CN110737749A - Entrepreneurship plan evaluation method, entrepreneurship plan evaluation device, computer equipment and storage medium - Google Patents
Entrepreneurship plan evaluation method, entrepreneurship plan evaluation device, computer equipment and storage medium Download PDFInfo
- Publication number
- CN110737749A CN110737749A CN201910980350.1A CN201910980350A CN110737749A CN 110737749 A CN110737749 A CN 110737749A CN 201910980350 A CN201910980350 A CN 201910980350A CN 110737749 A CN110737749 A CN 110737749A
- Authority
- CN
- China
- Prior art keywords
- startup
- entrepreneurship
- plan
- case
- documents
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
- G06F16/31—Indexing; Data structures therefor; Storage structures
-
- 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
- G06F16/3331—Query processing
- G06F16/3332—Query translation
- G06F16/3334—Selection or weighting of terms from queries, including natural language queries
-
- 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
- G06F16/35—Clustering; Classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Artificial Intelligence (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The embodiment of the invention discloses startup plan evaluation methods and devices, computer equipment and a storage medium.
Description
Technical Field
The embodiment of the invention relates to the field of innovation spaces, in particular to a method and a device for evaluating startup plans, computer equipment and a storage medium.
Background
The technological innovation is changing day by day, the public entrepreneurship is fiercely, and the innovation and entrepreneurship become new states and trends for creating employment in the future society.
At present, China is in a stage of vigorously supporting entrepreneurship enterprises, but various examinations are inevitably encountered on the way of independent entrepreneurship, entrepreneurship success can be realized under the situation of surf and sand washing, and the survivors are the feather unicorn.
Disclosure of Invention
The embodiment of the invention provides startup plans evaluation methods and devices, computer equipment and a storage medium, which can realize objective evaluation on startup plans, reduce labor cost for evaluating the startup plans and improve efficiency for evaluating the startup.
, an embodiment of the present invention provides a entrepreneurship plan evaluation method, including:
receiving a startup plan uploaded by a user, and acquiring description information of the startup plan;
inquiring a target evaluation model matched with the description information, and inputting the startup plan into the target evaluation model to obtain a startup evaluation result of the startup plan;
and analyzing the startup plan, determining the optimization information of the startup plan, and providing the optimization information for the user.
In a second aspect, an embodiment of the present invention further provides an kinds of startup plan evaluation devices, including:
receiving a startup plan uploaded by a user, and acquiring description information of the startup plan;
inquiring a target evaluation model matched with the description information, and inputting the startup plan into the target evaluation model to obtain a startup evaluation result of the startup plan;
and analyzing the startup plan, determining the optimization information of the startup plan, and providing the optimization information for the user.
In a third aspect, an embodiment of the present invention further provides computer apparatuses, including a memory, a processor, and a computer program stored on the memory and operable on the processor, where the processor executes the computer program to implement the startup plan evaluation method according to any of in the embodiment of the present invention.
In a fourth aspect, the embodiment of the present invention further provides computer-readable storage media, on which a computer program is stored, where the computer program, when executed by a processor, implements the startup plan evaluation method according to any in the embodiment of the present invention.
The embodiment of the invention screens the target evaluation model from the plurality of evaluation models to evaluate the startup plan by describing information of the startup plan to obtain the startup evaluation result of the startup plan, analyzes the startup plan to obtain the optimization information, provides the startup suggestion of the user, solves the problems that a method for evaluating the startup plan and a platform for providing the startup suggestion do not exist in the prior art, can automatically realize the evaluation of the startup plan and automatically provide the startup suggestion, reduces the labor cost for evaluating the startup plan, ensures the objectivity of the startup plan evaluation, and simultaneously evaluates the startup plan by the evaluation models to improve the accuracy of the startup evaluation result.
Drawings
FIG. 1 is a flowchart of a startup plan evaluation method in example of the present invention;
FIG. 2a is a flowchart of an evaluation method for startup projects in the second embodiment of the present invention;
FIG. 2b is a flowchart of an evaluation method for startup projects in the second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an startup plan evaluation device in the third embodiment of the present invention;
fig. 4 is a schematic structural diagram of computer devices in the fourth embodiment of the present invention.
Detailed Description
The present invention will now be described in further detail with reference to the drawings and examples, it being understood that the specific embodiments herein described are merely illustrative of and not restrictive on the broad invention, and it should be further noted that for the purposes of description, only some, but not all, of the structures associated with the present invention are shown in the drawings.
Example
Fig. 1 is a flowchart of a startup plan evaluation method in , which is applicable to a case where success/failure evaluation is performed on a startup plan provided by a user and a corresponding startup improvement suggestion is provided, and which can be executed by a startup plan evaluation device provided in an embodiment of the present invention, where the device can be implemented in software and/or hardware, and is generally integrated into a computer device, such as a server, as shown in fig. 1, where the method of this embodiment specifically includes:
and S110, receiving the startup plan uploaded by the user and acquiring the description information of the startup plan.
In general, a startup may be divided into a research phase, a verification development phase, a financing phase, and a marketing phase.
The investigation stage specifically includes selecting technical directions, fully collecting information such as market evaluation, questionnaire results, technical evaluation reports, representative scientific and technical literature and the like, and analyzing and counting the collected information to judge the establishment prospect of the technical directions or technical points.
The verification development stage specifically comprises the following steps: according to the research stage, a research and development plan, a technical research and development and the like are made, a product is formed, and feasibility evaluation analysis is carried out on the product, such as feasibility questionnaire survey results of the product collected after being put into the market. And improving the product according to the analysis result, and the like.
In the process of the two stages, team construction, product release, company registration and the like are realized simultaneously.
