting abnormal comment data and marking a single comment;
the data marking module is used for carrying out secondary screening on marked comments, judging the occurrence times of keywords and fuzzy words, checking the belonged user ID according to the occurrence times, and marking the user ID;
and the exposure control module is used for carrying out key screening on the marked user IDs and controlling the exposure of the abnormal comment data.
The invention also provides an electronic device, which is entity equipment, comprising:
the device comprises a processor and a memory, wherein the memory is in communication connection with the processor;
the memory is configured to store executable instructions that are executed by at least one of the processors, and the processor is configured to execute the executable instructions to implement a network data information processing method as described above.
The present invention also provides a computer-readable storage medium having stored therein a computer program which, when executed by a processor, implements a network data information processing method as described above.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the keyword library is preset, AI is trained to screen user comments, comments containing keywords or fuzzy words are selected to be abnormal comments, if the keywords or fuzzy words in the abnormal comments are more, the comments are judged to be malicious comments, the user IDs of the malicious comments are marked, important attention is paid, the proportion of the malicious comments in all the comments with the user IDs screened again is checked, the user IDs exceeding a certain proportion are warned, or the malicious comments are screened while warning is carried out.
Drawings
FIG. 1 is a main flow chart of a network data information processing method according to an embodiment of the present invention;
fig. 2 is a flowchart of specific steps of a network data information processing method according to an embodiment of the present invention;
fig. 3 is a flowchart of specific steps for filtering malicious comments in a network data information processing method according to an embodiment of the present invention;
fig. 4 is a block diagram of a network data information processing system according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The main execution body of the method in this embodiment is a terminal, and the terminal may be a device such as a mobile phone, a tablet computer, a PDA, a notebook or a desktop, but of course, may be another device with a similar function, and this embodiment is not limited thereto.
Referring to fig. 1, the invention provides a network data information processing method, which is applied to abnormal information screening processing of comment data of network users, and comprises the following steps:
step 101, user comment data and user ID of unit materials in a network environment are obtained at fixed time.
Specifically, the step 101 further includes:
user comment data and user ID of the unit materials are read at regular time, and uploaded to a database;
marking the user comment data through the time stamp, and skipping over repeated comment data of the same user ID in the same time stamp, and only adding the newly-appearing user comment data.
And 102, formulating a keyword library, and training AI to perform keyword and fuzzy word screening.
Specifically, the step 102 further includes:
formulating a keyword library, inputting keywords, and setting a fuzzy word rule;
and inputting user comment data, and training AI through the keyword and fuzzy word rules to screen the keyword and the fuzzy word.
And 103, intelligently screening the comment data of the user through AI, selecting abnormal comment data, and marking a single comment.
Specifically, the step 103 further includes:
intelligently screening user comment data through AI, screening comments with keywords and/or fuzzy words, and selecting the comments as abnormal comment data;
and carrying out single comment abnormality marking on the selected abnormality comment data one by one.
And 104, secondarily screening the marked comments, judging the occurrence times of the keywords and the fuzzy words, checking the user ID according to the occurrence times, and marking the user ID.
Specifically, the step 104 further includes:
presetting a malicious comment judgment value, judging through the occurrence times of keywords and fuzzy words, and setting a judgment threshold;
secondarily screening marked comments, and judging the occurrence times of keywords and fuzzy words;
if the occurrence times of the keywords and the fuzzy words exceed the judgment threshold, judging that the comment is a malicious comment, otherwise, still judging that the comment is an abnormal comment;
the user ID of the malicious comment is marked.
And 105, performing key screening on the marked user ID and controlling the exposure degree of the abnormal comment data.
Specifically, the step 105 includes:
selecting all comments of a user ID marked by the malicious comments to perform key screening, checking the proportion of all comments of the malicious comments in the ID, and if the proportion exceeds a threshold value, controlling the exposure of abnormal comment data and automatically shielding the abnormal comments.
The method comprises the steps of carrying out key screening on marked user IDs, controlling exposure of abnormal comment data, and further comprising the following steps:
presetting a proportion threshold value of malicious comments of a user ID in all comments in the ID, wherein the threshold value comprises a warning threshold value and a shielding threshold value;
the proportional value of the warning threshold is smaller than the proportional value of the shielding threshold;
after the marked user IDs are subjected to key screening, judging whether the proportion of all comments in the marked user IDs exceeds a warning threshold and a shielding threshold, if so, directly sending out warning to the user IDs, and if so, automatically shielding abnormal comments of the user after sending out warning.
In the embodiment, through presetting a keyword library and training AI to screen user comments, selecting comments containing keywords or fuzzy words as abnormal comments, judging the comments as malicious comments if the keywords or fuzzy words appear in the abnormal comments are more, marking user IDs of the malicious comments, focusing on, and rescuing all comments of the user IDs, checking the proportion of the malicious comments in the comments, warning the user IDs exceeding a certain proportion, or shielding the malicious comments while warning.
