WO2018157391A1 - Big-data enterprise evaluation method and system - Google Patents
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- WO2018157391A1 WO2018157391A1 PCT/CN2017/075625 CN2017075625W WO2018157391A1 WO 2018157391 A1 WO2018157391 A1 WO 2018157391A1 CN 2017075625 W CN2017075625 W CN 2017075625W WO 2018157391 A1 WO2018157391 A1 WO 2018157391A1
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- the present invention relates to the field of data processing, and in particular, to a method and system for evaluating big data enterprises.
- the McKinsey Global Institute defines big data as a collection of data that is large enough to capture, store, manage, and analyze the capabilities of traditional database software tools. It has a large data scale and fast data flow. Four different data types and low value density.
- Big Data The strategic significance of big data technology is not to master huge data information, but to professionalize these meaningful data.
- big data the key to profitability in this industry is to increase the “processing capability” of the data and “add value” of the data through “processing”.
- Big data must not be processed by a single computer, and a distributed architecture must be used. It features distributed data mining for massive data. But it must rely on cloud computing for distributed processing, distributed databases and cloud storage, and virtualization technologies. With the advent of the cloud era, big data (Big Data) has also attracted more and more attention.
- Big Data (Big) Data) is often used to describe a large amount of unstructured data and semi-structured data created by a company that spends too much time and money when downloaded to a relational database for analysis. Big data analytics is often associated with cloud computing because real-time large dataset analysis requires a framework like MapReduce to distribute work to dozens, hundreds, or even thousands of computers.
- the application provides a method for big data enterprise evaluation. It solves the shortcomings that the prior art technical solutions cannot evaluate the enterprise.
- a method for evaluating a big data enterprise comprising the following steps: a method for evaluating a big data enterprise, the method comprising the following steps:
- the server obtains the enterprise identifier to be evaluated
- the server queries, according to the enterprise identifier, information related to the enterprise identifier from the big data;
- the server evaluates the enterprise credit based on the related information.
- the method further includes:
- the server queries the related information for the default amount and the default amount of the contract of the enterprise information. If the default data and the default amount exceed the set threshold, the enterprise evaluates the dish as dishonest.
- the method further includes:
- the server queries from the related information whether there is the number and amount of unexecuted cases of the court of the enterprise, and if so, the enterprise is evaluated as dishonest.
- a system for big data enterprise evaluation comprising:
- An obtaining unit configured to obtain an enterprise identifier to be evaluated
- the processing unit is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
- system further includes:
- the processing unit is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, and if the default data and the default amount exceed a set threshold, the enterprise is evaluated as dishonest.
- system further includes:
- a processing unit configured to query, from the related information, whether there is a number of the unexecuted cases of the enterprise and the amount of the case, and if yes, the enterprise is evaluated as dishonest.
- a third aspect provides a server, including: a processor, a wireless transceiver, a memory, and a bus, wherein the processor, the wireless transceiver, and the memory are connected by a bus, and the wireless transceiver is configured to acquire an enterprise identifier to be evaluated. ;
- the processor is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
- the processor is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, and if the default data and the default amount exceed a set threshold, the enterprise evaluation is performed. For dishonesty.
- the processor is configured to query, from the related information, whether there is a number of court unexecuted cases and an amount of the enterprise, and if yes, the enterprise is evaluated as dishonest.
- the technical solution provided by the invention retrieves big data related to the enterprise by searching for big data, and then evaluates the integrity of the enterprise according to the breach information or the court execution information in the big data, so it has the advantages of realizing the evaluation of the enterprise. .
- FIG. 1 is a flowchart of a method for evaluating big data enterprises according to a first preferred embodiment of the present invention
- FIG. 2 is a structural diagram of a system for evaluating big data enterprises according to a second preferred embodiment of the present invention.
- FIG. 3 is a hardware structural diagram of a server according to a second preferred embodiment of the present invention.
- FIG. 1 is a method for evaluating a big data enterprise according to a first preferred embodiment of the present invention. The method is as shown in FIG. 1 and includes the following steps:
- Step S101 The server acquires an enterprise identifier to be evaluated.
