CN117745125A

CN117745125A - Information processing method, information processing device, electronic equipment and storage medium

Info

Publication number: CN117745125A
Application number: CN202311639404.0A
Authority: CN
Inventors: 周燕川; 贾佳; 王超; 申丹丹
Original assignee: China Construction Bank Corp; CCB Finetech Co Ltd
Current assignee: China Construction Bank Corp; CCB Finetech Co Ltd
Priority date: 2023-12-01
Filing date: 2023-12-01
Publication date: 2024-03-22

Abstract

The disclosure provides an information processing method, an information processing device, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring a main business set of a target enterprise; aiming at any candidate camping service, acquiring an enterprise set which belongs to any candidate camping service; acquiring first fund running information of each reference enterprise, and determining a first fund feature vector of any candidate camping service; acquiring second fund running information of the target enterprise, and determining a second fund feature vector of the target enterprise; a target hosting service for the target enterprise is determined from the set of hosting services based on the first funding feature vector for each candidate hosting service and the second funding feature vector for the target enterprise. Therefore, the main business is identified by tracking the fund condition of the enterprise, and when the main business of the target enterprise changes, the relevant changes of the target enterprise can be tracked in time based on the fund condition of the enterprise.

Description

Information processing method, information processing device, electronic equipment and storage medium

Technical Field

The disclosure relates to the technical field of data processing, and in particular relates to an information processing method, an information processing device, electronic equipment and a storage medium.

Background

Because some small and micro enterprises are restricted by factors such as self multiparty operation, weak financial accounting foundation and the like, the situation that the main business is difficult to accurately judge exists, meanwhile, the main business is influenced by policies, industries and environments, the main business also follows the conversion, and the related changes cannot be tracked in time by the prior art method.

Disclosure of Invention

The disclosure provides an information processing method, an information processing device, electronic equipment and a storage medium, which are used for solving the problem that the primary service of a small enterprise cannot be timely and accurately determined.

To this end, an object of the present disclosure is to propose an information processing method.

A second object of the present disclosure is to propose an information processing apparatus.

A third object of the present disclosure is to propose an electronic device.

A fourth object of the present disclosure is to propose a non-transitory computer readable storage medium.

A fifth object of the present disclosure is to propose a computer programme product.

To achieve the above object, an embodiment of a first aspect of the present disclosure provides an information processing method, including: acquiring a main business set of a target enterprise, wherein the main business set comprises one or more candidate main businesses; for any candidate camping service, acquiring an enterprise set belonging to the same candidate camping service, wherein the enterprise set comprises one or more reference enterprises; acquiring first fund running information of each reference enterprise, and determining a first fund feature vector of any candidate primary service based on the first fund running information of each reference enterprise; acquiring second fund running information of the target enterprise, and determining a second fund feature vector of the target enterprise based on the second fund running information of the target enterprise; a target hosted business for the target enterprise is determined from the set of hosted businesses based on the first fund feature vector for each candidate hosted business and the second fund feature vector for the target enterprise.

According to one embodiment of the disclosure, the determining the first fund feature vector of the any candidate hosting service based on the first fund flowing information of each reference enterprise includes: determining a first upstream fund occurrence for payment to an upstream and a first downstream fund occurrence for receipt from a downstream for each first period for the reference enterprise based on the first fund flowing information; determining a first payout funds occurrence total and a first in-coming funds occurrence total of the reference enterprise in each first period based on the first funds running information; for each first period, determining a first global fund feature of the first period corresponding to the any candidate camping service based on a first upstream fund occurrence amount and a first payout fund occurrence total amount of the first period; determining a second global fund feature of the first period corresponding to the any candidate primary service based on a first downstream fund occurrence amount and a first revenue fund occurrence total amount of the first period; a first fund feature vector for the any one candidate host service is determined based on the first global fund feature and the second global fund feature for each of the first periods.

According to one embodiment of the present disclosure, the determining of the first global funding feature includes: determining a first sub-fund feature of the first period based on a first upstream fund occurrence amount and a first payout fund occurrence amount of the first period; determining the first sub-funding feature of the same first period in a plurality of second periods, and determining a first average sub-funding feature of the first period based on the first sub-funding feature of the first period in the plurality of second periods for each first period; the first global funding feature is determined based on a first average sub-funding feature of the first period for each of the reference enterprises.

According to one embodiment of the present disclosure, the determining of the second global funding feature includes: determining a second sub-fund feature of the first period based on a first downstream fund occurrence amount and a first revenue fund occurrence amount of the first period; determining the second sub-funding feature of the same first period in a plurality of second periods, and determining a second average sub-funding feature of the first period for each first period based on the second sub-funding feature of the first period in the plurality of second periods; the second global funding feature is determined based on a second average sub-funding feature of the first period for each of the reference enterprises.

According to one embodiment of the disclosure, the determining the second fund feature vector of the target enterprise based on the second fund flowing information of the target enterprise includes: determining a second upstream funds occurrence for payment to the upstream and a second downstream funds occurrence for receipt from the downstream for each first period for the target enterprise based on the second funds movement information; determining a second payout funds occurrence total and a second revenue funds occurrence total of the target enterprise in each first period based on the second funds running information; determining, for each of the first periods, a third global fund feature for the first period for the target enterprise based on a second upstream fund occurrence amount and a second payout fund occurrence total amount for the first period; determining a fourth global funds characteristic of the first period for the target enterprise based on a second downstream funds occurrence amount and a second revenue funds occurrence total amount for the first period; a second funding feature vector for the target enterprise is determined based on the third global funding feature and the fourth global funding feature for each of the first periods.

According to one embodiment of the present disclosure, the determining of the third global funding feature includes: determining a third sub-fund feature of the first period based on a second upstream fund occurrence amount and a second payout fund occurrence amount of the first period; determining the third sub-funding feature for the same first cycle in a plurality of second cycles; for each first period, averaging the third sub-funding features of the first period over the plurality of second periods, determining the third global funding feature.

According to one embodiment of the present disclosure, the determining of the fourth global fund feature includes: determining a fourth sub-fund feature of the first period based on a second downstream fund occurrence amount and a second revenue fund occurrence amount of the first period; determining the fourth sub-funding feature for the same first period in a plurality of second periods; for each first period, averaging the fourth sub-funding features of the first period over the plurality of second periods to determine the fourth global funding feature.

According to one embodiment of the disclosure, the determining the target hosting service of the target enterprise from the hosting service set based on the first fund feature vector of each candidate hosting service and the second fund feature vector of the target enterprise includes: for each candidate camping service, obtaining the similarity between the first fund feature vector and the second fund feature vector; and selecting the candidate camping service with the similarity larger than or equal to the set similarity threshold as the target camping service.