A business plan is full project plans that are primarily intended to be delivered to an investor so that they can make a judgment about an enterprise or project to obtain financing for the enterprise.
The financing stage specifically comprises the following steps: and forming a business plan, providing the business plan to each investor, and raising funds.
The marketing stage specifically comprises the following steps: and (4) formulating a marketing strategy of the product, and selling the product according to the marketing strategy of the product to realize profit.
A startup plan may refer to a document provided by a user that includes startup information. The startup information may include information for the research phase, the verification development phase, the financing phase, and the marketing phase. It should be noted that the business plan includes the contents of the investigation phase and the verification development phase, that is, the startup plan includes the information of the business plan, the financing phase and the marketing phase.
The description information is used to determine the stage of the startup plan.
In fact, the startup plan uploaded by the user may be information of a partial startup phase. Illustratively, the startup plan includes only the business plan book, and the business plan book may be subjected to startup evaluation.
The description information may be information uploaded by the user at the same time when the startup plan is uploaded. Or performing stage analysis on the startup plan, and extracting keywords capable of describing the startup stage from the startup plan as description information. In addition, the description information may also be obtained in other ways, and thus, the embodiment of the present invention is not limited in particular.
The obtaining of the description information of the startup plan includes: and acquiring the startup stage key words in the startup plan, and determining the description information of the startup plan.
The startup stage keywords are used for determining a startup stage to which the startup case document belongs, and for example, the startup stage keywords include production test products and are used for determining that the startup stage is a verification research and development stage. The startup stage keywords can be extracted from the startup plan and used as the description information of the startup plan. The keyword is extracted from the startup plan to serve as the description information of the startup plan so as to determine the matched evaluation model, and the objective analysis of the startup plan is ensured, so that the evaluation accuracy of the startup plan is improved.
Optionally, before receiving the startup plan uploaded by the user, the method further includes collecting startup case documents, obtaining keywords matched with the startup case documents, storing the startup case documents in a classified manner according to the keywords matched with the startup case documents to form a startup case database, and establishing an index according to a matching relationship between the keywords and the startup case documents, wherein the startup case database includes at least startup databases, financing databases and marketing databases.
The startup case documents may include at least startup news, startup papers, startup templates (e.g., business plan templates), startup case articles, and the like, as described below.
The classification direction of the startup case documents can comprise at least items including startup stage, startup result, startup field, product type, marketing, management team, share right structure, investor, financial management plan, operation plan, financing plan and the like.
The keyword extraction method includes various methods, such as a Term Frequency-Inverse Document Frequency algorithm (TF-IDF), a Latent Semantic Analysis (LSA), a web Page ranking algorithm (Page Rank), and the like, which may be specifically set according to needs, and the embodiments of the present invention are not limited specifically.
For example, the startup case database comprises a startup database, a financing database and a marketing database, wherein the startup database is used for storing startup case documents associated with a research and development stage, a verification and development stage and a company registration stage, the actual startup database is used for storing startup case documents associated with a startup preparation stage, the financing database is used for storing startup case documents associated with a financing stage, and the marketing database is used for storing startup case documents associated with a product marketing stage.
According to the corresponding relation between the keywords extracted from the startup case documents and the startup case documents, an index can be established, so that a user can search the startup case documents based on the keywords.
In addition, when collecting entrepreneurship case documents, if only part of web pages is related to entrepreneurship, multiple sections of texts related to entrepreneurship can be intercepted from the web pages and written into document files to form entrepreneurship case documents.
By collecting entrepreneurship case documents, extracting keywords, classifying and storing the entrepreneurship case documents based on the keywords and establishing indexes of the entrepreneurship case documents, the entrepreneurship case documents are classified and inquired, entrepreneurship data can be effectively collected and provided for users as reference.
Optionally, before receiving the startup plan uploaded by the user, the method further comprises the steps of collecting startup knowledge documents, obtaining keywords matched with the startup knowledge documents, storing the startup knowledge documents in a classified mode according to the keywords matched with the startup knowledge documents to form a startup knowledge database system, and establishing an index according to the matching relation between the keywords and the startup knowledge documents, wherein the startup knowledge database system comprises at least of a law and regulation database, a financial knowledge base, an investor database and a business plan database.
The startup knowledge documents may include at least startup news, startup papers, startup templates (e.g., business plan templates), and startup knowledge articles, among others, as described below.
The startup knowledge document may actually include only startup-related data, providing startup information, while the startup case document includes at least the content of the startup phases and the corresponding startup results, i.e., the startup case document includes startup-related processes and resulting data.
For example, the startup knowledge database system includes at least items including a laws and regulations database, a finance knowledge database, an investor database, and a business plan database.
The law and regulation database is used for storing the law and regulation information related to entrepreneurship; the financial knowledge base is used for storing related financial information of startup; the investor database is used for storing information of investors who can provide funds, and the business plan database is used for storing information related to business plans, such as templates of the business plans, statistical information of the business plans, business plan cases with successful business creation results and the like.
The investor database stores the basic information of each investor, the investment field of the investor and the investment success rate of the investor. The investor database can collect the user portrait of investor in advance to obtain the attribute information of investor, and count the historical investment record of investor and the success and failure result of each investment case to determine the investment field, investment preference and corresponding investment success rate of investor. And counting the investment times and the investment times of successful entrepreneurship structure in each investment field, determining the success rate in the investment field, and writing the success rate into an investor database as the data of the investor.
By collecting the startup knowledge documents, extracting the key words, classifying and storing the startup knowledge documents based on the key words and establishing indexes of all the startup knowledge documents, classification and query of the startup knowledge documents are realized, startup knowledge data can be effectively collected, query is provided, and startup knowledge reference is provided for users.