- the company logo may specifically be a company name or a corporate unified credit code.
- Step S102 The server queries, according to the enterprise identifier, information related to the enterprise identifier from the big data.
- Step S103 The server evaluates the enterprise credit according to the related information.
- the technical solution provided by the invention retrieves big data related to the enterprise by searching for big data, and then evaluates the integrity of the enterprise according to the breach information or the court execution information in the big data, so it has the advantages of realizing the evaluation of the enterprise. .
- the server queries, from the related information, the default amount and the default amount of the contract of the enterprise information, and if the default data and the default amount exceed a set threshold, the enterprise is evaluated as dishonest.
- the server queries, from the related information, whether there is a number of the unexecuted cases of the enterprise and the amount of the case, and if yes, the enterprise is evaluated as dishonest.
- FIG. 2 is a system for evaluating big data enterprises according to a second preferred embodiment of the present invention.
- the system is as shown in FIG. 2, and includes:
- the obtaining unit 201 is configured to obtain an enterprise identifier to be evaluated
- the processing unit 202 is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
- the technical solution provided by the invention retrieves big data related to the enterprise by searching for big data, and then evaluates the integrity of the enterprise according to the breach information or the court execution information in the big data, so it has the advantages of realizing the evaluation of the enterprise. .
- the processing unit 202 is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, and if the default data and the default amount exceed a set threshold, the enterprise is evaluated as not honest.
- the processing unit 202 is configured to query, from the related information, whether the number of the unexecuted cases of the enterprise and the amount of the enterprise are obtained, and if yes, the enterprise is evaluated as dishonest.
- FIG. 3 is a server 30, including: a processor 301, a wireless transceiver 302, a memory 303, and a bus 304.
- the wireless transceiver 302 is configured to send and receive data with and from an external device.
- the number of processors 301 can be one or more.
- processor 301, memory 302, and transceiver 303 may be connected by bus 304 or other means.
- Server 30 can be used to perform the steps of FIG. For the meaning and examples of the terms involved in the embodiment, reference may be made to the corresponding embodiment of FIG. 1. I will not repeat them here.
- the wireless transceiver 302 is configured to obtain an enterprise identifier to be evaluated.
- the program code is stored in the memory 303.
- the processor 901 is configured to call the program code stored in the memory 903 for performing the following operations:
- the processor 301 is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
- the processor 301 herein may be a processing component or a general term of multiple processing components.
- the processing element can be a central processor (Central) Processing Unit, CPU), or a specific integrated circuit (Application Specific Integrated) Circuit, ASIC), or one or more integrated circuits configured to implement embodiments of the present application, such as one or more microprocessors (digital singnal Processor, DSP), or one or more Field Programmable Gate Arrays (FPGAs).
- CPU central processor
- ASIC Application Specific Integrated Circuit
- DSP digital singnal Processor
- FPGAs Field Programmable Gate Arrays
- the memory 303 may be a storage device or a collective name of a plurality of storage elements, and is used to store executable program code or parameters, data, and the like required for the application running device to operate. And the memory 303 may include random access memory (RAM), and may also include non-volatile memory (non-volatile memory) Memory), such as disk storage, flash (Flash), etc.
- RAM random access memory
- non-volatile memory non-volatile memory
- flash flash
- Bus 304 can be an industry standard architecture (Industry Standard Architecture, ISA) bus, Peripheral Component (PCI) bus or extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc.
- the bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is shown in Figure 3, but it does not mean that there is only one bus or one type of bus.
- the terminal may further include input and output means connected to the bus 304 for connection to other parts such as the processor 301 via the bus.
- the input/output device can provide an input interface for the operator, so that the operator can select the control item through the input interface, and can also be other interfaces through which other devices can be externally connected.
- the program may be stored in a computer readable storage medium, and the storage medium may include: Flash drive, read-only memory (English: Read-Only Memory, referred to as: ROM), random accessor (English: Random Access Memory, referred to as: RAM), disk or CD.