For better understanding of the foregoing embodiments, as shown in fig. 2, the present invention further provides a specific step flowchart of a network data information processing method, where the method at least includes:
step 201, user comment data and user ID of unit materials are read at regular time, and uploaded to a database;
step 202, inputting user comment data, and training AI through keywords and fuzzy word rules to screen keywords and fuzzy words;
step 203, intelligently screening user comment data through AI, screening comments with keywords and/or fuzzy words, and selecting the comments as abnormal comment data;
step 204, carrying out single comment abnormality marking on the selected abnormality comment data one by one;
step 205, performing secondary screening on marked comments, and judging whether the occurrence times of the keywords and the fuzzy words exceed a judging threshold value;
step 206, if the occurrence times of the keywords and the fuzzy words exceed the judgment threshold, judging the comment as a malicious comment and marking the user ID of the malicious comment, executing step 207, otherwise, still being an abnormal comment, returning to step 202, and waiting for new user comment data to be screened;
step 207, selecting all comments of the user ID marked by the malicious comments to perform key screening, checking whether the proportion of all comments of the malicious comments in the ID exceeds a threshold value, if so, continuing to execute step 208, otherwise, returning to step 206, continuing to wait for refreshing of new malicious comments of the user ID marked by the malicious comments, and rescreening;
and step 208, controlling the exposure degree of the abnormal comment data, and automatically shielding the abnormal comments.
In order to better understand the above embodiments, as shown in fig. 3, the present invention further provides a flowchart for filtering malicious comments of a network data information processing method, where the method at least includes:
step 301, selecting all comments of user IDs marked by malicious comments to perform key screening;
step 302, judging whether the proportion of all comments in the user ID marked by the malicious comments exceeds a warning threshold and a shielding threshold, if so, continuing to execute step 303;
step 303, giving a warning to the user ID, and continuing to judge whether the shielding threshold is exceeded, if yes, continuing to execute step 304, otherwise, ending;
step 304, automatically shielding the abnormal comments of the user.
On the basis of the above embodiment, as shown in fig. 4, the present invention further provides a network data information processing system for supporting the network data information processing method of the above embodiment, where the network data information processing system includes:
a data acquisition module 41, configured to acquire user comment data and a user ID of a unit material in a network environment at regular time;
a data training module 42 for formulating a keyword library and training the AI to perform keyword and fuzzy word screening;
the data screening module 43 is used for intelligently screening the comment data of the user through AI, selecting abnormal comment data and marking a single comment;
the data marking module 44 is used for performing secondary screening on marked comments, judging the occurrence times of keywords and fuzzy words, checking the belonged user ID according to the occurrence times, and marking the user ID;
and the exposure control module 45 is used for carrying out key screening on the marked user IDs and controlling the exposure of the abnormal comment data.
Further, the network data information processing system may operate the network data information processing method, and specific implementation may refer to a method embodiment, which is not described herein.
On the basis of the embodiment, the invention further provides electronic equipment, which comprises:
the device comprises a processor and a memory, wherein the processor is in communication connection with the memory;
in this embodiment, the memory may be implemented in any suitable manner, for example: the memory can be read-only memory, mechanical hard disk, solid state disk, USB flash disk or the like; the memory is used for storing executable instructions executed by at least one of the processors;
in this embodiment, the processor may be implemented in any suitable manner, e.g., the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an application specific integrated circuit (ApplicationSpecificIntegratedCircuit, ASIC), a programmable logic controller, and an embedded microcontroller, etc.; the processor is configured to execute the executable instructions to implement a network data information processing method as described above.
On the basis of the above-described embodiments, the present invention also provides a computer-readable storage medium in which a computer program is stored, which when executed by a processor, implements a network data information processing method as described above.
Those of ordinary skill in the art will appreciate that the modules and method steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination 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 solution. 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 invention.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus, device and module described above may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus, device, and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple modules or units may be combined or integrated into another apparatus, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or apparatuses, which may be in electrical, mechanical or other form.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a read-only memory server, a random access memory server, a magnetic disk or an optical disk, or other various media capable of storing program instructions.
In addition, it should be noted that the combination of the technical features described in the present invention is not limited to the combination described in the claims or the combination described in the specific embodiments, and all the technical features described in the present invention may be freely combined or combined in any manner unless contradiction occurs between them.
It should be noted that the above-mentioned embodiments are merely examples of the present invention, and it is obvious that the present invention is not limited to the above-mentioned embodiments, and many similar variations are possible. All modifications attainable or obvious from the present disclosure set forth herein should be deemed to be within the scope of the present disclosure.
