CN107463640B - Artificial intelligence based information data acquisition method - Google Patents
Artificial intelligence based information data acquisition method Download PDFInfo
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- CN107463640B CN107463640B CN201710588721.2A CN201710588721A CN107463640B CN 107463640 B CN107463640 B CN 107463640B CN 201710588721 A CN201710588721 A CN 201710588721A CN 107463640 B CN107463640 B CN 107463640B
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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
- G06F16/95—Retrieval from the web
- G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/14—Session management
- H04L67/146—Markers for unambiguous identification of a particular session, e.g. session cookie or URL-encoding
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Abstract
The invention relates to the technical field of artificial intelligence correlation, in particular to an artificial intelligence based information data acquisition method. The basic unit of the method comprises an information acquisition unit, a data judgment unit, an information classification unit and a result execution unit, wherein the information acquisition unit is connected with the data judgment unit, the data judgment unit is connected with the information classification unit, and the information classification unit is connected with the result execution unit; the information acquisition unit collects information and transmits the information to the data judgment unit, the data judgment unit judges characteristics provided by the collected information and further transmits the characteristics to the information classification unit for classification, and the result execution unit judges according to results classified by the information classification unit and filters and accepts or rejects the information. The invention utilizes the specific session set of artificial intelligence to filter and collect data, thereby improving the working efficiency, avoiding repeated information acquisition and ensuring the accuracy of the data.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence based information data acquisition method.
Background
Artificial intelligence is the principle of studying human intelligence activities, constructs an artificial system with certain intelligence, and studies how to enable a computer to complete the work which needs human intelligence to be sufficient in the past, namely, studies how to use the software and hardware of the computer to simulate the basic theory, method and technology of human intelligence behaviors.
Information data collection is a thing that we often do when we do a job that requires public participation. However, it is not easy to collect a large amount of information data by normal manual work, and a large amount of manpower, material resources and time are required to be invested if a desired result is obtained. In order to improve the efficiency and universality of information data acquisition, people need to be assisted by a certain intelligent artificial system to collect data; at present, the problem of repeated acquisition exists in the process of information acquisition by using artificial intelligence, and in order to increase the accuracy of acquired information, a judgment method needs to be designed to avoid the phenomenon of repeated acquisition and enable the result to be as accurate as possible.
Disclosure of Invention
In order to increase the information data acquisition efficiency and ensure that the acquisition result is as accurate as possible, the invention provides an artificial intelligence-based information data acquisition method.
An artificial intelligence based information data acquisition method is characterized by comprising the following steps: step 1: acquiring required conversation elements as a conversation set, wherein the conversation elements comprise a conversation question, a scene starting identifier, a scene ending identifier and an expected answer: step 2: counting and outputting the behavior characteristics of all session elements; and step 3: judging the type of the collected information according to the output result of the step 2 and classifying; and 4, step 4: and (4) filtering and accepting or rejecting the acquired information according to the judgment made in the step (3).
The session set is characterized in that a webpage is logged in through a mobile phone or a computer to serve as a scene starting identifier, a webpage which is logged in a closed or quit mode is a scene ending identifier, the standard of the webpage which is logged out is that all session questions are answered and confirmed to be correct, participants agree to submit the webpage which is logged out, and the participants need to provide answer information to collect the session questions for logging in and quitting and serve as a proof by taking face pictures when the participants provide answer information, so that the face irreproducibility of each person is ensured, and the probability of avoiding repetition is improved.
The conversation problem also comprises mobile phone ICCID or computer IP and identity card information of a participant, the mobile phone ICCID or computer IP only needs to be read by authorization without manual input of the participant, the identity card information of the participant needs to be input by handwriting, or the identity card information of the participant is uploaded in a photo form by handwriting, so that the participant participates in the conversation, and the accuracy of information collection can be ensured from the other side according to handwriting reserved in the system by the participant.
The classification strategy in the step 3 and the filtering and accepting strategy in the step 4 comprise whether the IP of the mobile phone ICCID computer is repeated, whether the identity card information of the participant is repeated, and a conversation problem result:
1) the mobile phone ICCID computer IP repeats the ID card information of the participants, repeats the conversation problem result and abandons the conversation problem result;
2) the mobile phone ICCID computer IP repeats the ID card information of the participants, and repeats and gives a conversation problem result, so that the repeated ID card information and the conversation problem result are not repeated and are discarded;
3) the mobile phone ICCID computer IP repeats the ID card information of the participants, does not repeat the result of the conversation problem, does not repeat and is left;
4) the mobile phone ICCID computer IP repeats the ID card information of the participants, does not repeat the result of the conversation problem, repeats and abandons the result;
5) the mobile phone ICCID computer IP does not repeat the ID card information of the participants, and does not repeat the result of the problem of the repetition and conversation;
6) the mobile phone ICCID computer IP does not repeat the ID card information of the participants, and repeats and discards the problem result of the conversation;
7) the mobile phone ICCID computer IP does not repeat the ID card information of the participants and the results of the conversation problems and repeats and stores the data;
8) the mobile phone ICCID computer IP does not repeat the ID card information of the participants, does not repeat the result of the conversation problem, does not repeat, and stores the data.
