CN115577093B - AI analysis method and system for financial information - Google Patents
AI analysis method and system for financial information Download PDFInfo
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- CN115577093B CN115577093B CN202210588569.9A CN202210588569A CN115577093B CN 115577093 B CN115577093 B CN 115577093B CN 202210588569 A CN202210588569 A CN 202210588569A CN 115577093 B CN115577093 B CN 115577093B
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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
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/335—Filtering based on additional data, e.g. user or group profiles
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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
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
Abstract
The application provides an AI analysis method system of financial information, the method includes: the terminal searches policy information within a specific period of time before a specific point of time at the specific point of time; the terminal performs word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, inputs an AI model to the keywords, and performs type recognition to determine industry keywords and policy department keywords in the keywords; the terminal extracts a first level corresponding to the policy department keyword, inquires the history policy information which is the same as the first level, inquires m pieces of history policy information which is the same as the industry keyword from the history policy information, extracts a first trend after the release date of the history policy information corresponding to the first history trend, determines the first trend as an analysis result corresponding to the financial information, and pushes the analysis result to a user. The technical scheme provided by the application has the advantage of high user experience.
Description
Technical Field
The invention relates to the fields of finance and the Internet, in particular to an AI analysis method and system for financial information.
Background
Financial information refers to signals, instructions, data, conditions, messages generated during the process of organizing and managing currency circulation, various financial securities exchanges, credit activities, and funds settlement, the contents of which include government financial information, exchange rate information, securities market information, customer credit information, etc.
The existing analysis of the financial information is performed manually, so that the financial information cannot be automatically analyzed, and the timeliness of the financial analysis is further affected.
Disclosure of Invention
The embodiment of the invention provides an AI analysis method and an AI analysis system for financial information, which can analyze the financial information in an AI mode, thereby improving the timeliness of the financial analysis and improving the user experience.
In a first aspect, an embodiment of the present invention provides an AI analysis method for financial information, including the steps of:
the terminal searches policy information within a specific period of time before a specific point of time at the specific point of time;
the terminal performs word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, inputs an AI model to the keywords, and performs type recognition to determine industry keywords and policy department keywords in the keywords;
the terminal extracts a first level corresponding to the key word of the policy department, inquires the history policy information which is the same as the first level, inquires m pieces of history policy information which is the same as the key word of the industry from the history policy information, acquires m pieces of history trends corresponding to the m pieces of history policy information, searches a first history trend which is the most similar to the current trend from the m pieces of history trends, extracts a first trend after the release date of the history policy information corresponding to the first history trend, determines the first trend as an analysis result corresponding to the financial information, and pushes the analysis result to a user.
Optionally, the industry keywords include: industry names or industry concept words.
Optionally, the obtaining m history trends corresponding to the m history policy information specifically includes:
the method comprises the steps of obtaining m release times of m pieces of history policy information, extracting m historical trends of industries corresponding to the m pieces of history policy information in a set time interval, wherein the set time interval is a time interval with set duration, and the center point of the set time interval is the release time of the m pieces of history policy information.
Optionally, the searching the m historical trends for the first historical trend most similar to the current trend specifically includes:
the method comprises the steps of obtaining the number x of days of current trend, extracting x price k lines of the previous x days, extracting m segmentation trends before m release times from m historical trends, inquiring historical trends corresponding to the segmentation trend closest to the x price k lines from the m segmentation trends, and determining the historical trends as first historical trends.
In a second aspect, there is provided an AI analysis system for financial information, the system comprising:
a search unit for searching policy information within a specific period of time before a specific point of time at the specific point of time;
the processing unit is used for carrying out word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, inputting the keywords into the AI model, and carrying out type recognition on the keywords to determine industry keywords and policy department keywords in the keywords; extracting a first level corresponding to the key word of the policy department, inquiring the history policy information which is the same as the first level, inquiring m pieces of history policy information which is the same as the key word of the industry from the history policy information, acquiring m pieces of history trends corresponding to the m pieces of history policy information, searching a first history trend which is the most similar to the current trend from the m pieces of history trends, extracting a first trend after the release date of the history policy information corresponding to the first history trend, determining the first trend as an analysis result corresponding to the financial information, and pushing the analysis result to a user.