The foregoing is merely illustrative of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A network data information processing method, comprising the steps of:
user comment data and user ID of unit materials in a network environment are obtained at fixed time;
formulating a keyword library, and training AI to screen keywords and fuzzy words;
intelligently screening user comment data through AI, selecting abnormal comment data, and marking a single comment;
secondarily screening marked comments, judging the occurrence times of keywords and fuzzy words, checking the ID of the user according to the occurrence times, and marking the ID of the user;
the marked user IDs are subjected to key screening, and the exposure degree of the abnormal comment data is controlled;
the intelligent screening of the user comment data through the AI, the selection of the abnormal comment data and the marking of the single comment comprise the following steps:
intelligently screening user comment data through AI, screening comments with keywords and/or fuzzy words, and selecting the comments as abnormal comment data;
the selected abnormal comment data are marked with single comment abnormality one by one;
the second screening of marked comments is carried out, the occurrence times of keywords and fuzzy words are judged, the ID of the user is checked according to the occurrence times, and the ID of the user is marked, and the method comprises the following steps:
presetting a malicious comment judgment value, judging through the occurrence times of keywords and fuzzy words, and setting a judgment threshold;
secondarily screening marked comments, and judging the occurrence times of keywords and fuzzy words;
if the occurrence times of the keywords and the fuzzy words exceed the judgment threshold, judging that the comment is a malicious comment, otherwise, still judging that the comment is an abnormal comment;
marking the user ID of the malicious comment;
the step of carrying out key screening on the marked user ID and controlling the exposure of the abnormal comment data comprises the following steps:
selecting all comments of a user ID marked by the malicious comments to perform key screening, checking the proportion of all comments of the malicious comments in the ID, and if the proportion exceeds a threshold value, controlling the exposure of abnormal comment data and automatically shielding the abnormal comments;
the method comprises the steps of performing key screening on marked user IDs, controlling exposure of abnormal comment data, and further comprising the following steps:
presetting a proportion threshold value of malicious comments of a user ID in all comments in the ID, wherein the threshold value comprises a warning threshold value and a shielding threshold value;
the proportional value of the warning threshold is smaller than the proportional value of the shielding threshold;
after the marked user IDs are subjected to key screening, judging whether the proportion of all comments in the marked user IDs exceeds a warning threshold and a shielding threshold, if so, directly sending out warning to the user IDs, and if so, automatically shielding abnormal comments of the user after sending out warning.
2. The method for processing network data information according to claim 1, wherein the step of periodically acquiring the user comment data and the user ID of the unit material in the network environment comprises the steps of:
user comment data and user ID of the unit materials are read at regular time, and uploaded to a database;
marking the user comment data through the time stamp, and skipping over repeated comment data of the same user ID in the same time stamp, and only adding the newly-appearing user comment data.
3. The network data information processing method according to claim 1, wherein the formulating a keyword library and filtering keywords and ambiguous words by AI training comprises:
formulating a keyword library, inputting keywords, and setting a fuzzy word rule;
and inputting user comment data, and training AI through the keyword and fuzzy word rules to screen the keyword and the fuzzy word.
4. A network data information processing system relating to a network data information processing method as claimed in any one of claims 1 to 3, comprising:
the data acquisition module is used for acquiring user comment data and user ID of the unit materials in the network environment at fixed time;
the data training module is used for making a keyword library and training AI to carry out keyword and fuzzy word screening;
the data screening module is used for intelligently screening the comment data of the user through AI, selecting abnormal comment data and marking a single comment;
the data marking module is used for carrying out secondary screening on marked comments, judging the occurrence times of keywords and fuzzy words, checking the belonged user ID according to the occurrence times, and marking the user ID;
and the exposure control module is used for carrying out key screening on the marked user IDs and controlling the exposure of the abnormal comment data.
5. An electronic device, the electronic device comprising:
the device comprises a processor and a memory, wherein the memory is in communication connection with the processor;
the memory is configured to store executable instructions that are executed by at least one of the processors, the processor configured to execute the executable instructions to implement the network data information processing method of any one of claims 1 to 3.
6. A computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, implements the network data information processing method according to any one of claims 1 to 3.
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| CN112966500A (en) * | 2021-02-15 | 2021-06-15 | 珠海市鸿瑞信息技术股份有限公司 | Network data chain safety monitoring platform based on artificial intelligence configuration |
| KR20230049354A (en) * | 2021-10-06 | 2023-04-13 | 건국대학교 산학협력단 | Malicious comment filter device and method |
| CN115357680A (en) * | 2022-07-11 | 2022-11-18 | 深圳市永兴元科技股份有限公司 | Comment information processing method, comment information processing system and computer-readable storage medium |
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