According to one embodiment of the disclosure, the first fund feature vector includes a first global fund feature and a second global fund feature of the first period corresponding to the candidate hosting service, the second fund feature vector includes a third global fund feature and a fourth global fund feature of each first period of the target service, and the similarity between the first fund feature vector and the second fund feature vector is obtained by adopting the following formula:

Wherein the E_Avg (E _i ) For the first global funding feature of the ith first period, the F_Avg (F _i ) The second global resource for the ith first periodGold feature, the A_Avg (e _i ) For the third global funding feature of the ith first period, the b_avg (f _i ) And the fourth global fund feature for the ith first period.

According to one embodiment of the present disclosure, the obtaining a hosting service set of a target enterprise includes: the hosting service set of the target enterprise is determined according to one or more of a business, production information, and/or a service scope in which the target enterprise is located.

According to one embodiment of the present disclosure, the method further comprises: aiming at any enterprise of the target enterprise and the candidate enterprise, extracting key information of fund running information of any enterprise to obtain field elements; classifying and marking the fund flowing water of any enterprise to obtain a transaction object; and determining the upstream fund generation amount and the downstream fund generation amount of each first period of any enterprise, and the total amount of the expenditure funds generation amount and the total amount of the income funds generation amount of each first period according to the field elements and the transaction objects.

To achieve the above object, an embodiment of a second aspect of the present disclosure provides an information processing apparatus including: the first acquisition module is used for acquiring a main business set of a target enterprise, wherein the main business set comprises one or more candidate main businesses; the second acquisition module is used for acquiring an enterprise set which belongs to any candidate camping service and comprises one or more reference enterprises aiming at any candidate camping service; the first determining module is used for acquiring first fund running information of each reference enterprise and determining a first fund feature vector of any candidate principal business based on the first fund running information of each reference enterprise; the second determining module is used for acquiring second fund running information of the target enterprise and determining a second fund feature vector of the target enterprise based on the second fund running information of the target enterprise; and a third determining module, configured to determine a target camping service of the target enterprise from the camping service set based on the first fund feature vector of each candidate camping service and the second fund feature vector of the target enterprise.

According to one embodiment of the disclosure, the first determining module is further configured to: determining a first upstream fund occurrence for payment to an upstream and a first downstream fund occurrence for receipt from a downstream for each first period for the reference enterprise based on the first fund flowing information; determining a first payout funds occurrence total and a first in-coming funds occurrence total of the reference enterprise in each first period based on the first funds running information; for each first period, determining a first global fund feature of the first period corresponding to the any candidate camping service based on a first upstream fund occurrence amount and a first payout fund occurrence total amount of the first period; determining a second global fund feature of the first period corresponding to the any candidate primary service based on a first downstream fund occurrence amount and a first revenue fund occurrence total amount of the first period; a first fund feature vector for the any one candidate host service is determined based on the first global fund feature and the second global fund feature for each of the first periods.

According to one embodiment of the disclosure, the first determining module is further configured to: determining a first sub-fund feature of the first period based on a first upstream fund occurrence amount and a first payout fund occurrence amount of the first period; determining the first sub-funding feature of the same first period in a plurality of second periods, and determining a first average sub-funding feature of the first period based on the first sub-funding feature of the first period in the plurality of second periods for each first period; the first global funding feature is determined based on a first average sub-funding feature of the first period for each of the reference enterprises.

According to one embodiment of the disclosure, the first determining module is further configured to: determining a second sub-fund feature of the first period based on a first downstream fund occurrence amount and a first revenue fund occurrence amount of the first period; determining the second sub-funding feature of the same first period in a plurality of second periods, and determining a second average sub-funding feature of the first period for each first period based on the second sub-funding feature of the first period in the plurality of second periods; the second global funding feature is determined based on a second average sub-funding feature of the first period for each of the reference enterprises.

According to one embodiment of the disclosure, the second determining module is further configured to: determining a second upstream funds occurrence for payment to the upstream and a second downstream funds occurrence for receipt from the downstream for each first period for the target enterprise based on the second funds movement information; determining a second payout funds occurrence total and a second revenue funds occurrence total of the target enterprise in each first period based on the second funds running information; determining, for each of the first periods, a third global fund feature for the first period for the target enterprise based on a second upstream fund occurrence amount and a second payout fund occurrence total amount for the first period; determining a fourth global funds characteristic of the first period for the target enterprise based on a second downstream funds occurrence amount and a second revenue funds occurrence total amount for the first period; a second funding feature vector for the target enterprise is determined based on the third global funding feature and the fourth global funding feature for each of the first periods.

According to one embodiment of the disclosure, the second determining module is further configured to: determining a third sub-fund feature of the first period based on a second upstream fund occurrence amount and a second payout fund occurrence amount of the first period; determining the third sub-funding feature for the same first cycle in a plurality of second cycles; for each first period, averaging the third sub-funding features of the first period over the plurality of second periods, determining the third global funding feature.

According to one embodiment of the disclosure, the second determining module is further configured to: determining a fourth sub-fund feature of the first period based on a second downstream fund occurrence amount and a second revenue fund occurrence amount of the first period; determining the fourth sub-funding feature for the same first period in a plurality of second periods; for each first period, averaging the fourth sub-funding features of the first period over the plurality of second periods to determine the fourth global funding feature.

An embodiment according to the present disclosure is characterized in that the third determining module is further configured to: for each candidate camping service, obtaining the similarity between the first fund feature vector and the second fund feature vector; and selecting the candidate camping service with the similarity larger than or equal to the set similarity threshold as the target camping service.

According to one embodiment of the disclosure, the third determining module is further configured to:

wherein the E_Avg (E _i ) For the first global funding feature of the ith first period, the F_Avg (F _i ) For the second global funding feature of the ith first period, the a_avg (e _i ) For the third global funding feature of the ith first period, the b_avg (f _i ) And the fourth global fund feature for the ith first period.

According to one embodiment of the disclosure, the first obtaining module is further configured to: the hosting service set of the target enterprise is determined according to one or more of a business, production information, and/or a service scope in which the target enterprise is located.

According to one embodiment of the present disclosure, the apparatus further comprises: aiming at any enterprise of the target enterprise and the candidate enterprise, extracting key information of fund running information of any enterprise to obtain field elements; classifying and marking the fund flowing water of any enterprise to obtain a transaction object; and determining the upstream fund generation amount and the downstream fund generation amount of each first period of any enterprise, and the total amount of the expenditure funds generation amount and the total amount of the income funds generation amount of each first period according to the field elements and the transaction objects.

To achieve the above object, an embodiment of a third aspect of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to implement the information processing method according to the embodiments of the first aspect of the present disclosure.

To achieve the above object, a fourth aspect embodiment of the present disclosure proposes a non-transitory computer-readable storage medium storing computer instructions for implementing an information processing method according to an embodiment of the first aspect of the present disclosure.

To achieve the above object, an embodiment of a fifth aspect of the present disclosure proposes a computer program product comprising a computer program for implementing an information processing method according to an embodiment of the first aspect of the present disclosure when the computer program is executed by a processor.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.

Fig. 1 is a flowchart illustrating an information processing method according to an embodiment of the present disclosure;

FIG. 2 is a flowchart illustrating another information processing method according to an embodiment of the present disclosure;

FIG. 3 is a flowchart illustrating another information processing method according to an embodiment of the present disclosure;

FIG. 4 is a flowchart illustrating another information processing method according to an embodiment of the present disclosure;

FIG. 5 is a flowchart illustrating another information processing method according to an embodiment of the present disclosure;

FIG. 6 is a flowchart illustrating a process for determining a target hosting service for a target enterprise according to an embodiment of the present disclosure;

fig. 7 is a diagram showing an example of the structure of an information processing apparatus according to an embodiment of the present disclosure;

fig. 8 is a diagram illustrating a structure of an electronic device according to an embodiment of the present disclosure.

Specific embodiments of the present disclosure have been shown by way of the above drawings and will be described in more detail below. These drawings and the written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the disclosed concepts to those skilled in the art by reference to specific embodiments.

Detailed Description

In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.

The data acquisition, storage, use, processing and the like in the technical scheme of the present disclosure all conform to the relevant regulations of the national laws and regulations.

Fig. 1 is a flowchart illustrating an information processing method according to an embodiment of the present disclosure. As shown in fig. 1, the information processing method includes:

s101, acquiring a main service set of a target enterprise, wherein the main service set comprises one or more candidate main services.

It should be noted that, the execution body of the information processing method provided in the embodiment of the present disclosure is an electronic device, and the electronic device may be a terminal device. Alternatively, the terminal device may be a mobile electronic device or a non-mobile electronic device. By way of example, the mobile electronic device may be a cell phone, tablet, notebook, palmtop, vehicle-mounted electronic device, wearable device, ultra-mobile personal computer (UMPC), netbook or personal digital assistant (personal digital assistant, PDA), etc., and the non-mobile electronic device may be a network attached storage (Network Attached Storage, NAS), personal computer (personal computer, PC), television (TV), teller machine or self-service machine, etc. The embodiments of the present disclosure are not particularly limited.

It will be appreciated that a camping business refers to a major activity in a daily activity undertaken by an enterprise to accomplish its business objectives, and may be determined based on a major business scope specified on an enterprise's business license.

In some implementations, one or more candidate camping services may be determined based on enterprise information of the target enterprise, resulting in a set of camping services for the target enterprise. Alternatively, the enterprise information may be manually analyzed to determine candidate camping services. Candidate camping services may also be automatically generated by the management system based on the enterprise information.

Optionally, the enterprise information of the target enterprise includes, but is not limited to: the industry in which the target enterprise is located, production information, the business scope of the target enterprise, etc.

S102, aiming at any candidate camping service, acquiring an enterprise set which belongs to any candidate camping service, wherein the enterprise set comprises one or more reference enterprises.

In some implementations, the database may be established based on a correspondence between the enterprise and the candidate camping service to which it belongs. For any candidate main business, the database can be queried to acquire the reference enterprises belonging to the candidate main business, and then the main business set is traversed to acquire one or more reference enterprises belonging to any candidate main business, so as to acquire the enterprise set.

S103, acquiring first fund running information of each reference enterprise, and determining a first fund feature vector of any candidate primary service based on the first fund running information of each reference enterprise.

In some implementations, for each reference business, the first fund flowing information for each reference business may be determined by obtaining financial statements, payment records, contracts, invoices, and the like for the reference business. The amount of revenue and expenditure for any reference business may be determined from the first fund running information.

Optionally, for any candidate primary service, the sub-fund feature of any reference enterprise may be determined based on the income and expense amounts of any reference enterprise, so as to calculate an average sub-fund feature of any reference enterprise in a set period. Based on the average sub-fund characteristics of any reference enterprise, the fund characteristics of each reference enterprise can be obtained, and then the first fund characteristic vector of any candidate primary service is determined according to the fund characteristics of each reference enterprise.

S104, acquiring second fund flow information of the target enterprise, and determining a second fund feature vector of the target enterprise based on the second fund flow information of the target enterprise.

In some implementations, the second fund flowing information of the target business may be determined by obtaining financial statements, payment records, contracts, invoices, and the like of the target business. And determining the income and expense amounts of the target enterprises from the second fund running information.

Optionally, the sub-fund feature of the target enterprise may be determined based on the income and expense amounts of the target enterprise, so as to obtain the sub-fund feature of the target enterprise in a plurality of setting periods. Based on the plurality of sub-fund features of the target enterprise, the fund features of the target enterprise can be obtained, and further, a second fund feature vector of the target enterprise is determined according to the fund features of the target enterprise.

Alternatively, the fund features of the target enterprise may be obtained by calculating an average value of the plurality of fund features.

S105, determining a target principal business of the target enterprise from the principal business set based on the first principal feature vector of each candidate principal business and the second principal feature vector of the target enterprise.

In some implementations, the target hosted business of the target enterprise may be determined from a set of hosted businesses by calculating a similarity between the first and second funding feature vectors and based on a magnitude of the similarity.

Alternatively, the similarity between the first funding feature vector and the second funding feature vector may be determined by calculating a cosine value between the first funding feature vector and the second funding feature vector. The magnitude of similarity of the first and second fund feature vectors may be determined by determining whether the cosine value is within a target range. For example, if the cosine value is within (0, 1), the similarity between the first and second fund feature vectors is greater.

Optionally, if the similarity between the first fund feature vector and the second fund feature vector is greater, selecting the candidate camping service corresponding to the first fund feature vector as the target camping service.

The main service set includes a candidate main service 1 and a candidate main service 2. And if the cosine value between A and C is equal to-0.1, and the cosine value between B and C is equal to 0.5 and is in a target range, the more similar between B and C is indicated, the candidate primary service 2 is selected as the target primary service of the target enterprise.

In the information processing method provided by the embodiment of the disclosure, a target enterprise is analyzed to obtain a main business set of the target enterprise, and for any candidate main business, an enterprise set which belongs to any candidate main business is obtained. And further, for each reference enterprise in the enterprise set, acquiring first fund running information, determining a first fund feature vector of the candidate host business, acquiring second fund running information of the target enterprise, determining a second fund feature vector of the target enterprise, and determining the target host business of the target enterprise based on the first fund feature vector and the second fund feature vector. The method can simply acquire data such as fund running information, has high data availability, can identify the main business by tracking the fund condition of the enterprise, and can timely track the related change of the target enterprise based on the fund condition of the enterprise when the main business of the target enterprise changes.

Fig. 2 is a flowchart illustrating an information processing method according to an embodiment of the present disclosure. As shown in fig. 2, the information processing method includes:

s201, a main business set of a target enterprise is obtained, wherein the main business set comprises one or more candidate main businesses.

S202, for any candidate camping service, acquiring an enterprise set which belongs to any candidate camping service, wherein the enterprise set comprises one or more reference enterprises.