Optionally, the industry keywords include: industry names or industry concept words.
Optionally, the processing unit is specifically configured to obtain m release times of the m historical policy information, extract m historical trends of the industry corresponding to the m historical policy information in a set time interval, where the set time interval is a time interval with a set duration, and a center point of the set time interval is the release time of the m historical policy information.
Optionally, the processing unit is specifically configured to obtain a number x of days of the current trend, extract x price k lines of the previous x days, extract m segment trends before m release times from the m historical trends, and query a historical trend corresponding to a segment trend most similar to the x price k lines from the m segment trends to determine the first historical trend.
In a third aspect, a computer-readable storage medium storing a program for electronic data exchange is provided, wherein the program causes a terminal to execute the method provided in the first aspect.
The embodiment of the invention has the following beneficial effects:
it can be seen that the technical scheme terminal provided by the application searches the policy information in a specific period before a specific time point at the specific time point; the terminal performs word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, inputs an AI model to the keywords, and performs type recognition to determine industry keywords and policy department keywords in the keywords; the terminal extracts a first level corresponding to the key word of the policy department, inquires the history policy information which is the same as the first level, inquires m pieces of history policy information which is the same as the key word of the industry from the history policy information, acquires m pieces of history trends corresponding to the m pieces of history policy information, searches a first history trend which is the most similar to the current trend from the m pieces of history trends, extracts a first trend after the release date of the history policy information corresponding to the first history trend, determines the first trend as an analysis result corresponding to the financial information, and pushes the analysis result to a user. According to the technical scheme, the corresponding recommendation trend is obtained through grading treatment of the policy information, so that corresponding recommendation is provided for the user, and the experience of the user is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structure of a terminal
FIG. 2 is a flow chart of an AI analysis method of financial information;
fig. 3 is a schematic diagram of the structure of an AI analysis system for financial information.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. 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 terms "first," "second," "third," and "fourth" and the like in the description and in the claims and drawings are used for distinguishing between different objects and not necessarily for describing a particular sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, result, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Referring to fig. 1, fig. 1 provides a terminal, where the terminal may be a terminal of an IOS, an android, etc. system, and of course, may also be a terminal of another system, for example, a hong mo, etc., and the application is not limited to the specific system, and as shown in fig. 1, the terminal device may specifically include: the processor, memory, display screen, communication circuitry, and audio components (optional) may be connected by a bus, or may be connected by other means, and the present application is not limited to the specific manner of connection described above.
Referring to fig. 2, fig. 2 provides an AI-analysis method of financial information, which may be implemented in a terminal connected to a network device by a wireless means, which may be specifically a wireless communication system, as shown in fig. 2.
Step S201, the terminal searches the policy information in a specific period before a specific time point at the specific time point;
the specific time point may be a specific time period of 8 am or 7 am, and the specific time period may be 24 hours, 48 hours, 1 week, and the like.
Step S202, the terminal performs word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, and performs type recognition on the input AI models of the keywords to determine industry keywords and policy department keywords in the keywords;
for example, the word segmentation method may be a conventional word segmentation method, and the word segmentation method is not limited herein.
By way of example, the industry keywords include, but are not limited to: industry names, such as wind power, coal, electricity, etc., although industry keywords may also be industry concept words, including but not limited to: meta universe, east-west algorithm, etc.
For example, the AI model may specifically include: classifier or neural network models, etc.
Step S203, the terminal extracts a first level corresponding to the policy department keyword, inquires the history policy information which is the same as the first level, inquires m pieces of history policy information which is the same as the industry keyword from the history policy information, acquires m pieces of history trends corresponding to the m pieces of history policy information, searches a first history trend which is the most similar to the current trend from the m pieces of history trends, extracts a first trend after the release date of the history policy information corresponding to the first history trend, determines the first trend as an analysis result corresponding to the financial information, and pushes the analysis result to the user.
By way of example, the above-mentioned levels may include in particular: administrative level.
For example, the obtaining m history trends corresponding to the m history policy information may specifically include:
the method comprises the steps of obtaining m release times of m pieces of history policy information, extracting m historical trends of industries corresponding to the m pieces of history policy information in a set time interval, wherein the set time interval is a time interval with set duration, and the center point of the set time interval is the release time of the m pieces of history policy information.
The set time interval may be specifically 1 month or 2 months, and the m distribution times are based on days, for example, 18 days in 5 months in 2020.
By way of example, the searching for the first historical trend from the m historical trends that is most similar to the current trend may specifically include:
the method comprises the steps of obtaining the number x of days of current trend, extracting x price k lines of the previous x days, extracting m segmentation trends before m release times from m historical trends, inquiring historical trends corresponding to the segmentation trend closest to the x price k lines from the m segmentation trends, and determining the historical trends as first historical trends.
For example, the extracting the first trend after the release date of the history policy information corresponding to the first history trend may specifically include:
the rise and fall condition and the total amount of the rise and fall amplitude of the first history trend after its release time are determined, and the rise and fall condition and the total amount of the rise and fall amplitude are determined as information contained in the first trend.
Referring to fig. 3, fig. 3 provides a schematic structural diagram of an AI analysis system for financial information, the system including:
a search unit 301 for searching policy information within a specific period of time before a specific point of time at the specific point of time;
the processing unit 302 is configured to perform word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, and perform type recognition on the plurality of keywords input into the AI model to determine an industry keyword and a policy department keyword in the plurality of keywords; extracting a first level corresponding to the key word of the policy department, inquiring the history policy information which is the same as the first level, inquiring m pieces of history policy information which is the same as the key word of the industry from the history policy information, acquiring m pieces of history trends corresponding to the m pieces of history policy information, searching a first history trend which is the most similar to the current trend from the m pieces of history trends, extracting a first trend after the release date of the history policy information corresponding to the first history trend, determining the first trend as an analysis result corresponding to the financial information, and pushing the analysis result to a user.
The technical scheme terminal searches the policy information in a specific period before a specific time point at the specific time point; the terminal performs word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, inputs an AI model to the keywords, and performs type recognition to determine industry keywords and policy department keywords in the keywords; the terminal extracts a first level corresponding to the key word of the policy department, inquires the history policy information which is the same as the first level, inquires m pieces of history policy information which is the same as the key word of the industry from the history policy information, acquires m pieces of history trends corresponding to the m pieces of history policy information, searches a first history trend which is the most similar to the current trend from the m pieces of history trends, extracts a first trend after the release date of the history policy information corresponding to the first history trend, determines the first trend as an analysis result corresponding to the financial information, and pushes the analysis result to a user. According to the technical scheme, the corresponding recommendation trend is obtained through grading treatment of the policy information, so that corresponding recommendation is provided for the user, and the experience of the user is improved.
Optionally, the industry keywords include: industry names or industry concept words.
Optionally, the processing unit is specifically configured to obtain m release times of the m historical policy information, extract m historical trends of the industry corresponding to the m historical policy information in a set time interval, where the set time interval is a time interval with a set duration, and a center point of the set time interval is the release time of the m historical policy information.
Optionally, the processing unit is specifically configured to obtain a number x of days of the current trend, extract x price k lines of the previous x days, extract m segment trends before m release times from the m historical trends, and query a historical trend corresponding to a segment trend most similar to the x price k lines from the m segment trends to determine the first historical trend.
The embodiment of the present invention also provides a computer storage medium storing a computer program for electronic data exchange, the computer program causing a computer to execute part or all of the steps of any one of the AI-analysis methods of financial information as set forth in the above-described method embodiment.
Embodiments of the present invention also provide a computer program product comprising a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of an AI analysis method of financial information, as set forth in any one of the method embodiments above.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts, as some steps may be performed in other orders or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are alternative embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as the division of the units, merely a logical function division, and there may be additional manners of dividing the actual implementation, such as multiple units or components may be combined or integrated into another system, 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 units, or may be in electrical or other forms.
Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be implemented by a program that instructs associated hardware, and the program may be stored in a computer readable memory, which may include: flash disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.
The foregoing has outlined rather broadly the more detailed description of embodiments of the invention, wherein the principles and embodiments of the invention are explained in detail using specific examples, the above examples being provided solely to facilitate the understanding of the method and core concepts of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (9)
1. An AI analysis method of financial information, the method comprising the steps of:
the terminal searches policy information within a specific period of time before a specific point of time at the specific point of time;
the terminal performs word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, inputs an AI model to the keywords, and performs type recognition to determine industry keywords and policy department keywords in the keywords;
the terminal extracts a first level corresponding to the key word of the policy department, inquires the history policy information which is the same as the first level, inquires m pieces of history policy information which is the same as the key word of the industry from the history policy information, acquires m pieces of history trends corresponding to the m pieces of history policy information, searches a first history trend which is the most similar to the current trend from the m pieces of history trends, extracts a first trend after the release date of the history policy information corresponding to the first history trend, determines the first trend as an analysis result corresponding to the financial information, and pushes the analysis result to a user.
2. The method of claim 1, wherein the industry keywords comprise: industry names or industry concept words.
3. The method of claim 1, wherein the obtaining m history trends corresponding to the m history policy information specifically includes:
the method comprises the steps of obtaining m release times of m pieces of history policy information, extracting m historical trends of industries corresponding to the m pieces of history policy information in a set time interval, wherein the set time interval is a time interval with set duration, and the center point of the set time interval is the release time of the m pieces of history policy information.
4. The method according to claim 1, wherein searching for a first historical trend from the m historical trends that is most similar to the current trend specifically comprises:
the method comprises the steps of obtaining the number x of days of current trend, extracting x price k lines of the previous x days, extracting m segmentation trends before m release times from m historical trends, inquiring the historical trend corresponding to the segmentation trend most similar to the x price k lines from the m segmentation trends, and determining the historical trend as a first historical trend.
5. An AI analysis system for financial information, the system comprising:
a search unit for searching policy information within a specific period of time before a specific point of time at the specific point of time;
the processing unit is used for carrying out word segmentation processing on the policy information to obtain a plurality of keywords of the policy information, inputting the keywords into the AI model, and carrying out type recognition on the keywords to determine industry keywords and policy department keywords in the keywords; extracting a first level corresponding to the key word of the policy department, inquiring the history policy information which is the same as the first level, inquiring m pieces of history policy information which is the same as the key word of the industry from the history policy information, acquiring m pieces of history trends corresponding to the m pieces of history policy information, searching a first history trend which is the most similar to the current trend from the m pieces of history trends, extracting a first trend after the release date of the history policy information corresponding to the first history trend, determining the first trend as an analysis result corresponding to the financial information, and pushing the analysis result to a user.
6. The system of claim 5, wherein the industry keywords comprise: industry names or industry concept words.
7. The system of claim 5, wherein the system further comprises a controller configured to control the controller,
the processing unit is specifically configured to obtain m release times of the m pieces of history policy information, extract m historical trends of industries corresponding to the m pieces of history policy information in a set time interval, where the set time interval is a time interval with a set duration, and a center point of the set time interval is the release time of the m pieces of history policy information.
8. The system of claim 5, wherein the system further comprises a controller configured to control the controller,
the processing unit is specifically configured to obtain a number x of days of a current trend, extract x price k lines of a previous x days, extract m segmentation trends of m release times from m historical trends, and query a historical trend corresponding to a segmentation trend most similar to the x price k lines from the m segmentation trends to determine a first historical trend.
9. A computer-readable storage medium storing a program for electronic data exchange, wherein the program causes a terminal to perform the method of any one of claims 1-4.
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