Artificial intelligence information processing system and method

Abstract

The invention relates to the technical field of information processing, in particular to an artificial intelligence information processing system and method, and the method comprises the steps: collecting enterprise data on the market in real time through a collection subsystem, compressing and transmitting the data to a receiving module, and obtaining received data; the decompression module decompresses the received data to restore the collected data, the collected data is trained and processed through the processing module, enterprise demand information is extracted, and demand data is obtained; the strategy module automatically plans a promotion strategy based on the demand data, and finally, the database subsystem stores the demand data and the promotion strategy and generates a database, the system can automatically train, process and collect data, extract enterprise demand information to obtain the demand data, and automatically plan the promotion strategy, so that design, planning and management demands of an enterprise are accurately obtained, and the promotion efficiency is improved. The phenomena that manual understanding is insufficient and customer requirements cannot be accurately recognized are avoided, accurate marketing of enterprises is achieved, manpower input is reduced, and enterprise cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to an artificial intelligence information processing system and method. Background Art

[0002] With the rapid development of the economy, more and more companies are focusing on the promotion, planning and management of their own companies. Therefore, there are many demands for corporate management consulting, design planning, etc. When looking for these demands, usually manual telephone consultation or door-to-door promotion is used.

[0003] However, when manual consultation is used, consultants do not fully understand the company's information and are unable to accurately identify customer needs, resulting in poor consulting results and low consulting efficiency.

[0004] Artificial intelligence is a branch of computer science that seeks to understand the essence of intelligence and develop new intelligent machines that can respond in ways similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. Information processing is the process of extracting the essential from collected information, from the superficial to the underlying, and from one point to another. It is the process of producing valuable, user-friendly secondary information based on raw information. Using artificial intelligence to process information can improve the efficiency of this process.

[0005] Therefore, using artificial intelligence to process corporate information is the key to obtaining the company's planning, management and other needs, and achieving precise demand control is a technical problem that needs to be solved at this stage. Summary of the Invention

[0006] The purpose of the present invention is to provide an artificial intelligence information processing system and method, aiming to solve the problem that existing manual consultations do not fully understand the information of enterprises and cannot accurately identify customer needs.

[0007] To achieve the above objectives, in a first aspect, the present invention provides an artificial intelligence information processing system, comprising an acquisition subsystem, a processing subsystem, and a database subsystem, wherein the acquisition subsystem, the processing subsystem, and the database subsystem are connected in sequence; the processing subsystem comprises a receiving module, a decompression module, a processing module, and a policy module, wherein the receiving module, the decompression module, the processing module, and the policy module are connected in sequence;

[0008] The acquisition subsystem is used to collect enterprise data on the market in real time and compress the data and transmit it to the receiving module;

[0009] The receiving module is used to receive the data transmitted by the acquisition subsystem and obtain received data;

[0010] The decompression module is used to decompress the received data and restore the collected data;

[0011] The processing module is used to train and process the collected data, extract enterprise demand information, and obtain demand data;

[0012] The strategy module automatically plans promotion strategies based on the demand data;

[0013] The database subsystem is used to store the demand data and the promotion strategy to generate a database.

[0014] The processing module includes a training unit, an extraction unit and a clearing unit, and the training unit is connected to the extraction unit and the clearing unit respectively;

[0015] The training unit trains the collected data based on the enterprise information training model to filter enterprise needs and useless data;

[0016] The extraction unit is used to extract the enterprise demand and obtain demand data;

[0017] The clearing unit is used to clear the useless data.

[0018] Wherein, the training unit includes a construction subunit and a training subunit, and the construction subunit and the training subunit are connected;

[0019] The construction subunit establishes an enterprise information training model based on a bidirectional long short-term memory neural network;

[0020] The training subunit trains the collected data based on the enterprise information training model to filter enterprise needs and useless data.

[0021] Wherein, the acquisition subsystem includes an acquisition module and a transmission module, and the acquisition module and the transmission module are connected;

[0022] The acquisition module is used to collect enterprise data on the market in real time to obtain collected data;

[0023] The transmission module is used to compress the collected data and transmit the compressed data to the receiving module.

[0024] Wherein, the transmission module includes a compression unit and a transmission unit, and the compression unit and the transmission unit are connected;

[0025] The compression unit is used to compress the collected data;

[0026] The transmission unit is used to transmit the compressed data to the receiving module.

[0027] Wherein, the database subsystem includes a storage module and a calling module, and the storage module is connected to the calling module;

[0028] The storage module divides the storage folders based on the initial letters of the companies of the demand data and stores the demand data;

[0029] The calling module is used by marketing personnel to search and call the demand data of the target enterprise.

[0030] In a second aspect, the present invention further provides an artificial intelligence information processing method, comprising the following steps:

[0031] The acquisition subsystem collects enterprise data on the market in real time, compresses the data and transmits it to the receiving module to obtain received data;

[0032] The decompression module decompresses the received data to restore the collected data, and the processing module trains and processes the collected data to extract the enterprise demand information and obtain the demand data;

[0033] The strategy module automatically plans promotion strategies based on demand data. Finally, the database subsystem stores the demand data and promotion strategies to generate a database.

[0034] An artificial intelligence information processing system of the present invention collects enterprise data on the market in real time through the collection subsystem, and compresses the data and transmits it to the receiving module to obtain received data; the decompression module decompresses the received data to restore the collected data, and the collected data is trained and processed by the processing module to extract enterprise demand information to obtain demand data; the strategy module automatically plans promotion strategies based on the demand data, and finally, the database subsystem stores the demand data and promotion strategies to generate a database. The system can automatically train and process the collected data, extract enterprise demand information to obtain demand data, and automatically plan promotion strategies, thereby accurately obtaining the design, planning and management needs of the enterprise, isolating the phenomenon of insufficient manual understanding and inability to accurately identify customer needs, realizing precise marketing for the enterprise, reducing manpower investment, reducing enterprise costs, and solving the problem that existing manual consultations have insufficient understanding of enterprise information and cannot accurately identify customer needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1This is a flow chart of an artificial intelligence information processing system provided by the present invention.

[0037] Figure 2 This is a schematic diagram of a processing module of an artificial intelligence information processing system provided by the present invention.

[0038] Figure 3 It is a schematic diagram of an acquisition subsystem of an artificial intelligence information processing system provided by the present invention.

[0039] Figure 4 It is a schematic diagram of a database subsystem of an artificial intelligence information processing system provided by the present invention.

[0040] Figure 5 This is a flow chart of an artificial intelligence information processing method provided by the present invention.

[0041] In the figure: 1-acquisition subsystem, 2-processing subsystem, 3-database subsystem, 4-receiving module, 5-decompression module, 6-processing module, 7-strategy module, 8-training unit, 9-extraction unit, 10-clearing unit, 11-construction subunit, 12-training subunit, 13-acquisition module, 14-transmission module, 15-compression unit, 16-transmission unit, 17-storage module, 18-calling module, 19-partitioning unit, 20-storage unit. DETAILED DESCRIPTION

[0042] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0043] See also Figures 1 to 4 In a first aspect, the present invention provides an artificial intelligence information processing system, comprising an acquisition subsystem 1, a processing subsystem 2, and a database subsystem 3, wherein the acquisition subsystem 1, the processing subsystem 2, and the database subsystem 3 are sequentially connected; the processing subsystem 2 comprises a receiving module 4, a decompression module 5, a processing module 6, and a policy module 7, wherein the receiving module, the decompression module 5, the processing module 6, and the policy module 7 are sequentially connected;

[0044] The acquisition subsystem 1 is used to collect enterprise data on the market in real time and compress the data and transmit it to the receiving module 4;

[0045] The receiving module 4 is used to receive the data transmitted by the acquisition subsystem 1 and obtain received data;

[0046] The decompression module 5 is used to decompress the received data and restore the collected data;

[0047] The processing module 6 is used to train and process the collected data, extract enterprise demand information, and obtain demand data;

[0048] The strategy module 7 automatically plans promotion strategies based on the demand data;

[0049] The database subsystem 3 is used to store the demand data and the promotion strategy to generate a database.

[0050] In this embodiment, the enterprise data on the market is collected in real time by the collection subsystem 1, and the data is compressed and transmitted to the receiving module 4 to obtain the received data; the decompression module 5 decompresses the received data to restore the collected data, and the collected data is trained and processed by the processing module 6 to extract the enterprise demand information and obtain the demand data; the strategy module 7 automatically plans the promotion strategy based on the demand data. Finally, the database subsystem 3 stores the demand data and promotion strategy to generate a database. The system can automatically train and process the collected data, extract the enterprise demand information to obtain demand data, and automatically plan the promotion strategy, so as to accurately obtain the design, planning and management needs of the enterprise, isolate the phenomenon of insufficient manual understanding and inability to accurately identify customer needs, realize precise marketing for the enterprise, reduce manpower investment, reduce enterprise costs, and solve the problem that the existing manual consultation has insufficient understanding of the enterprise information and cannot accurately identify customer needs.

[0051] Furthermore, the processing module 6 includes a training unit 8, an extraction unit 9 and a clearing unit 10, wherein the training unit 8 is connected to the extraction unit 9 and the clearing unit 10 respectively; the training unit 8 includes a construction subunit 11 and a training subunit 12, wherein the construction subunit 11 is connected to the training subunit 12;

[0052] The training unit 8 trains the collected data based on the enterprise information training model to filter enterprise needs and useless data;

[0053] The extraction unit 9 is used to extract the enterprise demand and obtain demand data;

[0054] The clearing unit 10 is used to clear the useless data;

[0055] The construction subunit 11 establishes an enterprise information training model based on a bidirectional long short-term memory neural network;

[0056] The training subunit 12 trains the collected data based on the enterprise information training model to filter enterprise needs and useless data.

[0057] In this embodiment, the construction subunit 11 of the training unit 8 establishes an enterprise information training model based on a bidirectional long short-term memory neural network, the training subunit 12 trains the collected data based on the enterprise information training model, and filters enterprise needs and useless data. The extraction unit 9 extracts the enterprise needs and obtains demand data. The clearing unit 10 is used to clear the useless data to avoid the residual useless data affecting the system memory and causing system freezes.

[0058] Furthermore, the acquisition subsystem 1 includes an acquisition module 13 and a transmission module 14, and the acquisition module 13 is connected to the transmission module 14; the transmission module 14 includes a compression unit 15 and a transmission unit 16, and the compression unit 15 is connected to the transmission unit 16;

[0059] The collection module 13 is used to collect enterprise data on the market in real time to obtain collected data;

[0060] The transmission module 14 is used to compress the collected data and transmit the compressed data to the receiving module 4;

[0061] The compression unit 15 is used to compress the collected data;

[0062] The transmission unit 16 is configured to transmit the compressed data to the receiving module 4 .

[0063] In this embodiment, the collection module 13 collects enterprise data on the market in real time to obtain collected data, the compression unit 15 of the transmission module 14 compresses the collected data, and transmits the compressed data to the receiving module 4 through the transmission unit 16.

[0064] Furthermore, the database subsystem 3 includes a storage module 17 and a calling module 18, and the storage module 17 and the calling module 18 are connected;

[0065] The storage module 17 divides the storage folders based on the initial letters of the companies of the demand data and stores the demand data;

[0066] The calling module 18 is used for marketing personnel to search and call the demand data of the target enterprise.

[0067] In this embodiment, the storage module 17 divides storage folders based on the initial letters of the companies of the demand data and stores the demand data; the calling module 18 is used for marketing personnel to search and call the demand data of the target company.

[0068] Furthermore, the storage module 17 includes a partitioning unit 19 and a storage unit 20, and the partitioning unit 19 and the storage unit 20 are connected;

[0069] The division unit 19 divides the storage folders based on the initial letters of the companies of the demand data;

[0070] The storage unit 20 stores the demand data based on the divided folders.

[0071] In this embodiment, the division unit 19 divides storage folders based on the company initials of the demand data, and the storage unit 20 stores the demand data based on the divided folders.

[0072] See also Figure 5 In a second aspect, the present invention further provides an artificial intelligence information processing method, comprising the following steps:

[0073] S1 collects enterprise data on the market in real time through the collection subsystem 1, and compresses the data and transmits it to the receiving module 4 to obtain received data;

[0074] Specifically, the collection module 13 collects enterprise data on the market in real time to obtain collected data, the compression unit 15 of the transmission module 14 compresses the collected data, and transmits the compressed data to the receiving module 4 through the transmission unit 16.

[0075] S2 decompression module 5 decompresses the received data to restore the collected data, and processes the collected data through training module 6 to extract enterprise demand information and obtain demand data;

[0076] Specifically, the decompression module 5 decompresses the received data and restores the collected data. The construction subunit 11 of the training unit 8 establishes an enterprise information training model based on a bidirectional long short-term memory neural network. The training subunit 12 trains the collected data based on the enterprise information training model to screen enterprise needs and useless data. The extraction unit 9 extracts the enterprise needs and obtains the demand data. The clearing unit 10 is used to clear the useless data to avoid the residual useless data affecting the system memory and causing system freezes.

[0077] The S3 strategy module 7 automatically plans promotion strategies based on the demand data. Finally, the database subsystem 3 stores the demand data and promotion strategies to generate a database.

[0078] Specifically, the strategy module 7 automatically plans promotion strategies based on the demand data, the storage module 17 divides storage folders based on the initials of the companies in the demand data and stores the demand data; the calling module 18 is used by promoters to search and call the demand data of the target company.

[0079] The above disclosure is merely a preferred embodiment of an artificial intelligence information processing system and method of the present invention, and certainly does not limit the scope of the present invention. A person skilled in the art will understand that implementing all or part of the processes of the above embodiment and making equivalent changes in accordance with the claims of the present invention still fall within the scope of the invention.

Claims

1. An artificial intelligence information processing system, characterized in that: It includes a collection subsystem, a processing subsystem and a database subsystem, which are connected in sequence. The processing subsystem includes a receiving module, a decompression module, a processing module and a policy module, which are connected in sequence. The acquisition subsystem is used to collect enterprise data on the market in real time and compress the data and transmit it to the receiving module; The receiving module is used to receive the data transmitted by the acquisition subsystem and obtain received data; The decompression module is used to decompress the received data and restore the collected data; The processing module is used to train and process the collected data, extract enterprise demand information, and obtain demand data; The strategy module automatically plans promotion strategies based on the demand data; The database subsystem is used to store the demand data and the promotion strategy to generate a database.

2. An artificial intelligence information processing system according to claim 1, characterized in that: The processing module includes a training unit, an extraction unit and a clearing unit, wherein the training unit is connected to the extraction unit and the clearing unit respectively; The training unit trains the collected data based on the enterprise information training model to filter enterprise needs and useless data; The extraction unit is used to extract the enterprise demand and obtain demand data; The clearing unit is used to clear the useless data.

3. An artificial intelligence information processing system according to claim 2, characterized in that: The training unit includes a construction subunit and a training subunit, and the construction subunit and the training subunit are connected; The construction subunit establishes an enterprise information training model based on a bidirectional long short-term memory neural network; The training subunit trains the collected data based on the enterprise information training model to filter enterprise needs and useless data.

4. An artificial intelligence information processing system according to claim 1, characterized in that: The acquisition subsystem includes an acquisition module and a transmission module, and the acquisition module is connected to the transmission module; The acquisition module is used to collect enterprise data on the market in real time to obtain collected data; The transmission module is used to compress the collected data and transmit the compressed data to the receiving module.

5. An artificial intelligence information processing system according to claim 4, characterized in that: The transmission module includes a compression unit and a transmission unit, and the compression unit is connected to the transmission unit; The compression unit is used to compress the collected data; The transmission unit is used to transmit the compressed data to the receiving module.

6. An artificial intelligence information processing system according to claim 1, characterized in that: The database subsystem includes a storage module and a calling module, and the storage module is connected to the calling module; The storage module divides the storage folders based on the initial letters of the companies of the demand data and stores the demand data; The calling module is used by marketing personnel to search and call the demand data of the target enterprise.

7. An artificial intelligence information processing method, applied to an artificial intelligence information processing system according to any one of claims 1 to 6, characterized in that: The following steps are involved: The acquisition subsystem collects enterprise data on the market in real time, compresses the data and transmits it to the receiving module to obtain received data; The decompression module decompresses the received data to restore the collected data, and the processing module trains and processes the collected data to extract the enterprise demand information and obtain the demand data; The strategy module automatically plans promotion strategies based on demand data. Finally, the database subsystem stores the demand data and promotion strategies to generate a database.

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