S203, first fund flow information of each reference enterprise is acquired.

The relevant content of step S201 to step S203 can be referred to the above embodiment, and will not be described here again.

S204, determining a first upstream fund generation amount for paying the upstream and a first downstream fund generation amount for receiving from the downstream in each first period of the reference enterprise based on the first fund flowing information.

S205, determining a first payout funds generation total and a first income funds generation total of the reference enterprise in each first period based on the first funds flowing information.

In some implementations, the upstream funds occurrence represents an amount of expenditure for an upstream customer or individual, and the downstream funds occurrence represents an amount of revenue for a downstream customer. The payout funds total represents the payout total and the revenue funds total represents the revenue total.

In some implementations, the first upstream funds occurrence amount, the first downstream funds occurrence amount, the first payout funds occurrence total amount, and the first income funds occurrence total amount may be determined from the first funds flow information according to field elements and transaction objects of the first funds flow information, so as to facilitate analysis of funds flow, and make feature processing more convenient.

Optionally, for any enterprise of the target enterprise and the candidate enterprise, key information extraction can be performed on the funds running information of any enterprise, so as to obtain the field element. Wherein the field elements include, but are not limited to: transaction time, transaction amount, transaction opponent name, transaction opponent uniform social credit code (e.g., for business opponents), transaction remarks (instructions), expense/income flag, etc.

Further, the fund flowing water of any enterprise is classified and marked, and a transaction object is obtained. Wherein, the transaction objects can be divided into: upstream businesses or individuals, downstream customers, other traders, etc. And determining the upstream fund generation amount and the downstream fund generation amount of each first period of any enterprise, and the total amount of the expenditure funds generation amount and the total amount of the income funds generation amount of each first period according to the field elements and the transaction objects. Wherein the first period may be one month.

For example, assuming that the first period is 3 months, for the first fund running information of any reference enterprise in 3 months, determining field elements as payouts from the fund running information, and determining that the transaction time is within 3 months and the transaction object is the amount of money of the upstream enterprise or the person, the amount of money is the first upstream fund occurrence of 3 months, which indicates the amount of money paid to the upstream enterprise or the person in 3 months.

And determining the field element as expenditure from the first fund running information, wherein the fund amount of the transaction time within 3 months is the total occurrence amount of the first expenditure fund of 3 months, and the total amount of the fund paid out in 3 months is represented.

And determining field elements as income from the fund running information, wherein the transaction time is within 3 months, and the transaction object is the amount of funds of the downstream clients, and the amount of funds is the first downstream funds occurrence amount of 3 months, and represents the income amount of funds for the downstream clients in 3 months.

And determining the field element as income from the first fund running information, wherein the fund amount of the transaction time within 3 months is the first income fund occurrence total of 3 months, and represents the fund total of income within 3 months.

S206, for each first period, determining a first global fund feature of the first period corresponding to any candidate primary service based on the first upstream fund occurrence amount and the first payout fund occurrence total amount of the first period.

In some implementations, changes in the enterprise funds characteristics may be determined by calculating an average sub-funds characteristic of the same first period over a plurality of second periods and determining a global funds characteristic of the first period based on the average sub-funds characteristic in order to track the running water information of the enterprise in time. Wherein the first period may be one month and the second period may be year. For example, the first period is 4 months, and then the same first period in the second period is 4 months of different years.

In some implementations, the first average sub-fund feature of the first period may be determined based on the first sub-fund feature of the first period, and the first global fund feature may be determined based on the first average sub-fund feature of each reference enterprise in the set of reference enterprises.

Optionally, a first sub-fund feature of the first period is determined based on a first upstream fund occurrence amount and a first payout fund occurrence amount of the first period. The formula for calculating the first sub-funding feature is as follows:

wherein E represents a first sub-funding feature.

Optionally, the first average sub-fund feature of the first period is determined by determining a first sub-fund feature of the same first period in the plurality of second periods and, for each first period, based on the first sub-fund features of the first period in the plurality of second periods. The formula for calculating the first average sub-funding feature is as follows:

where n represents the number of years spanned by the data taken and m represents the first period, i.e., month. Avg (E) represents the first average sub-funding feature and E represents the first sub-funding feature.

For example, m takes 3 months and n takes 4, then the first period is 3 months and comprises 4 second periods, i.e., based on the first sub-fund feature of 3 months for 4 years, a first average sub-fund feature may be calculated as

Further, a first global funding feature may be determined based on the first average sub-funding feature for the first period for each reference enterprise. The first global funding feature may be obtained by calculating an average of the first average sub-funding features. The formula for calculating the first global fund feature is as follows:

where k represents the number of reference enterprises, j represents the candidate hosting service, avg (E) represents the first average sub-fund feature, and e_avg (E) represents the first global fund feature.

S207, determining a second global fund feature of the first period corresponding to any candidate primary service based on the first downstream fund generation amount and the first income fund generation total amount of the first period.

In some implementations, the second sub-fund feature of the first period may be determined based on the first downstream fund occurrence amount and the first revenue fund occurrence amount of the first period to timely track the running water information of the enterprise to determine changes in the enterprise fund feature. The formula for calculating the second sub-funding feature is as follows:

wherein F represents a second sub-funding feature.

Further, a second sub-funding feature of the same first period in the plurality of second periods is determined, and for each first period, a second average sub-funding feature of the first period is determined based on the second sub-funding features of the first period in the plurality of second periods. The formula for calculating the second average sub-funding feature is as follows:

Where n represents the number of years spanned by the retrieved data, m represents the first period, i.e., month, F represents the second sub-funding feature, and Avg (F) represents the second average sub-funding feature.

Further, a second global funding feature is determined based on the second average sub-funding feature for the first period for each reference enterprise. The second global funding feature may be obtained by calculating an average of the second average sub-funding features for each reference enterprise. The formula for calculating the second global fund feature is as follows:

where k represents the number of reference enterprises, j represents the candidate hosting service, avg (F) represents the second global funds feature, and f_avg (F) represents the second average sub-funds feature.

And S208, determining a first fund feature vector of any candidate primary service based on the first global fund feature and the second global fund feature of each first period.

In some implementations, the first funding feature vector may be formed based on a combination of the first global funding feature and the second global funding feature. Alternatively, the first global fund feature and the second global fund feature of each first period may be used as one dimension in the fund feature vector, and then combined to form the first fund feature vector. The first funding feature vector is as follows:

S _j ＝{E_Avg(E _j1 )、…、E_Avg(E _j12 )、F_Avg(F _j1 )、…、F_Avg(F _j12 )} (7)

Wherein j represents a candidate camping service. E_Avg (E) _j1 ) Then the first global fund feature for 1 month of any candidate camping service is represented.

S209, obtaining second fund flowing information of the target enterprise, and determining a second fund feature vector of the target enterprise based on the second fund flowing information of the target enterprise.