- ROM Read-Only Memory
- RAM Random Access Memory
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Abstract
A big-data enterprise evaluation method, comprising the following steps: a server obtains an enterprise identification to be evaluated (101); the server queries information related to the enterprise identification from big data according to the enterprise identification (102); and the server evaluates the enterprise credit according to the related information (103). The method can achieve enterprise evaluation.
Description
本发明涉及数据处理领域,尤其涉及一种大数据企业评价的方法及系统。The present invention relates to the field of data processing, and in particular, to a method and system for evaluating big data enterprises.
麦肯锡全球研究所对大数据给出的定义是:一种规模大到在获取、存储、管理、分析方面大大超出了传统数据库软件工具能力范围的数据集合,具有海量的数据规模、快速的数据流转、多样的数据类型和价值密度低四大特征。The McKinsey Global Institute defines big data as a collection of data that is large enough to capture, store, manage, and analyze the capabilities of traditional database software tools. It has a large data scale and fast data flow. Four different data types and low value density.
大数据技术的战略意义不在于掌握庞大的数据信息,而在于对这些含有意义的数据进行专业化处理。换而言之,如果把大数据比作一种产业,那么这种产业实现盈利的关键,在于提高对数据的“加工能力”,通过“加工”实现数据的“增值”。从技术上看,大数据与云计算的关系就像一枚硬币的正反面一样密不可分。大数据必然无法用单台的计算机进行处理,必须采用分布式架构。它的特色在于对海量数据进行分布式数据挖掘。但它必须依托云计算的分布式处理、分布式数据库和云存储、虚拟化技术。随着云时代的来临,大数据(Big
data)也吸引了越来越多的关注。《著云台》的分析师团队认为,大数据(Big
data)通常用来形容一个公司创造的大量非结构化数据和半结构化数据,这些数据在下载到关系型数据库用于分析时会花费过多时间和金钱。大数据分析常和云计算联系到一起,因为实时的大型数据集分析需要像MapReduce一样的框架来向数十、数百或甚至数千的电脑分配工作。
The strategic significance of big data technology is not to master huge data information, but to professionalize these meaningful data. In other words, if big data is likened to an industry, the key to profitability in this industry is to increase the “processing capability” of the data and “add value” of the data through “processing”. From a technical point of view, the relationship between big data and cloud computing is as inseparable as the front and back of a coin. Big data must not be processed by a single computer, and a distributed architecture must be used. It features distributed data mining for massive data. But it must rely on cloud computing for distributed processing, distributed databases and cloud storage, and virtualization technologies. With the advent of the cloud era, big data (Big
Data) has also attracted more and more attention. The team of analysts at Yuntai believes that Big Data (Big)
Data) is often used to describe a large amount of unstructured data and semi-structured data created by a company that spends too much time and money when downloaded to a relational database for analysis. Big data analytics is often associated with cloud computing because real-time large dataset analysis requires a framework like MapReduce to distribute work to dozens, hundreds, or even thousands of computers.
现有的企业评价无法依据大数据对企业进行评价。Existing corporate evaluations cannot evaluate companies based on big data.
本申请提供一种大数据企业评价的方法。其解决现有技术的技术方案无法对企业进行评价的缺点。The application provides a method for big data enterprise evaluation. It solves the shortcomings that the prior art technical solutions cannot evaluate the enterprise.
一方面,提供一种大数据企业评价的方法,所述方法包括如下步骤:大数据企业评价的方法,所述方法包括如下步骤:In one aspect, a method for evaluating a big data enterprise is provided, the method comprising the following steps: a method for evaluating a big data enterprise, the method comprising the following steps:
服务器获取待评价的企业标识;The server obtains the enterprise identifier to be evaluated;
服务器依据所述企业标识从大数据中查询与所述企业标识相关的信息;The server queries, according to the enterprise identifier, information related to the enterprise identifier from the big data;
服务器依据所述相关的信息对所述企业信用进行评价。The server evaluates the enterprise credit based on the related information.
可选的,所述方法还包括:Optionally, the method further includes:
服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。The server queries the related information for the default amount and the default amount of the contract of the enterprise information. If the default data and the default amount exceed the set threshold, the enterprise evaluates the dish as dishonest.
可选的,所述方法还包括:Optionally, the method further includes:
服务器从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。The server queries from the related information whether there is the number and amount of unexecuted cases of the court of the enterprise, and if so, the enterprise is evaluated as dishonest.
第二方面,提供一种大数据企业评价的系统,所述系统包括:In a second aspect, a system for big data enterprise evaluation is provided, the system comprising:
获取单元,用于获取待评价的企业标识;An obtaining unit, configured to obtain an enterprise identifier to be evaluated;
处理单元,用于依据所述企业标识从大数据中查询与所述企业标识相关的信息,依据所述相关的信息对所述企业信用进行评价。The processing unit is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
可选的,所述系统还包括:Optionally, the system further includes:
处理单元,用于服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。The processing unit is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, and if the default data and the default amount exceed a set threshold, the enterprise is evaluated as dishonest.
可选的,所述系统还包括:Optionally, the system further includes:
处理单元,用于从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。And a processing unit, configured to query, from the related information, whether there is a number of the unexecuted cases of the enterprise and the amount of the case, and if yes, the enterprise is evaluated as dishonest.
第三方面,提供一种服务器,包括:处理器、无线收发器、存储器和总线,所述处理器、无线收发器、存储器通过总线连接,所述无线收发器,用于获取待评价的企业标识;A third aspect provides a server, including: a processor, a wireless transceiver, a memory, and a bus, wherein the processor, the wireless transceiver, and the memory are connected by a bus, and the wireless transceiver is configured to acquire an enterprise identifier to be evaluated. ;
所述处理器,用于依据所述企业标识从大数据中查询与所述企业标识相关的信息,依据所述相关的信息对所述企业信用进行评价。The processor is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
可选的,所述处理器,用于服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。Optionally, the processor is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, and if the default data and the default amount exceed a set threshold, the enterprise evaluation is performed. For dishonesty.
可选的,所述处理器,用于从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。Optionally, the processor is configured to query, from the related information, whether there is a number of court unexecuted cases and an amount of the enterprise, and if yes, the enterprise is evaluated as dishonest.
本发明提供的技术方案对大数据进行检索获取与企业相关的大数据,然后依据该大数据中的违约信息或法院执行信息对该企业的诚信度进行评价,所以其具有实现对企业评价的优点。The technical solution provided by the invention retrieves big data related to the enterprise by searching for big data, and then evaluates the integrity of the enterprise according to the breach information or the court execution information in the big data, so it has the advantages of realizing the evaluation of the enterprise. .
为了更清楚地说明本发明实施例的技术方案,下面将对实施例描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without paying any creative work.
图1为本发明第一较佳实施方式提供的一种大数据企业评价的方法的流程图;1 is a flowchart of a method for evaluating big data enterprises according to a first preferred embodiment of the present invention;
图2为本发明第二较佳实施方式提供的一种大数据企业评价的系统的结构图。2 is a structural diagram of a system for evaluating big data enterprises according to a second preferred embodiment of the present invention.
图3为本发明第二较佳实施方式提供的一种服务器的硬件结构图。FIG. 3 is a hardware structural diagram of a server according to a second preferred embodiment of the present invention.
下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are a part of the embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.
请参考图1,图1是本发明第一较佳实施方式提出的一种大数据企业评价的方法,该方法如图1所示,包括如下步骤:Please refer to FIG. 1. FIG. 1 is a method for evaluating a big data enterprise according to a first preferred embodiment of the present invention. The method is as shown in FIG. 1 and includes the following steps:
步骤S101、服务器获取待评价的企业标识。Step S101: The server acquires an enterprise identifier to be evaluated.
该企业标识具体可以为,企业名称或企业统一信用代码。The company logo may specifically be a company name or a corporate unified credit code.
步骤S102、服务器依据所述企业标识从大数据中查询与所述企业标识相关的信息。Step S102: The server queries, according to the enterprise identifier, information related to the enterprise identifier from the big data.
步骤S103、服务器依据所述相关的信息对所述企业信用进行评价。Step S103: The server evaluates the enterprise credit according to the related information.
