A business opportunity information management method and system

Abstract

The application discloses a business opportunity information management system, which comprises an information collection module, an information extraction module and a structured module. The information collection module is used for collecting customer information and sending the customer information to the information extraction module. The information extraction module is used for segmenting the customer information and filling the segmented customer information into information groups according to preset information groups, wherein the information groups at least comprise a time group and a customer name group. The structured module uses time and customer name as indexes and uses semantic analysis to reorganize the content of the information groups to obtain corresponding business opportunity information, and sends the business opportunity information to a storage module. Through the system, customer information can be obtained, the customer information can be extracted, the business opportunity information of the customer can be generated, the demand and preference of the customer can be quickly understood by a businessperson through the business opportunity information, the extraction difficulty of the business opportunity information is greatly reduced, and the acquisition efficiency of the business opportunity information is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information processing, and in particular to a business opportunity information management method and system. BACKGROUND

[0002] In the current rapidly changing and highly competitive business environment, enterprises are exposed to a vast amount of customer information and complex business communication data every day. The scale and complexity of these data far exceed any time in the past, bringing unprecedented opportunities and challenges to enterprises. Traditional business opportunity information management methods mostly rely on manual data sorting, screening and analysis. This method is not only inefficient and difficult to meet the needs of instant decision-making, but also prone to errors due to human factors, thereby affecting the accuracy and timeliness of enterprise decision-making.

[0003] With the rapid progress of big data technology and artificial intelligence, enterprises have unprecedented technological means to cope with this challenge. The use of big data technology enables enterprises to efficiently collect, store and process these massive data sets, while artificial intelligence technology, especially advanced algorithms such as machine learning, natural language processing (NLP) and deep learning, makes it possible to automatically analyze and mine valuable information from these data.

[0004] Therefore, how to combine information processing technology to process the business opportunity information of enterprises and obtain useful valuable information has become a technical problem to be solved. SUMMARY

[0005] In view of the above defects, the purpose of the present application is to provide a business opportunity information management system to solve the problem of long time and high difficulty in existing business opportunity information mining.

[0006] To achieve this purpose, the present application adopts the following technical solution: a business opportunity information management system, comprising:

[0007] The information collection module is used to collect customer information and send the customer information to the information extraction module;

[0008] The information extraction module is used to segment the customer information and fill the segmented customer information into the information grouping according to the preset information grouping, and send the content of the information grouping to the structured module, wherein the information grouping at least includes a time grouping and a customer name grouping;

[0009] The structured module uses time and customer name as an index and uses semantic analysis to reorganize the content of the information grouping to obtain corresponding business opportunity information, and sends the business opportunity information to the storage module;

[0010] The storage module is used for searching in the database using the customer name, judging whether the customer exists in the data to build a corresponding storage document, if not, building a storage document with the customer name plus the generated ID, and storing the business opportunity information in the storage document, if yes, obtaining the time in the business opportunity information, and sorting the business opportunity information according to different times of the business opportunity information;

[0011] The reminding module is used for reading the business opportunity information sorted at the front in the storage document, judging whether the current time reaches the predetermined time, if yes, sending the business opportunity information to the corresponding business personnel, and triggering the feedback module;

[0012] The feedback module is used for receiving the feedback information of the business personnel within a time threshold, if the feedback information is received within the time threshold, sending a deletion instruction to the reminding module, if the feedback information is not received within the time threshold, sending a resend instruction to the reminding module;

[0013] The reminding module removes the business opportunity information sorted at the front in the storage document after receiving the deletion instruction;

[0014] The reminding module re-sends the business opportunity information to the corresponding business personnel and continues to trigger the feedback module after receiving the resend instruction.

[0015] Preferably, the customer information includes text content, voice content and picture content;

[0016] The information collection module includes a document information acquisition submodule, a voice information acquisition submodule and an image information acquisition submodule;

[0017] The document information acquisition submodule is used for generating a first program interface, and acquiring the text content in the specified chat software through the first program;

[0018] The voice information acquisition submodule is used for generating a second program interface, and acquiring the voice content in the specified chat software through the second program, or acquiring the voice content in the telephone communication through the second program interface after receiving the request instruction of the business personnel;

[0019] The image information acquisition submodule is used for generating a third program interface, and acquiring the picture content in the specified chat software through the third program.