S210, determining a target principal business of the target enterprise from the principal business set based on the first principal feature vector of each candidate principal business and the second principal feature vector of the target enterprise.

The relevant content of step S209 to step S210 can be referred to the above embodiment, and will not be described here again.

In the information processing method provided by the embodiment of the disclosure, a target enterprise is analyzed to obtain a main business set of the target enterprise, and for any candidate main business, an enterprise set which belongs to any candidate main business is obtained. And further, for each reference enterprise in the enterprise set, acquiring first fund running information, determining the income and the expenditure amount, determining a first fund feature vector of the candidate main service, acquiring second fund running information of the target enterprise, determining a second fund feature vector of the target enterprise, and determining the target main service of the target enterprise based on the first fund feature vector and the second fund feature vector. The method can simply acquire data such as fund running information, has high data availability, can identify the main business by tracking the fund condition of the enterprise, and can timely track the related change of the target enterprise based on the fund condition of the enterprise when the main business of the target enterprise changes.

Fig. 3 is a flowchart illustrating an information processing method according to an embodiment of the present disclosure. As shown in fig. 3, the information processing method includes:

s301, acquiring a main service set of a target enterprise, wherein the main service set comprises one or more candidate main services.

S302, for any candidate camping service, an enterprise set which belongs to any candidate camping service is obtained, wherein the enterprise set comprises one or more reference enterprises.

S303, acquiring first fund running information of each reference enterprise, and determining a first fund feature vector of any candidate host business based on the first fund running information of each reference enterprise.

S304, second fund flow information of the target enterprise is obtained.

The relevant content of step S301 to step S304 can be referred to the above embodiments, and will not be described here again.

S305, determining a second upstream fund generation amount for paying the upstream and a second downstream fund generation amount for receiving the downstream of the target enterprise in each first period based on the second fund flowing information.

S306, determining a second payout funds generation total amount and a second income funds generation total amount of the target enterprise in each first period based on the second funds running information.

In some implementations, a second upstream funds occurrence and a second downstream funds occurrence, and a second payout funds occurrence and a second revenue funds occurrence of the target enterprise may be determined based on field elements and transaction objects of the target enterprise.

Optionally, aiming at the target enterprise, extracting key information of second fund flowing information of the target enterprise, obtaining field elements, and classifying and marking the fund flowing of the target enterprise to obtain the transaction object. Wherein the field elements include, but are not limited to: transaction time, transaction amount, trade opponent name, trade opponent uniform social credit code, trade remarks, expense/income flag, etc. The transaction objects may be divided into: upstream businesses or individuals, downstream customers, other traders, etc.

Further, a second upstream funds occurrence and a second downstream funds occurrence for each first period, and a second payout funds occurrence and a second revenue funds occurrence for each first period, of the target business may be determined based on the field elements and the transaction objects.

For example, assuming that the first period is 3 months, based on the second fund flowing information of the target enterprise in 3 months, determining field elements as payouts from the second fund flowing information, and the transaction time is within 3 months and the transaction object is the amount of money of the upstream enterprise or the person, the amount of money is the second upstream fund occurrence amount of 3 months, which indicates the amount of money paid to the upstream enterprise or the person in 3 months.

S307, for each first period, determining a third global fund feature of the first period of the target enterprise based on the second upstream fund occurrence amount and the second payout fund occurrence total amount of the first period.

In some implementations, the change in the enterprise funds characteristics may be determined by calculating an average sub-funds characteristic of the first period over the plurality of second periods and determining a global funds characteristic of the first period based on the average sub-funds characteristic in order to track the running water information of the target enterprise in time.

Alternatively, a third sub-fund feature of the first period may be determined based on the second upstream fund occurrence amount and the second payout fund occurrence amount of the first period. The third sub-funding feature e may be calculated according to equation (1) above, then

Further, a third sub-funding feature of the same first cycle in the plurality of second cycles is determined. For each first period, a third global fund feature is determined by averaging third sub-fund features of the first period over a plurality of second periods.

And S308, determining a fourth global fund feature of the first period of the target enterprise based on the second downstream fund generation amount and the second income fund generation total amount of the first period.

In some implementations, a fourth sub-fund feature of the first period may be determined based on the second downstream fund occurrence amount and the second revenue fund occurrence amount of the first period. Alternatively, a fourth sub-funding feature f may be calculated based on equation (4) above, then

Further, a fourth sub-funding feature of the same first period over the plurality of second periods is determined. For each first period, a fourth global fund feature is determined by averaging the fourth sub-fund features of the first period over a plurality of second periods.

S309, determining a second fund feature vector of the target enterprise based on the third global fund feature and the fourth global fund feature of each first period.

In some implementations, the second funding feature vector may be formed based on a combination of the third global funding feature and the fourth global funding feature. Alternatively, the third global fund feature and the fourth global fund feature of each first period may be used as one dimension of the fund feature vectors, and then combined to form the second fund feature vector. The second funding feature vector is as follows:

O _t ＝{A_Avg(e _t1 )、…、A_Avg(e _t12 )、B_Avg(f _t1 )、…、B_Avg(f _t12 ) (8)

where t represents the target enterprise, A_Avg (e) represents the third global funds feature, B_Avg (f) represents the fourth global funds feature, e represents the third sub-funds feature, and f represents the fourth sub-funds feature.

S310, determining a target principal business of the target enterprise from the principal business set based on the first principal feature vector of each candidate principal business and the second principal feature vector of the target enterprise.

The relevant content of step S310 may be referred to the above embodiments, and will not be described herein.

In the information processing method provided by the embodiment of the disclosure, a target enterprise is analyzed to obtain a main business set of the target enterprise, and for any candidate main business, an enterprise set which belongs to any candidate main business is obtained. And further, for each reference enterprise in the enterprise set, acquiring first fund running information, determining a first fund feature vector of the candidate principal business, acquiring second fund running information of the target enterprise, determining income and expense of the target enterprise, determining a second fund feature vector of the target enterprise, and determining the target principal business of the target enterprise based on the first fund feature vector and the second fund feature vector. The method can simply acquire data such as fund running information, has high data availability, can identify the main business by tracking the fund condition of the enterprise, and can timely track the related change of the target enterprise based on the fund condition of the enterprise when the main business of the target enterprise changes.

Fig. 4 is a flowchart illustrating an information processing method according to an embodiment of the present disclosure. As shown in fig. 4, the information processing method includes:

s401, determining a main service set of the target enterprise according to one or more of the industries, production information and/or service ranges of the target enterprise.

In some implementations, the set of camping services may be obtained by analyzing the industry, production information, and/or service scope in which the target enterprise is located, knowing information about the industry market size, enterprise resources, etc., and analyzing the products of the target enterprise to determine one or more candidate camping services that are relevant to the target enterprise.

S402, for any candidate camping service, acquiring an enterprise set which belongs to any candidate camping service, wherein the enterprise set comprises one or more reference enterprises.

S403, acquiring first fund running information of each reference enterprise, and determining a first fund feature vector of any candidate primary service based on the first fund running information of each reference enterprise.

S404, second fund flowing information of the target enterprise is obtained, and a second fund feature vector of the target enterprise is determined based on the second fund flowing information of the target enterprise.

The relevant content of step S402 to step S404 can be referred to the above embodiments, and will not be described here again.

S405, for each candidate camping service, the similarity between the first fund feature vector and the second fund feature vector is obtained.

In some implementations, the first funding feature vector includes first global funding features and second global funding features of a first period corresponding to the candidate host business, and the second funding feature vector includes third global funding features and fourth global funding features of each first period of the target business.

Optionally, the similarity between the first fund feature vector and the second fund feature vector can be calculated based on a vector space cosine theorem, so that the similarity between the vectors can be conveniently and rapidly obtained. The formula for calculating the similarity between the first and second funding feature vectors is as follows:

wherein E_Avg (E _i ) For the first global funding feature of the ith first period, F_Avg (F _i ) For the second global funding feature of the ith first period, a_avg (e _i ) For the third global funding feature of the ith first period, B_Avg (f _i ) A fourth global funding feature for the ith first period.

S406, selecting candidate camping services with similarity larger than or equal to the set similarity threshold as target camping services.

In some implementations, the target camping service may be determined based on the magnitude of the similarity. Optionally, a similarity threshold may be preset, and if the similarity of any candidate camping service is greater than or equal to the similarity threshold, which indicates that the candidate camping service is similar to the camping service of the target enterprise, the candidate camping service is the target camping service.

In some implementations, when a plurality of candidate host services are included in the host service set, a plurality of candidate host services with similarity greater than or equal to a set similarity threshold are required to be calculated, and the candidate host services are used as candidate target host services, and a candidate target host service table of the target enterprise is generated based on the similarity and the corresponding candidate target host services.

Alternatively, the candidate target primary service table may be provided to service personnel, and the service personnel determines the similarity between the target enterprise and each candidate target primary service based on the table, and may select the candidate target primary service with the largest similarity as the target primary service of the target enterprise.

In the information processing method provided by the embodiment of the disclosure, a target enterprise is analyzed to obtain a main business set of the target enterprise, and for any candidate main business, an enterprise set which belongs to any candidate main business is obtained. And further, for each reference enterprise in the enterprise set, acquiring first fund running information, determining a first fund feature vector of the candidate host business, acquiring second fund running information of the target enterprise, determining a second fund feature vector of the target enterprise, and determining the target host business of the target enterprise by calculating the similarity of the first fund feature vector and the second fund feature vector. The vector similarity is calculated by adopting the cosine theorem, so that simple and direct similarity calculation can be realized, and the efficiency of determining the target camping service is higher. The method can simply acquire data such as fund running information, has high data availability, can identify the main business by tracking the fund condition of the enterprise, and can timely track the related change of the target enterprise based on the fund condition of the enterprise when the main business of the target enterprise changes.

Fig. 5 is a flowchart illustrating an information processing method according to an embodiment of the present disclosure. As shown in fig. 5, the information processing method includes:

s501, a main business set of a target enterprise is obtained, wherein the main business set comprises one or more candidate main businesses.

S502, for any candidate camping service, acquiring an enterprise set which belongs to any candidate camping service, wherein the enterprise set comprises one or more reference enterprises.

S503, acquiring first fund running information of each reference enterprise and second fund running information of the target enterprise.

S504, determining a first upstream fund occurrence for paying upstream and a first downstream fund occurrence for receiving downstream for each first period for the reference enterprise based on the first fund flowing information.

S505, determining a first payout funds generation total and a first income funds generation total of the reference enterprise in each first period based on the first funds flowing information.

S506, for each first period, determining a first global fund feature of the first period corresponding to any candidate primary service based on the first upstream fund occurrence amount and the first payout fund occurrence total amount of the first period.

S507, determining a second global fund feature of the first period corresponding to any candidate primary service based on the first downstream fund generation amount and the first income fund generation total amount of the first period.

And S508, determining a first fund feature vector of any candidate primary service based on the first global fund feature and the second global fund feature of each first period.

S509, determining, based on the second funds running information, a second upstream funds occurrence for paying the upstream and a second downstream funds occurrence for receiving from the downstream for each first period for the target enterprise.

S510, determining a second payout fund generation total amount and a second income fund generation total amount of the target enterprise in each first period based on the second fund running information.

S511, for each first period, determining a third global fund feature of the first period of the target enterprise based on the second upstream fund occurrence amount and the second payout fund occurrence total amount of the first period.

And S512, determining a fourth global fund feature of the first period of the target enterprise based on the second downstream fund generation amount and the second income fund generation total amount of the first period.

And S513, determining a second fund feature vector of the target enterprise based on the third global fund feature and the fourth global fund feature of each first period.

S514, for each candidate camping service, the similarity between the first fund feature vector and the second fund feature vector is obtained.

S515, selecting candidate camping services with similarity larger than or equal to the set similarity threshold as target camping services.

A flow chart of a target hosting business for determining a target enterprise is shown in fig. 6. For a target enterprise, one or more candidate camping services of the target enterprise may be determined by manual or systematic analysis, and a set of camping services is formed. For any candidate camping business, one or more reference enterprises belonging to the candidate camping business are obtained, and an enterprise set is generated. And collecting first fund running information of each reference enterprise and second fund running information of the target enterprise, analyzing and marking the fund running information, and determining trade opponents of the reference enterprise and the target enterprise so as to determine the occurrence amount of upstream fund, the occurrence amount of downstream fund and the like of the reference enterprise and the target enterprise. Further, a first fund feature vector of any candidate camping service of the first period (month) and a second fund feature vector of the target enterprise are determined, the similarity between the first fund feature vector and the second fund feature vector is calculated based on a vector space cosine theorem, and the target camping service of the target enterprise can be determined according to the similarity.

In correspondence with the information processing methods provided in the above-described several embodiments, an embodiment of the present disclosure further provides an information processing apparatus, and since the information processing apparatus provided in the embodiment of the present disclosure corresponds to the information processing method provided in the above-described several embodiments, implementation of the information processing method described above is also applicable to the information processing apparatus provided in the embodiment of the present disclosure, and will not be described in detail in the following embodiments.

Fig. 7 is a diagram showing an example of the structure of an information processing apparatus according to an embodiment of the present disclosure. As shown in fig. 7, the information processing apparatus includes: a first acquisition module 701, a second acquisition module 702, a first determination module 703, a second determination module 704 and a third determination module 705.

The first obtaining module 701 is configured to obtain a camping service set of a target enterprise, where the camping service set includes one or more candidate camping services.

A second obtaining module 702, configured to obtain, for any candidate camping service, a set of enterprises that belong to the candidate camping service, where the set of enterprises includes one or more reference enterprises.