本发明提供的技术方案对大数据进行检索获取与企业相关的大数据,然后依据该大数据中的违约信息或法院执行信息对该企业的诚信度进行评价,所以其具有实现对企业评价的优点。The technical solution provided by the invention retrieves big data related to the enterprise by searching for big data, and then evaluates the integrity of the enterprise according to the breach information or the court execution information in the big data, so it has the advantages of realizing the evaluation of the enterprise. .
可选的,服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。Optionally, the server queries, from the related information, the default amount and the default amount of the contract of the enterprise information, and if the default data and the default amount exceed a set threshold, the enterprise is evaluated as dishonest.
可选的,服务器从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。Optionally, the server queries, from the related information, whether there is a number of the unexecuted cases of the enterprise and the amount of the case, and if yes, the enterprise is evaluated as dishonest.
请参考图2,图2是本发明第二较佳实施方式提出的一种大数据企业评价的系统,该系统如图2所示,包括:Please refer to FIG. 2. FIG. 2 is a system for evaluating big data enterprises according to a second preferred embodiment of the present invention. The system is as shown in FIG. 2, and includes:
获取单元201,用于获取待评价的企业标识;The obtaining unit 201 is configured to obtain an enterprise identifier to be evaluated;
处理单元202,用于依据所述企业标识从大数据中查询与所述企业标识相关的信息,依据所述相关的信息对所述企业信用进行评价。The processing unit 202 is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
本发明提供的技术方案对大数据进行检索获取与企业相关的大数据,然后依据该大数据中的违约信息或法院执行信息对该企业的诚信度进行评价,所以其具有实现对企业评价的优点。The technical solution provided by the invention retrieves big data related to the enterprise by searching for big data, and then evaluates the integrity of the enterprise according to the breach information or the court execution information in the big data, so it has the advantages of realizing the evaluation of the enterprise. .
可选的,处理单元202,用于服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。Optionally, the processing unit 202 is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, and if the default data and the default amount exceed a set threshold, the enterprise is evaluated as not honest.
可选的,处理单元202,用于从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。Optionally, the processing unit 202 is configured to query, from the related information, whether the number of the unexecuted cases of the enterprise and the amount of the enterprise are obtained, and if yes, the enterprise is evaluated as dishonest.
参阅图3,图3为一种服务器30,包括:处理器301、无线收发器302、存储器303和总线304,无线收发器302用于与外部设备之间收发数据。处理器301的数量可以是一个或多个。本申请的一些实施例中,处理器301、存储器302和收发器303可通过总线304或其他方式连接。服务器30可以用于执行图1的步骤。关于本实施例涉及的术语的含义以及举例,可以参考图1对应的实施例。此处不再赘述。Referring to FIG. 3, FIG. 3 is a server 30, including: a processor 301, a wireless transceiver 302, a memory 303, and a bus 304. The wireless transceiver 302 is configured to send and receive data with and from an external device. The number of processors 301 can be one or more. In some embodiments of the present application, processor 301, memory 302, and transceiver 303 may be connected by bus 304 or other means. Server 30 can be used to perform the steps of FIG. For the meaning and examples of the terms involved in the embodiment, reference may be made to the corresponding embodiment of FIG. 1. I will not repeat them here.
无线收发器302,用于获取待评价的企业标识。The wireless transceiver 302 is configured to obtain an enterprise identifier to be evaluated.
其中,存储器303中存储程序代码。处理器901用于调用存储器903中存储的程序代码,用于执行以下操作:The program code is stored in the memory 303. The processor 901 is configured to call the program code stored in the memory 903 for performing the following operations:
处理器301,用于依据所述企业标识从大数据中查询与所述企业标识相关的信息,依据所述相关的信息对所述企业信用进行评价。The processor 301 is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
需要说明的是,这里的处理器301可以是一个处理元件,也可以是多个处理元件的统称。例如,该处理元件可以是中央处理器(Central
Processing Unit,CPU),也可以是特定集成电路(Application Specific Integrated
Circuit,ASIC),或者是被配置成实施本申请实施例的一个或多个集成电路,例如:一个或多个微处理器(digital singnal
processor,DSP),或,一个或者多个现场可编程门阵列(Field Programmable Gate Array, FPGA)。It should be noted that the processor 301 herein may be a processing component or a general term of multiple processing components. For example, the processing element can be a central processor (Central)
Processing Unit, CPU), or a specific integrated circuit (Application Specific Integrated)
Circuit, ASIC), or one or more integrated circuits configured to implement embodiments of the present application, such as one or more microprocessors (digital singnal
Processor, DSP), or one or more Field Programmable Gate Arrays (FPGAs).
存储器303可以是一个存储装置,也可以是多个存储元件的统称,且用于存储可执行程序代码或应用程序运行装置运行所需要参数、数据等。且存储器303可以包括随机存储器(RAM),也可以包括非易失性存储器(non-volatile
memory),例如磁盘存储器,闪存(Flash)等。The memory 303 may be a storage device or a collective name of a plurality of storage elements, and is used to store executable program code or parameters, data, and the like required for the application running device to operate. And the memory 303 may include random access memory (RAM), and may also include non-volatile memory (non-volatile memory)
Memory), such as disk storage, flash (Flash), etc.
总线304可以是工业标准体系结构(Industry Standard
Architecture,ISA)总线、外部设备互连(Peripheral Component,PCI)总线或扩展工业标准体系结构(Extended
Industry Standard
Architecture,EISA)总线等。该总线可以分为地址总线、数据总线、控制总线等。为便于表示,图3中仅用一条粗线表示,但并不表示仅有一根总线或一种类型的总线。Bus 304 can be an industry standard architecture (Industry Standard
Architecture, ISA) bus, Peripheral Component (PCI) bus or extended industry standard architecture (Extended
Industry Standard
Architecture, EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is shown in Figure 3, but it does not mean that there is only one bus or one type of bus.
该终端还可以包括输入输出装置,连接于总线304,以通过总线与处理器301等其它部分连接。该输入输出装置可以为操作人员提供一输入界面,以便操作人员通过该输入界面选择布控项,还可以是其它接口,可通过该接口外接其它设备。The terminal may further include input and output means connected to the bus 304 for connection to other parts such as the processor 301 via the bus. The input/output device can provide an input interface for the operator, so that the operator can select the control item through the input interface, and can also be other interfaces through which other devices can be externally connected.
需要说明的是,对于前述的各个方法实施例,为了简单描述,故将其都表述为一系列的动作组合,但是本领域技术人员应该知悉,本发明并不受所描述的动作顺序的限制,因为依据本发明,某一些步骤可以采用其他顺序或者同时进行。其次,本领域技术人员也应该知悉,说明书中所描述的实施例均属于优选实施例,所涉及的动作和模块并不一定是本发明所必须的。It should be noted that, for the foregoing various method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should understand that the present invention is not limited by the described action sequence. Because certain steps may be performed in other sequences or concurrently in accordance with the present invention. In addition, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.
在上述实施例中,对各个实施例的描述都各有侧重,某个实施例中没有详细描述的部分,可以参见其他实施例的相关描述。In the above embodiments, the descriptions of the various embodiments are different, and the parts that are not described in detail in a certain embodiment can be referred to the related descriptions of other embodiments.
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成,该程序可以存储于一计算机可读存储介质中,存储介质可以包括:闪存盘、只读存储器(英文:Read-Only
Memory ,简称:ROM)、随机存取器(英文:Random Access Memory,简称:RAM)、磁盘或光盘等。A person skilled in the art may understand that all or part of the various steps of the foregoing embodiments may be performed by a program to instruct related hardware. The program may be stored in a computer readable storage medium, and the storage medium may include: Flash drive, read-only memory (English: Read-Only
Memory, referred to as: ROM), random accessor (English: Random Access Memory, referred to as: RAM), disk or CD.