[0020] Preferably, it further includes an official website information acquisition submodule, which is used for generating a fourth program interface, and the fourth program is used for connecting the official website of the customer and obtaining the text content and / or picture content through the network crawler technology.

[0021] Preferably, the information extraction module includes a text processing submodule, a voice processing submodule, and an image processing submodule;

[0022] The text processing submodule is used to receive the text content, perform semantic analysis on the text content using natural language processing technology, divide the text data according to the semantic analysis results, and extract key information from it.

[0023] The speech processing submodule is used to receive speech content, perform noise reduction and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into a deep learning model, extract speech features and map them to acoustic units of phonemes or subphonemes, generate a word sequence based on the acoustic unit sequence and natural language model, normalize the identified word sequence, and perform semantic analysis on the normalized word sequence through natural language processing technology to obtain key information.

[0024] The image processing submodule is used to receive image content, call the OCR interface, extract text content from the image content using OCR technology, and perform semantic analysis on the text content using natural language processing technology to obtain key information.

[0025] Preferably, the information extraction module further includes an input submodule;

[0026] The input submodule is used to clean key information and remove redundant, erroneous or irrelevant data;

[0027] The cleaned key information is then mapped to the defined information groups.

[0028] Preferably, the structured module includes a sentence-building module, which is used to call the artificial intelligence language model interface to sequentially output each information group to the artificial intelligence language model. The artificial intelligence language model reorganizes the content of the information group through semantic analysis to obtain a reorganized sentence.

[0029] By combining the reorganized statements with customer information sources, complete business opportunity information can be obtained.

[0030] A method for managing business opportunity information, applied to a management system for business opportunity information, includes the following steps:

[0031] Step S1: Collect customer information;

[0032] Step S2: Segment the customer information and fill the segmented customer information into the information groups according to the preset information groups;

[0033] Step S3: Using time and customer name as indexes, and semantic analysis to reorganize the information groupings, the corresponding business opportunity information is obtained;

[0034] Step S4: using the customer name to search in the database, judging whether the customer is in the data to build the corresponding storage document, if not, the storage document is built with the customer name plus the randomly generated ID, and the business opportunity information is stored in the storage document, if it exists, the time in the business opportunity information is obtained, and the business opportunity information is sorted according to different business opportunity information time;

[0035] Step S5: reading the business opportunity information sorted in the front in the storage document, judging whether the current time reaches the predetermined time, if it reaches, the business opportunity information is sent to the corresponding business personnel;

[0036] Step S6, judging whether the feedback information of the business personnel is received within the time threshold, if the feedback information is received within the time threshold, the business opportunity information sorted in the front in the storage document is removed, if no feedback information is received, step S5 is re-executed.

[0037] Preferably, the step S1 specifically includes the following steps:

[0038] A first program interface is generated to obtain the text content in the specified chat software through the first program;

[0039] A second program interface is generated to obtain the voice content in the specified chat software through the second program, or to obtain the voice content in the telephone communication through the second program interface after receiving the request instruction of the business personnel;

[0040] A third program interface is generated to obtain the picture content in the specified chat software through the third program, or to connect the official website of the customer and obtain the picture content by directional crawling of network information through the network crawler technology.

[0041] Preferably, the specific steps of the step S2 are as follows:

[0042] The text content is received, and the semantic analysis of the text content is performed through the natural language processing technology, the text data is divided according to the semantic analysis result, and the key information is extracted therefrom;

[0043] The voice content is received, and the de-noising and filtering operations are performed on the voice content to obtain the pre-processed voice, the pre-processed voice is input into the deep learning model, the extracted voice features are mapped to the acoustic units of phonemes or sub-phonemes, the vocabulary sequence is generated according to the acoustic unit sequence and the natural language model, the recognized vocabulary sequence is standardized, the semantic analysis of the standardized vocabulary sequence is performed through the natural language processing technology, and the key information is obtained;

[0044] Receive picture content, and call the interface of OCR, extract the text content in the picture content through the OCR technology, perform semantic analysis on the text content through the natural language processing technology, and obtain key information;

[0045] Clean the key information, and remove redundant, incorrect or irrelevant data;

[0046] And map the cleaned key information to a defined information group.