A first determining module 703, configured to obtain first fund flowing information of each of the reference enterprises, and determine a first fund feature vector of the any candidate hosting service based on the first fund flowing information of each of the reference enterprises.

A second determining module 704, configured to obtain second fund flowing information of the target enterprise, and determine a second fund feature vector of the target enterprise based on the second fund flowing information of the target enterprise.

A third determining module 705, configured to determine a target camping service of the target enterprise from the camping service set based on the first funding feature vector of each candidate camping service and the second funding feature vector of the target enterprise.

According to one embodiment of the present disclosure, the first determining module 703 is further configured to: determining a first upstream fund occurrence for payment to an upstream and a first downstream fund occurrence for receipt from a downstream for each first period for the reference enterprise based on the first fund flowing information; determining a first payout funds occurrence total and a first in-coming funds occurrence total of the reference enterprise in each first period based on the first funds running information; for each first period, determining a first global fund feature of the first period corresponding to the any candidate camping service based on a first upstream fund occurrence amount and a first payout fund occurrence total amount of the first period; determining a second global fund feature of the first period corresponding to the any candidate primary service based on a first downstream fund occurrence amount and a first revenue fund occurrence total amount of the first period; a first fund feature vector for the any one candidate host service is determined based on the first global fund feature and the second global fund feature for each of the first periods.

According to one embodiment of the present disclosure, the first determining module 703 is further configured to: determining a first sub-fund feature of the first period based on a first upstream fund occurrence amount and a first payout fund occurrence amount of the first period; determining the first sub-funding feature of the same first period in a plurality of second periods, and determining a first average sub-funding feature of the first period based on the first sub-funding feature of the first period in the plurality of second periods for each first period; the first global funding feature is determined based on a first average sub-funding feature of the first period for each of the reference enterprises.

According to one embodiment of the present disclosure, the first determining module 703 is further configured to: determining a second sub-fund feature of the first period based on a first downstream fund occurrence amount and a first revenue fund occurrence amount of the first period; determining the second sub-funding feature of the same first period in a plurality of second periods, and determining a second average sub-funding feature of the first period for each first period based on the second sub-funding feature of the first period in the plurality of second periods; the second global funding feature is determined based on a second average sub-funding feature of the first period for each of the reference enterprises.

According to one embodiment of the present disclosure, the second determining module 704 is further configured to: determining a second upstream funds occurrence for payment to the upstream and a second downstream funds occurrence for receipt from the downstream for each first period for the target enterprise based on the second funds movement information; determining a second payout funds occurrence total and a second revenue funds occurrence total of the target enterprise in each first period based on the second funds running information; determining, for each of the first periods, a third global fund feature for the first period for the target enterprise based on a second upstream fund occurrence amount and a second payout fund occurrence total amount for the first period; determining a fourth global funds characteristic of the first period for the target enterprise based on a second downstream funds occurrence amount and a second revenue funds occurrence total amount for the first period; a second funding feature vector for the target enterprise is determined based on the third global funding feature and the fourth global funding feature for each of the first periods.

According to one embodiment of the present disclosure, the second determining module 704 is further configured to: determining a third sub-fund feature of the first period based on a second upstream fund occurrence amount and a second payout fund occurrence amount of the first period; determining the third sub-funding feature for the same first cycle in a plurality of second cycles; for each first period, averaging the third sub-funding features of the first period over the plurality of second periods, determining the third global funding feature.

According to one embodiment of the present disclosure, the second determining module 704 is further configured to: determining a fourth sub-fund feature of the first period based on a second downstream fund occurrence amount and a second revenue fund occurrence amount of the first period; determining the fourth sub-funding feature for the same first period in a plurality of second periods; for each first period, averaging the fourth sub-funding features of the first period over the plurality of second periods to determine the fourth global funding feature.

According to an embodiment of the disclosure, the third determining module 705 is further configured to: for each candidate camping service, obtaining the similarity between the first fund feature vector and the second fund feature vector; and selecting the candidate camping service with the similarity larger than or equal to the set similarity threshold as the target camping service.

According to one embodiment of the present disclosure, the third determining module 705 is further configured to:

According to an embodiment of the present disclosure, the first obtaining module 701 is further configured to: the hosting service set of the target enterprise is determined according to one or more of a business, production information, and/or a service scope in which the target enterprise is located.

In the information processing device provided by the embodiment of the disclosure, the target enterprise is analyzed to obtain the main business set of the target enterprise, and the enterprise set which belongs to any candidate main business is obtained for any candidate main business. And further, for each reference enterprise in the enterprise set, acquiring first fund running information, determining a first fund feature vector of the candidate host business, acquiring second fund running information of the target enterprise, determining a second fund feature vector of the target enterprise, and determining the target host business of the target enterprise based on the first fund feature vector and the second fund feature vector. The method can simply acquire data such as fund running information, has high data availability, can identify the main business by tracking the fund condition of the enterprise, and can timely track the related change of the target enterprise based on the fund condition of the enterprise when the main business of the target enterprise changes.

Fig. 8 is a diagram illustrating a structure of an electronic device according to an embodiment of the present disclosure. As shown in fig. 8, the electronic device 800 may include: a transceiver 801, a processor 802, and a memory 803.

Processor 802 executes the computer-executable instructions stored in the memory, causing processor 802 to perform the aspects of the embodiments described above. The processor 802 may be a general-purpose processor including a central processing unit CPU, a network processor (network processor, NP), etc.; but may also be a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

The memory 803 is coupled to the processor 802 via a system bus and communicates with each other, and the memory 803 is adapted to store computer program instructions.

The transceiver 801 may be used to obtain tasks to be run and configuration information for the tasks to be run.

The system bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The system bus may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus. The transceiver is used to enable communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). The memory may include random access memory (random access memory, RAM) and may also include non-volatile memory (non-volatile memory).

The electronic device provided by the embodiment of the present disclosure may be a terminal device of the foregoing embodiment.

The embodiment of the disclosure also provides a chip for executing the instruction, which is used for executing the technical scheme of the information processing method in the embodiment.

The embodiment of the present disclosure further provides a computer readable storage medium, where computer instructions are stored, which when executed on a computer, cause the computer to execute the technical solution of the information processing method of the foregoing embodiment.

The embodiment of the present disclosure also provides a computer program product, where the computer program product includes a computer program, where the computer program is stored in a computer readable storage medium, and at least one processor may read the computer program from the computer readable storage medium, and the technical solution of the information processing method in the foregoing embodiment may be implemented by at least one processor when the computer program is executed.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An information processing method, characterized in that the method comprises:

acquiring a main business set of a target enterprise, wherein the main business set comprises one or more candidate main businesses;

for any candidate camping service, acquiring an enterprise set belonging to the same candidate camping service, wherein the enterprise set comprises one or more reference enterprises;

acquiring first fund running information of each reference enterprise, and determining a first fund feature vector of any candidate primary service based on the first fund running information of each reference enterprise;

acquiring second fund running information of the target enterprise, and determining a second fund feature vector of the target enterprise based on the second fund running information of the target enterprise;

a target hosted business for the target enterprise is determined from the set of hosted businesses based on the first fund feature vector for each candidate hosted business and the second fund feature vector for the target enterprise.

2. The method of claim 1, wherein determining the first fund feature vector for any of the candidate host businesses based on the first fund flowing information for each of the reference businesses comprises:

determining a first upstream fund occurrence for payment to an upstream and a first downstream fund occurrence for receipt from a downstream for each first period for the reference enterprise based on the first fund flowing information;

determining a first payout funds occurrence total and a first in-coming funds occurrence total of the reference enterprise in each first period based on the first funds running information;

for each first period, determining a first global fund feature of the first period corresponding to the any candidate camping service based on a first upstream fund occurrence amount and a first payout fund occurrence total amount of the first period;

determining a second global fund feature of the first period corresponding to the any candidate primary service based on a first downstream fund occurrence amount and a first revenue fund occurrence total amount of the first period;

a first fund feature vector for the any one candidate host service is determined based on the first global fund feature and the second global fund feature for each of the first periods.

3. The method of claim 2, wherein the determining of the first global funding feature comprises:

determining a first sub-fund feature of the first period based on a first upstream fund occurrence amount and a first payout fund occurrence amount of the first period;

determining the first sub-funding feature of the same first period in a plurality of second periods, and determining a first average sub-funding feature of the first period based on the first sub-funding feature of the first period in the plurality of second periods for each first period;

the first global funding feature is determined based on a first average sub-funding feature of the first period for each of the reference enterprises.

4. The method of claim 2, wherein the determining of the second global funding feature comprises:

determining a second sub-fund feature of the first period based on a first downstream fund occurrence amount and a first revenue fund occurrence amount of the first period;

determining the second sub-funding feature of the same first period in a plurality of second periods, and determining a second average sub-funding feature of the first period for each first period based on the second sub-funding feature of the first period in the plurality of second periods;

The second global funding feature is determined based on a second average sub-funding feature of the first period for each of the reference enterprises.

5. The method of claim 1, wherein the determining a second fund feature vector for the target enterprise based on the second fund flowing information for the target enterprise comprises:

determining a second upstream funds occurrence for payment to the upstream and a second downstream funds occurrence for receipt from the downstream for each first period for the target enterprise based on the second funds movement information;

determining a second payout funds occurrence total and a second revenue funds occurrence total of the target enterprise in each first period based on the second funds running information;

determining, for each of the first periods, a third global fund feature for the first period for the target enterprise based on a second upstream fund occurrence amount and a second payout fund occurrence total amount for the first period;

determining a fourth global funds characteristic of the first period for the target enterprise based on a second downstream funds occurrence amount and a second revenue funds occurrence total amount for the first period;

a second funding feature vector for the target enterprise is determined based on the third global funding feature and the fourth global funding feature for each of the first periods.

6. The method of claim 5, wherein the determining of the third global funding feature comprises:

determining a third sub-fund feature of the first period based on a second upstream fund occurrence amount and a second payout fund occurrence amount of the first period;

determining the third sub-funding feature for the same first cycle in a plurality of second cycles;

for each first period, averaging the third sub-funding features of the first period over the plurality of second periods, determining the third global funding feature.

7. The method of claim 5, wherein the determining of the fourth global funding feature comprises:

determining a fourth sub-fund feature of the first period based on a second downstream fund occurrence amount and a second revenue fund occurrence amount of the first period;

determining the fourth sub-funding feature for the same first period in a plurality of second periods;

for each first period, averaging the fourth sub-funding features of the first period over the plurality of second periods to determine the fourth global funding feature.

8. The method of any of claims 1-7, wherein the determining the target hosted business for the target enterprise from the hosted business collection based on the first funding feature vector for each of the candidate hosted businesses and the second funding feature vector for the target enterprise comprises:

For each candidate camping service, obtaining the similarity between the first fund feature vector and the second fund feature vector;

and selecting the candidate camping service with the similarity larger than or equal to the set similarity threshold as the target camping service.

9. The method of claim 8, wherein the first funding feature vector comprises a first global funding feature and a second global funding feature of the first period corresponding to the candidate host service, the second funding feature vector comprises a third global funding feature and a fourth global funding feature of each first period of the target service, and wherein a similarity between the first funding feature vector and the second funding feature vector is obtained using the following formula:

10. The method of claim 1, wherein the obtaining the hosting service set for the target enterprise comprises:

The hosting service set of the target enterprise is determined according to one or more of a business, production information, and/or a service scope in which the target enterprise is located.

11. The method according to claim 2 or 5, characterized in that the method further comprises:

aiming at any enterprise of the target enterprise and the candidate enterprise, extracting key information of fund running information of any enterprise to obtain field elements;

classifying and marking the fund flowing water of any enterprise to obtain a transaction object;

and determining the upstream fund generation amount and the downstream fund generation amount of each first period of any enterprise, and the total amount of the expenditure funds generation amount and the total amount of the income funds generation amount of each first period according to the field elements and the transaction objects.

12. An information processing apparatus, characterized in that the apparatus comprises:

the first acquisition module is used for acquiring a main business set of a target enterprise, wherein the main business set comprises one or more candidate main businesses;

the second acquisition module is used for acquiring an enterprise set which belongs to any candidate camping service and comprises one or more reference enterprises aiming at any candidate camping service;

The first determining module is used for acquiring first fund running information of each reference enterprise and determining a first fund feature vector of any candidate principal business based on the first fund running information of each reference enterprise;

the second determining module is used for acquiring second fund running information of the target enterprise and determining a second fund feature vector of the target enterprise based on the second fund running information of the target enterprise;

and a third determining module, configured to determine a target camping service of the target enterprise from the camping service set based on the first fund feature vector of each candidate camping service and the second fund feature vector of the target enterprise.

13. The apparatus of claim 12, wherein the first determining module is further configured to:

14. The apparatus of claim 13, wherein the first determining module is further configured to:

15. The apparatus of claim 13, wherein the first determining module is further configured to:

16. The apparatus of claim 12, wherein the second determining module is further configured to:

17. The apparatus of claim 16, wherein the second determining module is further configured to:

18. The apparatus of claim 16, wherein the second determining module is further configured to:

19. The apparatus of any one of claims 12-18, wherein the third determining module is further configured to:

20. The apparatus of claim 19, wherein the third determination module is further configured to:

21. The apparatus of claim 12, wherein the first acquisition module is further configured to:

22. The apparatus according to claim 13 or 16, characterized in that the apparatus further comprises:

23. An electronic device, comprising:

A processor, and a memory communicatively coupled to the processor;

the memory stores computer-executable instructions;

the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1-11.

24. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-11.

25. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-11.