以上对本发明实施例所提供的内容下载方法及相关设备、系统进行了详细介绍,本文中应用了具体个例对本发明的原理及实施方式进行了阐述,以上实施例的说明只是用于帮助理解本发明的方法及其核心思想;同时,对于本领域的一般技术人员,依据本发明的思想,在具体实施方式及应用范围上均会有改变之处,综上所述,本说明书内容不应理解为对本发明的限制。The content downloading method and the related device and system provided by the embodiments of the present invention are described in detail above. The principles and implementation manners of the present invention are described in the specific examples. The description of the above embodiments is only used to help understand the present invention. The method of the invention and its core idea; at the same time, for the person of ordinary skill in the art, according to the idea of the present invention, there are some changes in the specific embodiment and the scope of application. In summary, the content of the specification should not be understood. To limit the invention.
Claims (9)
- 一种大数据企业评价的方法,其特征在于,所述方法包括如下步骤: A method for evaluating a big data enterprise, characterized in that the method comprises the following steps:服务器获取待评价的企业标识;The server obtains the enterprise identifier to be evaluated;服务器依据所述企业标识从大数据中查询与所述企业标识相关的信息;The server queries, according to the enterprise identifier, information related to the enterprise identifier from the big data;服务器依据所述相关的信息对所述企业信用进行评价。The server evaluates the enterprise credit based on the related information.
- 根据权利要求1所述的方法,其特征在于,所述方法还包括:The method of claim 1 further comprising:服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。The server queries the related information for the default amount and the default amount of the contract of the enterprise information. If the default data and the default amount exceed the set threshold, the enterprise evaluates the dish as dishonest.
- 根据权要求2所述的方法,其特征在于,所述方法还包括:The method of claim 2, wherein the method further comprises:服务器从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。The server queries from the related information whether there is the number and amount of unexecuted cases of the court of the enterprise, and if so, the enterprise is evaluated as dishonest.
- 一种大数据企业评价的系统,其特征在于,所述系统包括:A system for evaluating big data enterprises, characterized in that the system comprises:获取单元,用于获取待评价的企业标识;An obtaining unit, configured to obtain an enterprise identifier to be evaluated;处理单元,用于依据所述企业标识从大数据中查询与所述企业标识相关的信息,依据所述相关的信息对所述企业信用进行评价。The processing unit is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
- 根据权利要求4所述的系统,其特征在于,所述系统还包括:The system of claim 4, wherein the system further comprises:处理单元,用于服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。The processing unit is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, and if the default data and the default amount exceed a set threshold, the enterprise is evaluated as dishonest.
- 根据权利要求5所述的系统,其特征在于,所述系统还包括:The system of claim 5, wherein the system further comprises:处理单元,用于从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。And a processing unit, configured to query, from the related information, whether there is a number of the unexecuted cases of the enterprise and the amount of the case, and if yes, the enterprise is evaluated as dishonest.
- 一种服务器,包括:处理器、无线收发器、存储器和总线,所述处理器、无线收发器、存储器通过总线连接,其特征在于,A server includes: a processor, a wireless transceiver, a memory, and a bus, wherein the processor, the wireless transceiver, and the memory are connected by a bus, wherein所述无线收发器,用于获取待评价的企业标识;The wireless transceiver is configured to obtain an enterprise identifier to be evaluated;所述处理器,用于依据所述企业标识从大数据中查询与所述企业标识相关的信息,依据所述相关的信息对所述企业信用进行评价。The processor is configured to query, according to the enterprise identifier, information related to the enterprise identifier from the big data, and evaluate the enterprise credit according to the related information.
- 根据权利要求7所述的服务器,其特征在于,所述处理器,用于服务器从所述相关信息中查询出所述企业信息的合同的违约数量和违约金额,如该违约数据和违约金额超过设定阈值,则将该企业评价为不诚信。The server according to claim 7, wherein the processor is configured to query, by the server, the default amount and the default amount of the contract of the enterprise information from the related information, if the default data and the default amount exceed When the threshold is set, the company is evaluated as dishonest.
- 根据权利要求7所述的服务器,其特征在于,所述处理器,用于从所述相关信息中查询是否具有所述企业的法院未执行案件的数量以及金额,如具有,则将所述企业评价为不诚信。 The server according to claim 7, wherein the processor is configured to query, from the related information, whether there is a number of court unexecuted cases and an amount of money of the enterprise, and if yes, the enterprise Evaluation is dishonest.
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