And S120, inquiring a target evaluation model matched with the description information, and inputting the startup plan into the target evaluation model to obtain a startup evaluation result of the startup plan.
The objective evaluation model is used to evaluate the startup plan. Specifically, multiple evaluation models may be trained in advance, with different evaluation models corresponding to different startup stages. For example, a startup plan includes only business plans, and the goal evaluation model is used to evaluate the business plans.
The evaluation model is a machine learning model trained in advance, and may be any machine learning model capable of realizing classification, and thus, embodiments of the present invention are not limited specifically. The entrepreneurship evaluation result is used for describing an entrepreneurship result of the entrepreneurship plan, and specifically, the entrepreneurship result comprises entrepreneurship success, entrepreneurship failure or entrepreneurship success rate.
Information of successful and failed entrepreneurship stages can be collected to serve as training samples, models are trained, and evaluation models are obtained.
Optionally, the classifying the entrepreneurship case documents according to the keywords matched with the entrepreneurship case documents includes: inquiring the key words of the entrepreneurship stage from the key words matched with each entrepreneurship case document; classifying the entrepreneurship case documents according to the entrepreneurship stage keywords matched with the entrepreneurship case documents to form entrepreneurship case documents of different entrepreneurship stages; before querying the target evaluation model matched with the description information, the method further comprises the following steps: inquiring entrepreneurship result keywords in the keywords matched with each entrepreneurship case document; taking each entrepreneurship case document and the matched entrepreneurship result keywords as training samples; in each entrepreneurship stage, taking a training sample formed by each corresponding entrepreneurship case as a training sample corresponding to the entrepreneurship stage; and respectively training a machine learning model according to the training sample corresponding to each entrepreneurship stage to obtain an evaluation model corresponding to each entrepreneurship stage.
In practice, the startup case documents may include all stages of startup.
The startup case documents are divided into classes or groups of different startup phases according to the startup phase keywords.
And the entrepreneurship result key words are used for determining entrepreneurship success and failure results. The method specifically comprises the following steps: startup success keywords and startup failure keywords. For example, the startup failure keyword includes bankruptcy.
For each startup stage, all startup case documents corresponding to startup stages and the startup result keywords matched with each startup case document are used as training samples corresponding to the startup stage, wherein startup case documents and the matched startup result keywords are used as training samples.
And training the machine learning model according to the training samples to obtain a corresponding evaluation model. The training samples correspond to the startup stage, and correspondingly, the evaluation model corresponds to the startup stage.
It should be noted that the startup case document used as the training sample includes at least startup stage contents and the corresponding startup result.
In addition, the startup plan provided by the user may be a plan including all stages of startup, and may collect startup case documents including all stages to form classes of startup complete stages, and for the startup complete stages, obtain training samples, train and form an evaluation model corresponding to the startup complete stages, and be used to evaluate the startup evaluation results of the plan including all stages of startup.
The entrepreneurship case documents are classified to form entrepreneurship case documents in different entrepreneurship stages, each entrepreneurship case document is obtained to form a training sample, the training sample of each entrepreneurship stage is determined, an evaluation model aiming at each entrepreneurship stage is obtained through training, the evaluation models are distinguished according to the entrepreneurship stages, entrepreneurship evaluation results corresponding to each entrepreneurship stage are evaluated in a targeted mode, entrepreneurship plans are evaluated according to the entrepreneurship stages, and accuracy of the entrepreneurship evaluation results is improved.
S130, analyzing the startup plan, determining the optimization information of the startup plan, and providing the optimization information for the user.
The optimization information is used to provide startup suggestions to the user. For example, the result of the predicted startup evaluation of the startup plan provided by the user is failure, and information of improvement of the startup plan can be provided for the user, so that guidance suggestions are provided for the user.
Analyzing the startup plan and determining the optimization information of the startup plan, which specifically comprises the following steps: the data with high similarity to the startup plan and successful startup can be obtained, and the different data between the data and the startup plan are used as the optimization information of the startup plan and provided for the user as the improvement suggestion of the startup plan.
Optionally, the analyzing the startup plan to determine the optimization information of the startup plan includes querying a matched target necessary content set according to keywords of a startup stage of the startup plan, performing content analysis on the startup plan to determine at least content keywords of the startup plan, determining to-be-supplemented content information of the startup plan according to the target necessary content set and the at least content keywords, extracting type keywords from the startup plan, querying at least matched target case documents in a preconfigured startup case database system according to the type keywords matched with the startup plan, comparing the at least target startup case documents with the startup plan respectively to determine a comparison result of the startup plan, determining the optimization dimension information of the startup plan according to the comparison result of the startup plan and each target startup case document, querying at least matched target knowledge document in a preconfigured startup knowledge database according to the optimization dimension information, and using the to-be-supplemented knowledge information of the startup plan and the target information as at least .
, the startup plan must include settings, for example, in the business plan of the startup preparation phase, including market analysis, prospect analysis, and input-output ratio.
The target necessary content set may be the content that must be included in the startup plan, that is, the content that is essential in the startup plan, in practice, the content that needs to be specified in startup stages is defined in the target necessary content set, and so on, generally, the necessary content corresponding to different startup stages is different,
the method comprises the steps of obtaining necessary content in a startup plan, obtaining content keywords from the startup plan, and extracting the content keywords from the startup plan to determine the content included in the startup plan, wherein the content information to be supplemented of the startup plan is used for prompting a user of the content to be supplemented of the startup plan.
Optionally, keywords other than the at least content keywords in the keywords included in the target necessary content set are used as content information to be supplemented.