[0047] Preferably, the specific steps of the step S3 are as follows:

[0048] Call the interface of the artificial intelligence language model, sequentially output the information groups to the artificial intelligence language model, and recombine the contents of the information groups through semantic analysis by the artificial intelligence language model to obtain recombined sentences;

[0049] Combine the recombined sentences and the customer information sources to obtain complete business opportunity information.

[0050] One of the technical solutions in the above technical solution has the following advantages or beneficial effects: through the system of the application, customer information can be obtained, and the customer information can be extracted to generate business opportunity information of the customer, through which the business personnel can quickly understand the needs and preferences of the customer, and promote the completion of the transaction. In addition, the system of the application can realize automatic acquisition of business opportunity information, greatly reducing the extraction difficulty of business opportunity information and improving the acquisition efficiency of business opportunity information. BRIEF DESCRIPTION OF DRAWINGS

[0051] Fig. 1 is a structural schematic diagram of an embodiment of the system of the application.

[0052] Fig. 2 is a flowchart of an embodiment of the method of the application. DETAILED DESCRIPTION

[0053] The embodiments of the application will be described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are only used to explain the application, and cannot be understood as a limitation of the application.

[0054] In the description of the embodiments of the application, the terms "first", "second" are only used for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include one or more of the features. In the description of the embodiments of the application, the meaning of "multiple" is two or more, unless otherwise specifically limited.

[0055] In addition, the terms "first", "second", etc. are used only for descriptive purposes and should not be construed as implying or suggesting relative importance or an indicated number of the technical features indicated. Thus, the features defined with "first", "second", etc. can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified. The specific meanings of the above terms in the present application can be understood by those of ordinary skill in the art on a case-by-case basis.

[0056] As shown in Figs. 1-2 An opportunity information management system, comprising:

[0057] The information collection module is used to collect customer information and send the customer information to the information extraction module;

[0058] The information extraction module is used to segment the customer information and fill the segmented customer information into information groups according to a preset information grouping, and send the content of the information groups to the structured module, wherein the information groups at least include a time group and a customer name group;

[0059] The structured module uses time and customer name as an index and uses semantic analysis to reorganize the content of the information groups to obtain corresponding opportunity information, and sends the opportunity information to the storage module;

[0060] The storage module is used to search the database using the customer name to determine whether the customer is in the data to build a corresponding storage document, if not, build a storage document with the customer name plus a generated ID, and store the opportunity information in the storage document, if so, obtain the time in the opportunity information, and sort the opportunity information according to different times of the opportunity information;

[0061] The reminder module is used to read the opportunity information sorted first in the storage document, determine whether the current time reaches a predetermined time, if so, send the opportunity information to the corresponding business personnel, and trigger the feedback module;

[0062] The feedback module is used to receive feedback information from the business personnel within a time threshold, if the feedback information is received within the time threshold, send a delete instruction to the reminder module, if the feedback information is not received within the time threshold, send a resend instruction to the reminder module;

[0063] The reminder module removes the opportunity information sorted first in the storage document after receiving the delete instruction;

[0064] The reminding module re-sends the business opportunity information to the corresponding business personnel after receiving the retransmission instruction, and continues to trigger the feedback module.

[0065] In order to solve the problem that the data is manually screened and the business opportunity information is slow in the prior art, and the business opportunity information cannot be technically utilized. In the present application, an information collection module is provided, which can collect customer information. After collecting different customer information, the information extraction module extracts the content in the customer information, for example, the customer information is: a customer in a certain area needs to purchase a certain product at XX time. However, the customer information is not always complete, and the customer information may be a group of scattered text, voice content and picture content. Therefore, the area, customer, time, product and quantity are segmented from the customer information, and then the above information is filled in according to the preset information grouping. The information grouping can be customized according to the importance of different information acquisition in different enterprises.

[0066] After the customer information is filled in the information grouping, the structured module uses time and customer name as index, so as to facilitate subsequent storage and search of different information, and accelerate the processing speed of information. At this time, the customer information exists in different information groupings respectively, and the existing natural language processing (NLP) can be used to reorganize the content in the information grouping to obtain a business opportunity information, which includes important information in business and can help the salesperson to promote transactions. At this time, the storage module stores the business opportunity information, and judges whether there is a corresponding storage document of the customer in the database. If it exists, a new storage document will not be created. When there is no corresponding storage document, a corresponding storage document is created to store the corresponding business opportunity information. It is worth mentioning that some customers (personal customers) may have the same name, so ID information is generated, which usually uses the customer's social unified code, ID card or mobile phone last four digits as ID information. If there are multiple business opportunity information in the storage document, the time is sorted according to the time, and the business opportunity information with earlier time is arranged in front.

[0067] Since the business opportunity information has its corresponding time, for example, A customer needs to purchase products on November 6, and if the business opportunity information is sent to the salesperson in advance, the salesperson may forget. Therefore, it is necessary to determine whether the current time reaches the predetermined time, wherein the predetermined time is obtained by subtracting a fixed time value from the time in the business opportunity information, for example, the time in the business opportunity information is November 6, and the fixed time is 3 days (the fixed time can be set according to different business scenarios). The predetermined time is November 3, and the business opportunity information is sent to the salesperson on November 3. The salesperson can also communicate with the customer in advance to seize the business opportunity as soon as possible.

[0068] And after the business opportunity information is sent by the business personnel, the business personnel can not pay attention to the business opportunity information, so the feedback module is arranged in the application, and the business personnel confirms after receiving the business opportunity information. After confirmation, the feedback module is fed back to the information, and the feedback information received indicates that the business personnel has understood. At this time, the business opportunity information stored in the storage document has no use, so the business opportunity information sorted in the front of the storage document can be removed to reduce the occupation of the content. If the feedback information is not received within the time threshold, it indicates that the business personnel has not paid attention to the business opportunity information, so the business personnel needs to be sent the business opportunity information again.

[0069] The system of the application can obtain customer information, extract the customer information, and generate business opportunity information of the customer. The business opportunity information can enable the business personnel to quickly understand the needs and preferences of the customer, and promote the completion of the transaction. In addition, the system of the application can automatically obtain the business opportunity information, greatly reducing the difficulty of extracting the business opportunity information and improving the efficiency of obtaining the business opportunity information.

[0070] Preferably, the customer information includes text content, voice content, and picture content.

[0071] The information collection module includes a document information acquisition submodule, a voice information acquisition submodule, and an image information acquisition submodule.

[0072] The document information acquisition submodule is used to generate a first program interface, and the text content in the specified chat software is acquired through the first program.

[0073] The voice information acquisition submodule is used to generate a second program interface, and the voice content in the specified chat software is acquired through the second program, or the voice content in the telephone communication is acquired through the second program interface after receiving the request instruction of the business personnel.

[0074] The image information acquisition submodule is used to generate a third program interface, and the picture content in the specified chat software is acquired through the third program.

[0075] Since the business personnel and the customer can use different ways to communicate, the customer information is diversified. Therefore, the document information acquisition submodule, the voice information acquisition submodule, and the image information acquisition submodule are arranged in the application. The document information acquisition submodule generates a first program interface, and the chat information of the specified chat program, such as WeChat Enterprise, is acquired through the first program. When the text information of the chat window is acquired, it is usually acquired in units of days, and the text content of the business personnel and the customer in the chat software is acquired every day.

[0076] And the voice information acquisition submodule will generate a second program interface, similarly, the second program will be in units of days, each day to get the voice content of the business and the customer in the chat software. Of course, the business and the customer may directly use the phone to communicate, in order to avoid illegal monitoring of the privacy of the business, as long as the business requests instructions, the second program will only listen to the content of the telephone communication. Record the voice content of the business and the customer.

[0077] The image information acquisition submodule will generate a third program interface, and the third program is responsible for listening to the picture content in the chat information.

[0078] Through the three programs, the chat content can be fully monitored to avoid missing customer information and help extract business information.

[0079] Preferably, it also includes an official website information acquisition submodule, which is used to generate a fourth program interface, and the fourth program is used to connect the official website of the customer and to obtain text content and / or picture content through web crawler technology.

[0080] In order to further expand the scope of business information acquisition, the official website information acquisition submodule is also provided in the present application, which can crawl useful text content and / or picture content from the official website of the enterprise to develop new customers.

[0081] Preferably, the information extraction module includes a text processing submodule, a voice processing submodule, and a picture processing submodule.

[0082] The text processing submodule is used to receive the text content and perform semantic analysis on the text content through natural language processing (NLP) technology. According to the semantic analysis result, the text data is divided, and the key information is extracted therefrom.

[0083] For the recognition of text content, the existing and mature natural language processing (NLP) technology can be used to perform semantic analysis on the text content. Through the analysis result, the customer transaction intention, the transaction content, etc. can be judged, so as to divide the text data and extract the corresponding key information. For example, set to extract the transaction time, quantity, product type, etc. At this time, the text data will be divided according to the above-mentioned need to extract the transaction time, quantity, product, and different key information of each group is obtained.

[0084] The voice processing submodule is used for receiving voice content, performing denoising and filtering operations on the voice content, obtaining preprocessed voice, inputting the preprocessed voice into a deep learning model, mapping extracted voice features to acoustic units of phonemes or sub-phonemes, generating a word sequence according to an acoustic unit sequence and a natural language model, performing normalization processing on the recognized word sequence, performing semantic analysis on the normalized word sequence through a natural language processing technology, and obtaining key information.

[0085] Since the voice content may be disturbed by the environment during recognition, it needs to be denoised and filtered before being converted into text content, so as to reduce the influence of external factors on the voice content in the recognition process. In voice recognition, a deep learning model can be used for recognition. The deep learning model maps the extracted voice features to acoustic units of phonemes or sub-phonemes, and then generates a corresponding word sequence according to an acoustic unit sequence and a natural language model. The recognized word sequence is normalized, for example, punctuation is added according to the position of the pause, and finally a complete text sentence (normalized word sequence) is obtained. Semantic analysis can be used to obtain key information.

[0086] The picture processing submodule is used for receiving picture content, calling an interface of an optical character recognition (OCR) technology, extracting text content in the picture content through the OCR technology, and performing semantic analysis on the text content through a natural language processing technology to obtain key information.

[0087] Preferably, the information extraction module further comprises an inputting submodule.

[0088] The inputting submodule is used for cleaning the key information to remove redundant, erroneous or irrelevant data.

[0089] And the cleaned key information is mapped into a defined information group.

[0090] Through the inputting module, redundant information can be cleared, ensuring the cleanliness and correctness of the information, and the content in the subsequent generated corresponding sentences will be more real and fluent.

[0091] Preferably, the structured module comprises a sentence generating submodule, which is used for calling an artificial intelligence language model interface, sequentially outputting each information group into the artificial intelligence language model, and recombining the content of the information group through semantic analysis by the artificial intelligence language model to obtain a recombined sentence.

[0092] Combining the recombined sentence and the customer information source, complete business opportunity information is obtained.

[0093] The multiple independent words in the information grouping can be assembled into a complete reorganized sentence by the existing artificial intelligence language model. The reorganized sentence is short but includes all the information that helps the transaction. The business personnel can quickly re-understand the customer.

[0094] In addition, since the reorganized sentence is synthesized by the artificial intelligence language model and is not audited by human beings, sometimes the reorganized sentence constructed may not reach the standard for use, so the customer information source is attached in the business opportunity information. When the business personnel feel that the reorganized sentence is not good, the information of the customer can be re-understood according to the customer information source.

[0095] A management method of business opportunity information, applied to the management system of the business opportunity information, comprising the following steps:

[0096] Step S1: collecting customer information;

[0097] Step S2: segmenting the customer information, and filling the segmented customer information into the information grouping according to a preset information grouping;

[0098] Step S3: taking time and customer name as indexes, and reorganizing the content of the information grouping by using semantic analysis to obtain corresponding business opportunity information;

[0099] Step S4: searching the database by using the customer name to determine whether the customer exists in the data to construct a corresponding storage document, if not, constructing the storage document by using the customer name plus a randomly generated ID, and storing the business opportunity information in the storage document, if yes, obtaining the time in the business opportunity information, and sorting the business opportunity information according to different times of the business opportunity information;

[0100] Step S5: reading the business opportunity information sorted in the front in the storage document, determining whether the current time reaches a predetermined time, if yes, sending the business opportunity information to the corresponding business personnel;

[0101] Step S6: determining whether the feedback information of the business personnel is received within a time threshold, if yes, removing the business opportunity information sorted in the front in the storage document, if not, re-executing step S5.

[0102] Preferably, the step S1 specifically comprises the following steps:

[0103] generating a first program interface to obtain the text content in the specified chat software by the first program;

[0104] A second program interface is generated to obtain voice content in the specified chat software through the second program, or to obtain voice content in the telephone communication through the second program interface after receiving the request instruction of the business personnel;

[0105] A third program interface is generated to obtain picture content in the specified chat software through the third program, or to connect the official website of the customer and obtain the picture content through the network crawler technology for directional crawling of network information.

[0106] Preferably, the specific steps of step S2 are as follows:

[0107] The text content is received, and the text content is subjected to semantic analysis through natural language processing technology, the text data is divided according to the semantic analysis result, and key information is extracted therefrom;

[0108] The voice content is received, and the voice content is subjected to denoising and filtering to obtain preprocessed voice. The preprocessed voice is input into a deep learning model, the extracted voice features are mapped to an acoustic unit of a phoneme or a sub-phoneme, a word sequence is generated according to an acoustic unit sequence and a natural language model, the recognized word sequence is subjected to normalization processing, the normalized word sequence is subjected to semantic analysis through natural language processing technology, and key information is obtained;

[0109] The picture content is received, and the interface of an OCR is called to extract text content in the picture content through the OCR technology, the text content is subjected to semantic analysis through natural language processing technology, and key information is obtained;

[0110] The key information is cleaned to remove redundant, erroneous or irrelevant data;

[0111] And the cleaned key information is mapped to a defined information group.

[0112] Preferably, the specific steps of step S3 are as follows:

[0113] An artificial intelligence language model interface is called to sequentially output each information group to the artificial intelligence language model, and the artificial intelligence language model reorganizes the content of the information group through semantic analysis to obtain a reorganized sentence;

[0114] The reorganized sentence and the customer information source are combined to obtain complete business opportunity information.

[0115] In the description of the specification, reference to "one embodiment", "some embodiments", "an exemplary embodiment", "an example", "a specific example", or "some examples" means that a particular feature, structure, material, or characteristic being described is included in at least one embodiment or example of the application. The appearances of the phrases "in one embodiment", "in some embodiments", "in an exemplary embodiment", "an example", "a specific example", or "some examples" in various places in the specification are not necessarily referring to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0116] Although embodiments of the application have been shown and described, it will be appreciated that those skilled in the art can make various changes, modifications, substitutions and alterations thereto without departing from the principles and scope of the application, which are defined by the claims and their equivalents.

Claims

1. A management system for business opportunity information, characterized in that, include: The information collection module is used to collect customer information and send the customer information to the information extraction module. The customer information includes text content, voice content, and image content. The information collection module includes a document information acquisition submodule, a voice information acquisition submodule, and an image information acquisition submodule. The document information acquisition submodule generates a first program interface to acquire text content from a specified chat application. The voice information acquisition submodule generates a second program interface to acquire voice content from a specified chat application, or, upon receiving a request from a salesperson, acquires voice content from a telephone conversation. The image information acquisition submodule generates a third program interface to acquire image content from a specified chat application. The information extraction module is used to segment customer information, fill the segmented customer information into the preset information groups according to the preset information groups, and send the content of the information groups to the structured module. The information groups include at least time groups and customer name groups. The information extraction module includes a text processing submodule, a voice processing submodule, and an image processing submodule. The text processing submodule is used to receive the text content, perform semantic analysis on the text content through natural language processing technology, divide the text data according to the semantic analysis results, and extract key information from it. The speech processing submodule is used to receive speech content, perform noise reduction and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into a deep learning model, extract speech features and map them to acoustic units of phonemes or subphonemes, generate a word sequence based on the acoustic unit sequence and natural language model, normalize the identified word sequence, and perform semantic analysis on the normalized word sequence through natural language processing technology to obtain key information. The image processing submodule is used to receive image content, call the OCR interface, extract text content from the image content using OCR technology, and perform semantic analysis on the text content using natural language processing technology to obtain key information. The structured module uses time and customer name as indexes and uses semantic analysis to reorganize the content of information groups to obtain corresponding business opportunity information, which is then sent to the storage module. The structured module includes a sentence-building module, which calls the artificial intelligence language model interface to sequentially output each information group to the artificial intelligence language model. The artificial intelligence language model reorganizes the content of the information groups through semantic analysis to obtain reorganized sentences. The reorganized sentences are combined with the customer information source to obtain complete business opportunity information. The storage module is used to retrieve the customer name from the database, determine whether the customer is in the data to build the corresponding storage document. If the customer does not exist, the storage document is built with the customer name plus the generated ID, and the business opportunity information is stored in the storage document. If the customer exists, the time in the business opportunity information is obtained, and the business opportunity information is sorted according to the time of different business opportunity information. The reminder module is used to read the top-ranked business opportunity information in the stored document, determine whether the current time has reached the predetermined time, and if so, send the business opportunity information to the corresponding business personnel and trigger the feedback module. The feedback module is used to receive feedback information from salespersons within a time threshold. If feedback information is received within the time threshold, a deletion command is sent to the reminder module. If no feedback information is received within the time threshold, a resend command is sent to the reminder module. After receiving a deletion command, the reminder module removes the top-ranked business opportunity information from the stored document. After receiving the resend instruction, the reminder module resends the business opportunity information to the corresponding business personnel and continues to trigger the feedback module.

2. The business opportunity information management system according to claim 1, characterized in that, It also includes an official website information acquisition submodule, which is used to generate a fourth program interface. The fourth program is used to connect to the client's official website and use web crawler technology to crawl web information in a targeted manner to obtain text content and / or image content.

3. The business opportunity information management system according to claim 1, characterized in that, The information extraction module also includes an input submodule; the input submodule is used to clean the key information, remove redundant, erroneous or irrelevant data, and map the cleaned key information into defined information groups.

4. A method for managing business opportunity information, applied to the business opportunity information management system described in any one of claims 1 to 3, characterized in that, Includes the following steps: Step S1: Collect customer information; Step S2: Segment the customer information and fill the segmented customer information into the information groups according to the preset information groups; Step S3: Using time and customer name as indexes, and semantic analysis to reorganize the information groupings, the corresponding business opportunity information is obtained; Step S4: Use the customer name to search the database and determine whether the customer is in the data to build the corresponding storage document. If it does not exist, build the storage document with the customer name plus a randomly generated ID and store the business opportunity information in the storage document. If it exists, obtain the time in the business opportunity information and sort the business opportunity information according to the time of different business opportunity information. Step S5: Read the top-ranked business opportunity information in the stored document, determine if the current time has reached the scheduled time, and if so, send the business opportunity information to the corresponding business personnel; Step S6: Determine whether feedback information from the salesperson has been received within the time threshold. If feedback information is received within the time threshold, remove the top-ranked business opportunity information in the stored document. If no feedback information is received, repeat step S5.

Images