Step 4, filtering and rejecting the collected information, and enabling the rejected information to enter a channel for preventing regeneration by crushing and deleting of an information protection unit; effective information enters a reinforced protection channel, information leakage is prevented, and information safety of participants is protected.
Compared with the traditional information data acquisition mode and the current artificial intelligence information data acquisition mode, the invention utilizes the specific session set of the artificial intelligence to filter and collect the data, thereby improving the working efficiency and ensuring the accuracy of the data.
Drawings
FIG. 1 is a schematic diagram of an information collection process in the present invention
FIG. 2 is a schematic diagram of the information collection and filtering process of the present invention.
Detailed Description
The following detailed description is made with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, a method for collecting information data based on artificial intelligence is characterized by comprising the following steps:
step 1: acquiring required session elements as a session set, wherein the session elements comprise a session question, a scene starting identifier, a scene ending identifier and an expected answer; step 2: counting and outputting the behavior characteristics of all session elements; and step 3: judging the type of the collected information according to the output result of the step 2 and classifying; and 4, step 4: and (4) filtering and accepting or rejecting the acquired information according to the judgment made in the step (3).
The session set is characterized in that a webpage is logged in through a mobile phone or a computer to serve as a scene starting identifier, a webpage which is logged in a closed or logged-out mode is a scene ending identifier, the standard of logging out the webpage is that all session questions are answered and confirmed to be correct, and participants agree to submit the webpage which is logged out.
The conversation problem also comprises the ICCID of the mobile phone or the IP of the computer and the identity card information of the participant, the ICCID is automatically read from the mobile phone card of the participant, the IP of the computer is read by the computer logged by the participant, and the identity card information is filled by the participant.
The classification strategy in the step 3 and the filtering and accepting strategy in the step 4 comprise whether the IP of the mobile phone ICCID computer is repeated, whether the identity card information of the participant is repeated, and a conversation problem result:
1) the mobile phone ICCID or the computer IP repeats the ID card information of the participants, repeats the session problem result, and abandons the repeated ID card information and the repeated session problem result without storing and adopting the information data;
2) the mobile phone ICCID or the computer IP repeats the ID card information of the participants, and the results of the problems of repetition and conversation are not repeated, so that the information data is not saved and adopted;
3) the mobile phone ICCID or the computer IP repeats the ID card information of the participants, does not repeat the result of the conversation problem, does not repeat the result, abandons the result, and does not store and adopt the information data;
4) the mobile phone ICCID or the computer IP repeats the ID card information of the participants, does not repeat the result of the conversation problem, repeats and discards the result, and does not store and adopt the information data;
5) the mobile phone ICCID or the computer IP does not repeat the ID card information of the participants, repeat the problem results of conversation, do not repeat, discard and do not store and adopt the information data;
6) the mobile phone ICCID or the computer IP does not repeat the ID card information of the participants, repeat the results of the problems of conversation, repeat and discard, and does not store and adopt the information data;
7) the ICCID of the mobile phone or the IP of the computer does not repeat the identity card information of the participants, does not repeat the result of the conversation problem, repeats and stores the data;
8) the ICCID of the mobile phone or the IP of the computer does not repeat the identity card information of the participants, does not repeat the result of the conversation problem, does not repeat, and stores data.
As shown in fig. 2, a basic unit based on an artificial intelligence information data acquisition method includes an information acquisition unit 101, a data judgment unit 102, an information classification unit 103, and a result execution unit 104, where the information acquisition unit 101 is connected to the data judgment unit 102, the data judgment unit 102 is connected to the information classification unit 103, and the information classification unit 103 is connected to the result execution unit 104; the information acquisition unit 101 collects information and transmits the information to the data judgment unit 102, the data judgment unit 102 judges characteristics provided by the collected information and further transmits the characteristics to the information classification unit 103 for classification, the result execution unit 104 judges according to results classified by the information classification unit 103, the information is filtered and rejected, and the information is protected or smashed and deleted by the incoming information protection unit 105 after the rejection.
Step 4, filtering and rejecting the collected information, and enabling the rejected information to enter a channel for preventing regeneration by crushing and deleting of an information protection unit; effective information enters a reinforced protection channel, information leakage is prevented, and information safety of participants is protected.
The initial purpose is achieved by calculating the collected and stored information.
The foregoing description shows preferred embodiments of the invention, and as noted above, it is to be understood that the invention is not limited to the forms disclosed herein, but is not intended to be limited to other forms, uses, or adaptations of the invention using its general purpose or use, as may be required by the skilled artisan, and as such, may be modified within the scope of the inventive concepts described herein. And that modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention except as it may be limited by the claims appended hereto.