Additionally , successful startup plans have rules defined at , while failed startup plans have rules defined at . thus, successful startup case documents can be compared to startup plans with differences being used as improvements, and failed startup case documents can be compared to startup plans with the same being used as improvements.
The type keywords are used for determining the entrepreneurship direction of the entrepreneurship plan, and specifically at least items comprise entrepreneurship fields, types of entrepreneurship products, entrepreneurship strategies (such as financing strategies and marketing strategies) and entrepreneurship financing directions.
Before the entrepreneurship case database system is used for inquiring, the database matched with the entrepreneurship case can be determined according to the entrepreneurship stage key words of the entrepreneurship plan. For example, the startup stage keywords of the startup case include the business plan and financing content, and the matching databases are determined to be the startup database and the financing database.
And selecting a database matched with the entrepreneurship case database system, and inquiring entrepreneurship case documents matched with the entrepreneurship plan in the matched database according to the type keywords matched with the entrepreneurship plan. For example, the type keywords are fruit planting, and the searched startup case documents are all startup associated documents of plant planting.
The target startup case documents are used as standard documents for improvement of the startup plan, and are used to determine the optimized content of the startup plan. The target startup case documents may include startup case documents with successful startup results and/or startup case documents with failed startup results.
The comparison result of the startup plan is used to determine the optimized content of the startup plan, and may specifically include data different from the startup case document whose startup result is successful, and/or data identical to the startup case document whose startup result is failed.
The optimization dimension information may be an improvement suggestion for the startup plan. Specifically, the information determined by counting and integrating the comparison results may be used as the optimization dimension information. More specifically, various data in the comparison result are counted, and the data with the counting times higher than a set time threshold value is used as the optimized dimension information.
And inquiring the target entrepreneurship knowledge document from the entrepreneurship knowledge database according to the optimized dimension information. The target startup knowledge document is provided to the user as startup objective data.
The content information to be supplemented, the optimization dimension information and the target startup knowledge document are used as the optimization information of the startup plan, so that comprehensive, reliable and objective optimization information is provided for the startup plan, the accuracy of the optimization information is improved, and the user experience is improved.
Optionally, the comparing of the at least target startup case documents with the startup plan to determine the comparison result of the startup plan includes dividing the at least target startup cases into a successful startup case set and a failed startup case set according to the startup result keywords matched with the at least target startup case documents, comparing the target startup case documents in the successful startup case set with the startup plan according to at least preset startup evaluation dimensions to obtain different data of the startup plan and the successful startup case documents in different startup evaluation dimensions, comparing the target startup case documents in the failed startup case set with the startup plan according to at least startup evaluation dimensions to obtain the same data of the startup plan and the failed startup case documents in different startup evaluation dimensions, counting the different data of the startup plan and the successful startup case documents in different startup evaluation dimensions, and comparing the same data of the startup plan and the failed startup case documents in different startup evaluation dimensions, and counting the same data of the startup plan and the startup plan as the startup plan.
The startup assessment dimension is used to determine the direction of assessment and may include at least items including market, prospect, input-output ratio, equity ratio, and the like.
It can be understood that the different data of the startup plan and each successful startup case document may be the direction in which the startup plan is to be improved; the same data for the startup plan and each failed startup case document may be the direction in which the startup plan is to be improved.
By configuring a plurality of entrepreneurship evaluation dimensions, acquiring different data of successful entrepreneurship case documents and the same data of failed entrepreneurship case documents under each entrepreneurship evaluation dimension as the optimization information of the entrepreneurship plan, the entrepreneurship plan can be evaluated in multiple dimensions, the accuracy of evaluation results is improved, and the improvement suggestions are inquired from the case documents, so that the objectivity of the optimization information is ensured.
The embodiment of the invention screens the target evaluation model from the plurality of evaluation models to evaluate the startup plan by describing information of the startup plan to obtain the startup evaluation result of the startup plan, analyzes the startup plan to obtain the optimization information, provides the startup suggestion of the user, solves the problems that a method for evaluating the startup plan and a platform for providing the startup suggestion do not exist in the prior art, can automatically realize the evaluation of the startup plan and automatically provide the startup suggestion, reduces the labor cost for evaluating the startup plan, ensures the objectivity of the startup plan evaluation, and simultaneously evaluates the startup plan by the evaluation models to improve the accuracy of the startup evaluation result.
Example two
Fig. 2 a-2 b are flowcharts of an -kind startup plan evaluation method in a second embodiment of the present invention, which is embodied based on the above embodiments, and as shown in fig. 2 a-2 b, the method of the present embodiment specifically includes:
s201, collecting entrepreneurship case documents and obtaining keywords matched with the entrepreneurship case documents.
The entrepreneurship case document, the key words, the entrepreneurship case database, the entrepreneurship database, the financing database, the marketing database, the entrepreneurship knowledge document, the law and regulation database, the financial knowledge base, the investor database, the business plan database, the entrepreneurship stage key words, the description information, the target necessary content set, the content key words, the content information to be supplemented, the optimization dimension information, the target entrepreneurship knowledge document, the comparison result, the optimization dimension information and the like in the embodiment of the invention can all refer to the description of the embodiment.
S202, classifying and storing the entrepreneurship case documents according to the keywords matched with the entrepreneurship case documents to form an entrepreneurship case database, and establishing an index according to the matching relation between the keywords and the entrepreneurship case documents, wherein the entrepreneurship case database comprises at least entrepreneurship databases, financing databases and marketing databases.
Optionally, the classifying the entrepreneurship case documents according to the keywords matched with the entrepreneurship case documents includes: inquiring the key words of the entrepreneurship stage from the key words matched with each entrepreneurship case document; classifying the entrepreneurship case documents according to the entrepreneurship stage keywords matched with the entrepreneurship case documents to form entrepreneurship case documents of different entrepreneurship stages; before querying the target evaluation model matched with the description information, the method further comprises the following steps: inquiring entrepreneurship result keywords in the keywords matched with each entrepreneurship case document; taking each entrepreneurship case document and the matched entrepreneurship result keywords as training samples; in each entrepreneurship stage, taking a training sample formed by each corresponding entrepreneurship case as a training sample corresponding to the entrepreneurship stage; and respectively training a machine learning model according to the training sample corresponding to each entrepreneurship stage to obtain an evaluation model corresponding to each entrepreneurship stage.
S203, collecting the startup knowledge documents and acquiring keywords matched with the startup knowledge documents.
And S204, classifying and storing the entrepreneurship knowledge documents according to the keywords matched with the entrepreneurship knowledge documents to form an entrepreneurship knowledge database system, and establishing an index according to the matching relation between the keywords and the entrepreneurship knowledge documents, wherein the entrepreneurship knowledge database system comprises at least of legal and legal rules database, financial knowledge database, investor database and business plan database.
It should be noted that the startup knowledge document and the startup case document may be subjected to data processing in a streaming computing manner, and are respectively written into different message queues according to the types of the matched keywords, and wait for different nodes in the server cluster to read and store, so that the startup knowledge document and the startup case document are classified and stored in different nodes in the server cluster in a distributed storage manner.
The data processing includes text analysis and classification (e.g., clustering algorithm) processing of the documents.
S205, receiving the startup plan uploaded by the user, acquiring the startup stage keywords in the startup plan, and determining the description information of the startup plan.
And S206, inquiring a target evaluation model matched with the description information, and inputting the startup plan into the target evaluation model to obtain a startup evaluation result of the startup plan.
And S207, inquiring a matched target necessary content set according to the startup stage key words of the startup plan.
S208, performing content analysis on the startup plan, and determining at least content keywords of the startup plan.
S209, determining the content information to be supplemented of the startup plan according to the target necessary content set and the at least content keywords.
S210, extracting type keywords from the startup plan, and inquiring at least target startup case documents matched in a preconfigured startup case database system according to the type keywords matched with the startup plan.
In addition, at least target startup case documents matched with the query in the startup case database system can be queried in the startup case database system according to the content of the startup plan by adopting a full-text-based matching algorithm or other similarity algorithms and the like, and at least target startup case documents matched with the query in the same or similar to the startup plan are queried in the startup case database system.
S211, comparing the at least target startup case documents with the startup plan respectively, and determining a comparison result of the startup plan.
Optionally, the comparing of the at least target startup case documents with the startup plan to determine the comparison result of the startup plan includes dividing the at least target startup cases into a successful startup case set and a failed startup case set according to the startup result keywords matched with the at least target startup case documents, comparing the target startup case documents in the successful startup case set with the startup plan according to at least preset startup evaluation dimensions to obtain different data of the startup plan and the successful startup case documents in different startup evaluation dimensions, comparing the target startup case documents in the failed startup case set with the startup plan according to at least startup evaluation dimensions to obtain the same data of the startup plan and the failed startup case documents in different startup evaluation dimensions, counting the different data of the startup plan and the successful startup case documents in different startup evaluation dimensions, and comparing the same data of the startup plan and the failed startup case documents in different startup evaluation dimensions, and counting the same data of the startup plan and the startup plan as the startup plan.
S212, determining the optimized dimension information of the startup plan according to the comparison result between the startup plan and each target startup case document.
And S213, inquiring at least target startup knowledge documents matched in a preset startup knowledge database according to the optimized dimension information.
S214, using the content information to be supplemented, the optimization dimension information and at least target startup knowledge documents as the optimization information of the startup plan, and providing the optimization information to the user.
The embodiment of the invention collects a plurality of startup case documents and startup knowledge documents in advance, stores the collected documents in a classified manner to form a database system, selects a matched target evaluation model for evaluation after receiving the startup plan uploaded by a user to obtain a startup evaluation result, analyzes the contents of the startup plan, determines the contents to be supplemented, determines the optimized dimension information and the target startup knowledge document according to the matched target startup case document, provides the optimized dimension information and the target startup knowledge document as the optimized information for the user, and provides the optimized dimension information and the target startup knowledge document as the improved suggestion of the startup plan, thereby ensuring the objectivity of the evaluation and the improved suggestion of the startup plan, reducing the labor cost of the evaluation of the startup plan, and improving the efficiency of the startup evaluation.
EXAMPLE III
Fig. 3 is a schematic diagram of startup plan evaluation devices in the third embodiment of the present invention, and the third embodiment is a corresponding device for implementing the startup plan evaluation method provided in the third embodiment of the present invention, and the device can be implemented by software and/or hardware, and can be integrated with a computer device and the like.
Accordingly, the apparatus of the present embodiment may include:
the startup plan receiving module 310 is configured to receive a startup plan uploaded by a user and obtain description information of the startup plan;
the startup evaluation module 320 is used for inquiring a target evaluation model matched with the description information, inputting the startup plan into the target evaluation model and obtaining a startup evaluation result of the startup plan;
and the optimization information determining module 330 is configured to analyze the startup plan, determine optimization information of the startup plan, and provide the optimization information to the user.