Claims (6)
1. An artificial intelligence based information data acquisition method is characterized by comprising the following steps:
step 1: acquiring required session elements as a session set, wherein the session elements comprise a session question, a scene starting identifier, a scene ending identifier and an expected answer, and the session question comprises a mobile phone ICCID or a computer IP and identity card information of participants;
step 2: counting and outputting the behavior characteristics of all session elements;
and step 3: judging the type of the collected information according to the output result of the step 2 and classifying;
and 4, step 4: and (4) filtering and accepting or rejecting the acquired information according to the judgment made in the step (3).
2. The method of claim 1, wherein the session set is a scene start flag indicating a web page logged in via a mobile phone or a computer, and a scene end flag indicating a web page logged in when the web page is closed or logged out.
3. The artificial intelligence based information data collection method of claim 2, wherein the scene start flag and the scene end flag are marked by respective photos of participants participating in the information collection session.
4. The method as claimed in claim 3, wherein the session problem includes the mobile phone ICCID or the computer IP, and the participant only needs to be authorized to read the information without manual input, and the information of the participant's ID card needs to be input by hand or uploaded by hand in the form of a photo, so as to ensure the participant.
5. The artificial intelligence based information data collection method of claim 1 or 3, wherein the step 3 classification strategy and the step 4 filtering selection strategy include whether the mobile phone ICCID computer IP is repeated, whether the participant ID card information is repeated, and the session problem result:
the mobile phone ICCID computer IP repeats the ID card information of the participants, repeats the conversation problem result and abandons the conversation problem result;
the mobile phone ICCID computer IP repeats the ID card information of the participants, and repeats and gives a conversation problem result, so that the repeated ID card information and the conversation problem result are not repeated and are discarded;
the mobile phone ICCID computer IP repeats the ID card information of the participants, does not repeat the result of the conversation problem, does not repeat and is left;
the mobile phone ICCID computer IP repeats the ID card information of the participants, does not repeat the result of the conversation problem, repeats and abandons the result;
the mobile phone ICCID computer IP does not repeat the ID card information of the participants, and does not repeat the result of the problem of the repetition and conversation;
the mobile phone ICCID computer IP does not repeat the ID card information of the participants, and repeats and discards the problem result of the conversation;
the mobile phone ICCID computer IP does not repeat the ID card information of the participants and the results of the conversation problems and repeats and stores the data;
the mobile phone ICCID computer IP does not repeat the ID card information of the participants, does not repeat the result of the conversation problem, does not repeat, and stores the data.
6. The artificial intelligence based information data collection method according to claim 1, wherein the collected information is filtered and rejected in step 4, and the rejected information enters a channel for preventing regeneration by crushing and deleting of an information protection unit; effective information enters a reinforced protection channel, information leakage is prevented, and information safety of participants is protected.
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| CN106027546A (en) * | 2016-06-28 | 2016-10-12 | 华为技术有限公司 | Network attack detection method, device and system |
| CN106656945A (en) * | 2015-11-04 | 2017-05-10 | 陈包容 | Method and device for initiating session with communication party |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| JP5272445B2 (en) * | 2008-02-28 | 2013-08-28 | 富士通株式会社 | Biometric authentication system, biometric authentication method, and biometric authentication program |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101827068A (en) * | 2009-03-02 | 2010-09-08 | 中国移动通信集团公司 | Business scenario reduction method and device |
| CN104570987A (en) * | 2013-10-29 | 2015-04-29 | 上海沐风数码科技有限公司 | 3G network-based automatic vehicle-mounted terminal equipment |
| CN104809062A (en) * | 2015-04-22 | 2015-07-29 | 北京京东尚科信息技术有限公司 | Test method and system of artificial intelligence answering system |
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| CN106027546A (en) * | 2016-06-28 | 2016-10-12 | 华为技术有限公司 | Network attack detection method, device and system |
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Address after: The 230000 Hefei Road, Anhui province Shushan New Industrial Park No. 1201 Business Park 3 Applicant after: Yituo Communications Group Co.,Ltd. Address before: The 230088 Hefei Road, Anhui province Shushan New Industrial Park No. 1201 Business Park 3 Applicant before: ANHUI ETUO COMMUNICATION TECHNOLOGY GROUP Co.,Ltd. |
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Address after: 210000 room 701, block B, Kechuang 1 building, No. 320, pubin Road, Nanjing area, Nanjing Free Trade Zone, Jiangsu Province Patentee after: Yituo Communications Group Co.,Ltd. Address before: 230000 Anhui Hefei Shushan new industrial park Huguang road 1201 electricity supplier park 3 phase Patentee before: Yituo Communications Group Co.,Ltd. |