The embodiment of the invention screens the target evaluation model from the plurality of evaluation models to evaluate the startup plan by describing information of the startup plan to obtain the startup evaluation result of the startup plan, analyzes the startup plan to obtain the optimization information, provides the startup suggestion of the user, solves the problems that a method for evaluating the startup plan and a platform for providing the startup suggestion do not exist in the prior art, can automatically realize the evaluation of the startup plan and automatically provide the startup suggestion, reduces the labor cost for evaluating the startup plan, ensures the objectivity of the startup plan evaluation, and simultaneously evaluates the startup plan by the evaluation models to improve the accuracy of the startup evaluation result.
, the startup plan evaluation device further comprises a startup case classification storage module used for collecting startup case documents and obtaining keywords matched with the startup case documents before receiving the startup plan uploaded by the user, a startup case database formed by classifying and storing the startup case documents according to the keywords matched with the startup case documents and establishing an index according to the matching relationship between the keywords and the startup case documents, wherein the startup case database comprises at least startup database, financing database and marketing database.
, the startup case classification storage module comprises a document classification unit used for inquiring startup stage keywords from the keywords matched with each startup case document, classifying each startup case document according to the startup stage keywords matched with each startup case document to form startup case documents of different startup stages, the startup plan evaluation device further comprises an evaluation model training module used for inquiring startup result keywords from the keywords matched with each corresponding startup case in each startup stage before inquiring a target evaluation model matched with the description information, taking the corresponding startup case document and the matched startup result keywords as training samples of the startup stage in each startup stage, and respectively training a machine learning model according to the training samples of each startup stage to obtain the evaluation model corresponding to each startup stage.
, the startup plan evaluating device further comprises a startup knowledge collecting module used for collecting startup knowledge documents and obtaining keywords matched with the startup knowledge documents before receiving the startup plan uploaded by the user, classifying and storing the startup knowledge documents according to the keywords matched with the startup knowledge documents to form a startup knowledge database system, and establishing an index according to the matching relationship between the keywords and the startup knowledge documents, wherein the startup knowledge database system comprises at least of a law and regulation database, a financial knowledge base, an investor database and a business plan database.
, the startup plan receiving module 310 includes a startup stage keyword obtaining unit, configured to obtain a startup stage keyword in the startup plan, and determine description information of the startup plan.
, the optimization information determination module 330 includes an optimization dimension information determination unit configured to query a matched target necessary content set according to the startup stage keywords of the startup plan, perform content analysis on the startup plan, determine at least content keywords of the startup plan, determine to-be-supplemented content information of the startup plan according to the target necessary content set and the at least content keywords, extract type keywords from the startup plan, query at least matched target case documents in a pre-configured startup case database system according to the type keywords matched with the startup plan, compare the at least target startup case documents with the startup plan respectively to determine a comparison result of the startup plan, determine to-be-optimized dimension information of the startup plan according to the comparison result of the startup plan and each target startup case document, query at least matched target startup case documents in a pre-configured startup knowledge database according to the optimization dimension information, and use the to-be-supplemented knowledge information of the startup plan as at least knowledge information of the startup plan.
, the optimization dimension information determination unit includes an entrepreneurship plan comparison subunit, which is used for dividing the at least target entrepreneurship cases into a successful entrepreneurship case set and a failed entrepreneurship case set according to the entrepreneurship result keywords matched with the at least target entrepreneurship case documents, respectively comparing the target entrepreneur case documents in the successful entrepreneurship case set with the entrepreneurship plan according to at least entrepreneurship evaluation dimensions to obtain different data of the entrepreneurship plan and each successful entrepreneurship case document in different entrepreneurship evaluation dimensions, respectively comparing the target entrepreneurship case documents in the failed entrepreneurship case set with the entrepreneurship plan according to at least entrepreneurship evaluation dimensions to obtain the same data of the entrepreneurship plan and each failed entrepreneurship case document in different entrepreneurship evaluation dimensions, and counting different data of the entrepreneurship plan and the same case data of the entrepreneursepreneurihip plan as the entrepreneurship plan result of the entrepreneurship plan and the case comparison result as the entrepreneursepr.
The startup plan evaluation device can execute the startup plan evaluation method provided by the embodiment of the invention, and has the corresponding functional modules and beneficial effects of the executed startup plan evaluation method.
Example four
FIG. 4 is a schematic diagram of computer devices provided in the fourth embodiment of the present invention, FIG. 4 is a block diagram of an exemplary computer device 12 suitable for implementing the embodiments of the present invention, and the computer device 12 shown in FIG. 4 is only examples, which should not bring any limitations to the functions and the scope of the application of the embodiments of the present invention.
As shown in FIG. 4, computer device 12 is embodied in a general purpose computing device, the components of computer device 12 may include, but are not limited to, or more processors or processing units 16, a system memory 28, a bus 18 that couples the various system components including the system memory 28 and the processing unit 16, and computer device 12 may be a device that is attached to the bus.
Program/utility 40 having sets (at least ) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, or more application programs, other program modules, and program data, each or some combination of these examples possibly including implementation of a network environment.
The processing unit 16 executes various functional applications and data processing, such as startup plan evaluation methods provided by any of the embodiments of the present invention, by executing programs stored in the system memory 28.
EXAMPLE five
Fifth embodiment of the present invention provides computer-readable storage media, where the computer-readable storage media store thereon a computer program, and the computer program, when executed by a processor, implements the startup plan evaluation method provided in all embodiments of the present invention:
that is, the program when executed by the processor implements: receiving a startup plan uploaded by a user, and acquiring description information of the startup plan; inquiring a target evaluation model matched with the description information, and inputting the startup plan into the target evaluation model to obtain a startup evaluation result of the startup plan; and analyzing the startup plan, determining the optimization information of the startup plan, and providing the optimization information for the user.
A more specific example (a non-exhaustive list) of the computer readable storage medium includes an electrical connection having or more wires, a portable computer diskette, a hard disk, a RAM, a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable CD-ROM, an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave .
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, Radio Frequency (RF), etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or a combination thereof, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1, kinds of startup plan evaluation method, characterized by comprising:
receiving a startup plan uploaded by a user, and acquiring description information of the startup plan;
inquiring a target evaluation model matched with the description information, and inputting the startup plan into the target evaluation model to obtain a startup evaluation result of the startup plan;
and analyzing the startup plan, determining the optimization information of the startup plan, and providing the optimization information for the user.
2. The method of claim 1, further comprising, prior to receiving the startup plan uploaded by the user:
collecting entrepreneurship case documents and acquiring keywords matched with the entrepreneurship case documents;
classifying and storing the entrepreneurship case documents according to the keywords matched with the entrepreneurship case documents to form an entrepreneurship case database, and establishing an index according to the matching relation between the keywords and the entrepreneurship case documents, wherein the entrepreneurship case database comprises at least entrepreneurship databases, financing databases and marketing databases.
3. The method of claim 2, wherein the classifying each startup case document according to the keywords that each startup case document matches comprises:
inquiring the key words of the entrepreneurship stage from the key words matched with each entrepreneurship case document;
classifying the entrepreneurship case documents according to the entrepreneurship stage keywords matched with the entrepreneurship case documents to form entrepreneurship case documents of different entrepreneurship stages;
before querying the target evaluation model matched with the description information, the method further comprises the following steps:
inquiring entrepreneurship result keywords in the keywords matched with each entrepreneurship case document;
taking each entrepreneurship case document and the matched entrepreneurship result keywords as training samples;
in each entrepreneurship stage, taking a training sample formed by each corresponding entrepreneurship case as a training sample corresponding to the entrepreneurship stage;
and respectively training a machine learning model according to the training sample corresponding to each entrepreneurship stage to obtain an evaluation model corresponding to each entrepreneurship stage.
4. The method of claim 1, further comprising, prior to receiving the startup plan uploaded by the user:
collecting entrepreneurship knowledge documents, and acquiring keywords matched with the entrepreneurship knowledge documents;
and classifying and storing the entrepreneurship knowledge documents according to the keywords matched with the entrepreneurship knowledge documents to form an entrepreneurship knowledge database system, and establishing an index according to the matching relation between the keywords and the entrepreneurship knowledge documents, wherein the entrepreneurship knowledge database system comprises at least items, namely a law and regulation database, a financial knowledge database, an investor database and a business plan database.
5. The method of claim 1, wherein said obtaining description information of said startup plan comprises:
and acquiring the startup stage key words in the startup plan, and determining the description information of the startup plan.
6. The method of claim 5, wherein analyzing the startup plan to determine optimization information for the startup plan comprises:
inquiring a matched target necessary content set according to the entrepreneurship stage key words of the entrepreneurship plan;
performing content analysis on the startup plan to determine at least content keywords of the startup plan;
determining content information to be supplemented of the startup plan according to the target necessary content set and the at least content keywords;
extracting type keywords from the startup plan, and inquiring at least matched target startup case documents in a preconfigured startup case database system according to the type keywords matched with the startup plan;
comparing the at least target startup case documents with the startup plan respectively to determine a comparison result of the startup plan;
determining optimized dimension information of the startup plan according to the comparison result between the startup plan and each target startup case document;
inquiring at least matched target startup knowledge documents from a pre-configured startup knowledge database according to the optimized dimension information;
and taking the content information to be supplemented, the optimization dimension information and at least target startup knowledge documents as the optimization information of the startup plan.
7. The method of claim 6 wherein said determining a comparison of said startup projects based on said at least target startup case documents being compared to said startup projects respectively comprises:
dividing the at least target entrepreneurship cases into a successful entrepreneurship case set and a failed entrepreneurship case set according to the entrepreneurship result keywords matched with the at least target entrepreneurship case documents;
respectively comparing target startup case documents in the successful startup case set with the startup plan according to at least preset startup evaluation dimensions to obtain different data of the startup plan and each successful startup case document under different startup evaluation dimensions;
comparing the target startup case documents in the failure startup case set with the startup plan respectively according to the at least startup evaluation dimensions to obtain the same data of the startup plan and each failure startup case document under different startup evaluation dimensions;
under different entrepreneurship evaluation dimensions, counting different data of the entrepreneurship plan and each successful entrepreneurship case document and the same data of the entrepreneurship plan and each failed entrepreneurship case document;
and taking the statistical result as a comparison result of the startup plan.
8, th kind of startup plan evaluation device, characterized by comprising:
the entrepreneurship plan receiving module is used for receiving an entrepreneurship plan uploaded by a user and acquiring description information of the entrepreneurship plan;
the entrepreneurship evaluation module is used for inquiring a target evaluation model matched with the description information, inputting the entrepreneurship plan into the target evaluation model and obtaining an entrepreneurship evaluation result of the entrepreneurship plan;
and the optimization information determining module is used for analyzing the startup plan, determining the optimization information of the startup plan and providing the optimization information for the user.
A computer device of the kind 9, , comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the program, implements the startup plan evaluation method of any of claims 1-7, wherein is the computer program.
10, a computer-readable storage medium, having stored thereon a computer program, wherein the program, when executed by a processor, implements the startup plan evaluation method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910980350.1A CN110737749B (en) | 2019-10-11 | 2019-10-11 | Entrepreneurship plan evaluation method, entrepreneurship plan evaluation device, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910980350.1A CN110737749B (en) | 2019-10-11 | 2019-10-11 | Entrepreneurship plan evaluation method, entrepreneurship plan evaluation device, computer equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110737749A true CN110737749A (en) | 2020-01-31 |
| CN110737749B CN110737749B (en) | 2022-09-27 |
Family
ID=69269021
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910980350.1A Active CN110737749B (en) | 2019-10-11 | 2019-10-11 | Entrepreneurship plan evaluation method, entrepreneurship plan evaluation device, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110737749B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113033178A (en) * | 2021-03-04 | 2021-06-25 | 海创汇科技创业发展有限公司 | Text evaluation method and device for business plan and computer |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107066599A (en) * | 2017-04-20 | 2017-08-18 | 北京文因互联科技有限公司 | A kind of similar enterprise of the listed company searching classification method and system of knowledge based storehouse reasoning |
| CN107315738A (en) * | 2017-07-05 | 2017-11-03 | 山东大学 | A kind of innovation degree appraisal procedure of text message |
| CN107622375A (en) * | 2017-08-01 | 2018-01-23 | 平安科技（深圳）有限公司 | Document automatic creation method, document automatic generator and readable storage medium storing program for executing |
| CN107688902A (en) * | 2017-05-27 | 2018-02-13 | 中科钢研节能科技有限公司 | A kind of High-tech Pioneering pattern analysis evaluation method |
| CN109816157A (en) * | 2019-01-07 | 2019-05-28 | 平安科技（深圳）有限公司 | Project plan optimization method, device, computer equipment and storage medium |
| CN109918626A (en) * | 2017-12-13 | 2019-06-21 | 厦门头家信息科技有限公司 | A kind of foundation investment and financing service system |
-
2019
- 2019-10-11 CN CN201910980350.1A patent/CN110737749B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107066599A (en) * | 2017-04-20 | 2017-08-18 | 北京文因互联科技有限公司 | A kind of similar enterprise of the listed company searching classification method and system of knowledge based storehouse reasoning |
| CN107688902A (en) * | 2017-05-27 | 2018-02-13 | 中科钢研节能科技有限公司 | A kind of High-tech Pioneering pattern analysis evaluation method |
| CN107315738A (en) * | 2017-07-05 | 2017-11-03 | 山东大学 | A kind of innovation degree appraisal procedure of text message |
| CN107622375A (en) * | 2017-08-01 | 2018-01-23 | 平安科技（深圳）有限公司 | Document automatic creation method, document automatic generator and readable storage medium storing program for executing |
| CN109918626A (en) * | 2017-12-13 | 2019-06-21 | 厦门头家信息科技有限公司 | A kind of foundation investment and financing service system |
| CN109816157A (en) * | 2019-01-07 | 2019-05-28 | 平安科技（深圳）有限公司 | Project plan optimization method, device, computer equipment and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113033178A (en) * | 2021-03-04 | 2021-06-25 | 海创汇科技创业发展有限公司 | Text evaluation method and device for business plan and computer |
| CN113033178B (en) * | 2021-03-04 | 2023-09-12 | 海创汇科技创业发展有限公司 | Text evaluation method, device and computer for business planning |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110737749B (en) | 2022-09-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10929348B2 (en) | Method and system for large scale data curation | |
| WO2019214245A1 (en) | Information pushing method and apparatus, and terminal device and storage medium | |
| Ur-Rahman et al. | Textual data mining for industrial knowledge management and text classification: A business oriented approach | |
| WO2017097231A1 (en) | Topic processing method and device | |
| WO2018040068A1 (en) | Knowledge graph-based semantic analysis system and method | |
| US10049148B1 (en) | Enhanced text clustering based on topic clusters | |
| CN113342976B (en) | Method, device, storage medium and equipment for automatically acquiring and processing data | |
| US20180336272A1 (en) | Generation of natural language processing events using machine intelligence | |
| Feng et al. | Practical duplicate bug reports detection in a large web-based development community | |
| US12020271B2 (en) | Identifying competitors of companies | |
| JP2020129232A (en) | Machine learning device, program, and machine learning method | |
| Eykens et al. | Fine-grained classification of social science journal articles using textual data: A comparison of supervised machine learning approaches | |
| Jaiswal et al. | Data Mining Techniques and Knowledge Discovery Database | |
| CN102902705A (en) | Locating ambiguities in data | |
| CN110597796B (en) | Big data real-time modeling method and system based on full life cycle | |
| CN110737749B (en) | Entrepreneurship plan evaluation method, entrepreneurship plan evaluation device, computer equipment and storage medium | |
| US20210117448A1 (en) | Iterative sampling based dataset clustering | |
| Cao et al. | Occupational profiling driven by online job advertisements: Taking the data analysis and processing engineering technicians as an example | |
| CN111104422A (en) | Training method, device, equipment and storage medium of data recommendation model | |
| US20220156285A1 (en) | Data Tagging And Synchronisation System | |
| CN113505117A (en) | Data quality evaluation method, device, equipment and medium based on data indexes | |
| Kumbhar et al. | Web mining: A Synergic approach resorting to classifications and clustering | |
| JP6496078B2 (en) | Analysis support device, analysis support method, and analysis support program | |
| Pinto et al. | Intelligent and fuzzy systems applied to language & knowledge engineering | |
| Schnell | Record-linkage from a technical point of view |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 300308 402, building 7, Zhongxing Industrial base, No.2, East 7th Road, Tianjin pilot free trade zone (Airport Economic Zone), Binhai New Area, Tianjin Applicant after: Softcom smart Information Technology Co.,Ltd. Address before: 300308 402, building 7, Zhongxing Industrial base, No.2, East 7th Road, Tianjin pilot free trade zone (Airport Economic Zone), Binhai New Area, Tianjin Applicant before: ISOFTSTONE INFORMATION TECHNOLOGY Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |