CN113961636A

CN113961636A - Object relation query method and device, computer equipment and storage medium

Info

Publication number: CN113961636A
Application number: CN202111393646.7A
Authority: CN
Inventors: 王亮; 王金虎
Original assignee: Qichacha Technology Co ltd
Current assignee: Qichacha Technology Co ltd
Priority date: 2021-11-23
Filing date: 2021-11-23
Publication date: 2022-01-21

Abstract

The disclosure relates to an object relationship query method, an object relationship query apparatus, a computer device, a storage medium and a computer program product. The method comprises the following steps: acquiring object information data, wherein the object information data comprises an object name and first data, and the first data comprises at least one of object address data and object telephone data; processing the first data according to a preset standardization method to obtain standardized data meeting a preset standard, and generating a standardized identifier according to the standardized data; associating the object name according to the standardized identification to obtain object association data; and acquiring object associated data corresponding to the data to be inquired based on the object associated data. The method can achieve the beneficial effect of obtaining the incidence relation between different objects. When the object is an enterprise, the beneficial effect of rapidly acquiring the incidence relation between the enterprises according to the enterprise address data and/or the enterprise telephone data can be achieved.

Description

Object relation query method and device, computer equipment and storage medium

Technical Field

The application relates to the technical field of big data calculation, in particular to an enterprise query method and device based on addresses and telephones, computer equipment and a computer storage medium.

Background

With the development of the field of big data computing, technologies for querying by using big data appear, including technologies for acquiring relationships between objects (such as enterprises) by using big data computing.

Some existing data query service parties may allow querying relationships between enterprises through personnel relationships or equity relationships, but this method has a limited effect on querying relationships between enterprises. When the relationship between enterprises cannot be found through the personnel relationship or the stock right relationship, the query requirement of the user cannot be met.

Disclosure of Invention

In view of the foregoing, it is desirable to provide an object relationship query method, apparatus, computer device, computer readable storage medium and computer program product for solving the above technical problems.

In a first aspect, the present disclosure provides an object relationship query method. The method comprises the following steps:

acquiring object information data, wherein the object information data comprises an object name and first data, and the first data comprises at least one of object address data and object telephone data;

processing the first data according to a preset standardization method to obtain standardization data meeting a preset standard, wherein the preset standardization method comprises a standardization method corresponding to the first data;

generating a standardized identification according to the standardized data, wherein the standardized identification comprises a unique identification of the object address and/or a unique identification of the object telephone;

associating the object name according to the standardized identification to obtain object association data;

and acquiring object associated data corresponding to the data to be inquired based on the object associated data.

In one embodiment, when the first data comprises subject telephone data, the normalization method comprises a telephone normalization method comprising at least one of:

deleting special characters in the object telephone data;

deleting the extension number in the object telephone data;

and verifying whether the number in the object telephone data meets the specification.

In one embodiment, when the first data includes object address data, the normalization method includes an address normalization method including at least one of:

deleting address data which does not contain Chinese in the object address data;

marking province data, city data and district data in the object address data;

supplementing missing province data, city data and district data in the object address data;

partitioning the object address data by address levels, the address levels including at least one of: province, city, district, town, street, road, number, cell, ridge, layer, unit, house number, others;

formatting the similar meaning words in the object address data;

converting the Chinese number in the object address data into an Arabic number;

and deleting the special characters in the object address data.

In one embodiment, the address standardization method comprises processing by using a user-defined Hive function.

In one embodiment, the object information data is acquired and processed by a Hive technique and a Hadoop technique.

In one embodiment, the object information data further includes an object state, where the object state corresponds to the first data, the first data whose object state is a normal state is processed by using the preset standardization method, and the first data whose object state is not a normal state is not processed.

In one embodiment, the obtaining, based on the object association data, object association data corresponding to data to be queried includes: and searching the object associated data corresponding to the data to be inquired from the object associated data by using an elastic search server.

In a second aspect, the present disclosure further provides an object relationship query apparatus. The device comprises:

the data acquisition module is used for acquiring object information data, wherein the object information data comprises an object name and first data, and the first data comprises at least one of object address data and object telephone data;

the data standardization module is used for processing the first data according to a preset standardization method to obtain standardized data meeting a preset standard, and the preset standardization method comprises a standardization method corresponding to the first data;

the data identification module is used for generating a standardized identification according to the standardized data, wherein the standardized identification comprises a unique identification of an object address and/or a unique identification of an object telephone;

the data association module is used for associating the object name according to the standardized identifier to obtain object association data;

and the data query module is used for acquiring object associated data corresponding to the data to be queried based on the object associated data.

In one embodiment, the data normalization module is configured to perform at least one of the following steps when the first data includes subject telephone data:

deleting special characters in the object telephone data;

deleting the extension number in the object telephone data;

In one embodiment, the data normalization module is configured to, when the first data includes object address data, perform at least one of the following steps:

marking province data, city data and district data in the object address data;

formatting the similar meaning words in the object address data;

converting the Chinese number in the object address data into an Arabic number;

and deleting the special characters in the object address data.

In one embodiment, the data normalization module is configured to process the object address data using a user-defined Hive function.

In one embodiment, at least one of the data acquisition module, the data standardization module, the data identification module, the data association module and the data query module uses a Hive technology and a Hadoop technology when performing corresponding processing.

In one embodiment, the object information data further includes an object state, where the object state corresponds to the first data, and the data normalization module is configured to process the first data in which the object state is a normal state by using the preset normalization method, and not process the first data in which the object state is not a normal state.

In one embodiment, the data query module is configured to search the object associated data corresponding to the data to be queried from the object associated data by using an elastic search server.

In a third aspect, the present disclosure also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:

In a fourth aspect, the present disclosure also provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

In a fifth aspect, the present disclosure also provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:

The embodiment scheme provided by the disclosure can obtain object information data, wherein the object information data comprises an object name and first data, the first data comprises at least one of object address data and object telephone data, the object address data and/or the object telephone data are processed according to a preset standardization method to obtain standardized data meeting a preset standard, and a unique identification mark of the standardized data is generated, because the same address only corresponds to one identification mark and the same address can correspond to a plurality of object names, the object names corresponding to the same address can be quickly associated through the identification mark, similarly, one telephone also only corresponds to one identification mark and the same telephone can correspond to a plurality of object names, so that the object names corresponding to the same telephone can be quickly associated through the identification mark, thereby obtaining object associated data, inquiring or retrieving the data to be inquired based on the object associated data, and obtaining the object associated data corresponding to the data to be inquired. When the object is an enterprise, the beneficial effect of acquiring the incidence relation between the enterprises according to the address data and/or the telephone data can be achieved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.

FIG. 1 is a diagram of an application environment for an object relational query method in one embodiment;

FIG. 2 is a flowchart illustrating an object relationship query method according to an embodiment;

FIG. 3 is a flowchart illustrating an object relationship query method according to another embodiment;

FIG. 4 is a flowchart illustrating an object relationship query method according to another embodiment;

FIG. 5 is a block diagram showing the structure of an object relationship query apparatus according to an embodiment;

FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the disclosure and are not intended to limit the disclosure.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

The object relationship query method provided by the embodiment of the disclosure can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104, or may be located on the cloud or other network server. The server 104 acquires object information data including an object name and first data including at least one of object address data and object telephone data. The server 104 processes the first data according to a preset standardization method, so as to obtain standardized data meeting a preset standard, where the preset standardization method includes a standardization method corresponding to the first data. The server 104 generates a standardized identification from the standardized data, the standardized identification comprising a unique identification of the address of the object and/or a unique identification of the phone of the object. The server 104 associates the object name according to the standardized identifier to obtain object association data. The terminal 102 sends data to be queried to the server 104, the server 104 queries object associated data corresponding to the data to be queried from the object associated data, and sends a query result to the terminal 102. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart car-mounted devices, and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers. The terminal 102 and the server 104 may belong to the same device.

In one embodiment, as shown in fig. 2, an object relationship query method is provided, which is described by taking the application environment in fig. 1 as an example, and includes the following steps:

s202, object information data is obtained, wherein the object information data comprises an object name and first data, and the first data comprises at least one of object address data and object telephone data.

Wherein the object may be a business.

Specifically, a large amount of object information data is acquired, and an object information database can be established. The object information data includes an object name and first data including at least one of object address data and object telephone data. Accordingly, an object address database and an object telephone database can be established. When the object is an enterprise, enterprise information data can be obtained from an industrial and commercial official network (such as a national enterprise credit information public system), and an enterprise information base can be constructed by using the enterprise information data.

And S204, processing the first data according to a preset standardization method to obtain standardized data meeting a preset standard, wherein the preset standardization method comprises a standardization method corresponding to the first data.

Specifically, when the first data includes object address data, the preset normalization method includes a preset address normalization method. When the first data includes subject telephone data, the preset standardization method includes a preset telephone standardization method. When the first data includes object address data and object telephone data, the preset standardization method includes a preset address standardization method and a preset telephone standardization method. And processing the first data according to the preset standardization method, and processing the first data into standardized data meeting preset standards. The preset address standardization method may refer to a method of enabling address data to become canonical address data (e.g., having a uniform format, a uniform form). The preset phone standardization method may refer to a method of enabling phone data to become standardized phone data (e.g., having a uniform format, a uniform form).

S206, generating a standardized identification according to the standardized data, wherein the standardized identification comprises the unique identification of the object address and/or the unique identification of the object telephone.

Wherein the standardized identity is an easily retrievable mark.

Specifically, the standardized identifier may be a number, a letter, or a code, or some combination of the number, the letter, and the code, or other easily retrievable marks. For example, each number may represent an address, with the numbers corresponding to the addresses one to one. For example, 4 different addresses may be represented by "a 1, a2, A3, a 4", respectively, and 5 different phones may be represented by "# a, # B, # C, # D, # E", respectively. The same type of identification can also be used for the unique identification of the subject address and the unique identification of the subject phone. And generating a standardized identifier corresponding to each piece of standardized data according to the standardized data. It should be noted that the same standardized data corresponds to the same standardized id.

And S208, associating the object name according to the standardized identification to obtain object association data.

Specifically, the standardized identifier and the object name have a corresponding relationship. One standardized identifier may correspond to one object name or a plurality of object names. And when one standardized identification corresponds to a plurality of object names, associating the object names corresponding to the same standardized identification to obtain object association data. The object association data may further include the same address data and/or the same telephone data associated with the plurality of object names. An object association database may be established based on the object association data. The object association database may include an object address association database and an object telephone association database.

S210, acquiring object associated data corresponding to the data to be inquired based on the object associated data.

The data to be queried may refer to data that needs to be queried.

Specifically, the data to be queried may be an object name, an object address, or an object phone. For example, a business name, a business address, or a business phone. And inquiring and acquiring the object associated data corresponding to the data to be inquired from the object associated data. For example, when the object is an enterprise and the data to be queried is an enterprise name _001 (where name _001 represents an enterprise name), name _001 may be searched from the object-related data to obtain another enterprise having the same address and/or the same phone as the enterprise name _ 001.

In the object relationship query method, the object information data is acquired, address data and telephone data contained in the object information data are standardized to obtain standardized data meeting a preset standard, then a unique identification mark corresponding to each piece of standardized data is set, and object names corresponding to the same identification marks are associated to obtain object associated data. Based on the object associated data, the data to be queried is queried or retrieved, and the object associated data corresponding to the data to be queried can be obtained, namely, the beneficial effect of obtaining the association relation between different objects can be achieved. When the object is an enterprise, the beneficial effect of rapidly acquiring the association relation between the enterprises according to the address data and/or the telephone data can be achieved.

In one embodiment, as shown in fig. 3, the first data comprises subject phone data, the normalization method comprises a phone normalization method, the phone normalization method comprises at least one of the following steps:

deleting special characters in the object telephone data;

deleting the extension number in the object telephone data;

Specifically, in processing the subject telephone data, it can be verified whether or not a telephone number in the subject telephone data conforms to a specification. When the telephone number is found not to contain the special character and not to contain the extension number, the object telephone data can be not processed. When a special character, such as "#", "&", "-", or the like, is found to be included in the phone number, the special character included in the phone number is deleted. And when the extension number is found to be contained in the telephone number, deleting the extension number in the telephone number. It should be noted that the three steps are not necessarily performed in the order shown in fig. 3, and other execution orders may be available.

In this embodiment, the object telephone data is processed by using a telephone standardization method such as deleting a special character, deleting an extension number, and the like, so that the purpose of processing the object telephone data into standardized data meeting a preset standard can be achieved, and query of the object telephone data is facilitated, and thus correlation of an object relationship and query of an object relationship are facilitated.

In one embodiment, as shown in fig. 4, when the first data includes object address data, the normalization method includes an address normalization method including at least one of the following steps:

marking province data, city data and district data in the object address data;

formatting the similar meaning words in the object address data;

converting the Chinese number in the object address data into an Arabic number;

and deleting the special characters in the object address data.

Where near word formatting may refer to replacing words with the same words that have similar meanings.

Specifically, when the target address data is processed, the address data not containing the chinese language in the target address data may be deleted first, or the foreign language address data may be translated into the chinese language address data, so as to achieve the same purpose. And converting the Chinese number in the object address data into an Arabic number. And deleting the special characters in the object address data. The similar meaning words in the object address data are formatted, and the words with the same meaning in the object address data are replaced by uniform words, for example, words such as 'number building', 'dong', 'seat', 'house', and the like can be replaced by 'dong' uniformly. The province data, city data, and district data missing in the object address data are supplemented, for example, a certain address data is "industrial park moon bay subway station", and the address may be supplemented as "industrial park moon bay subway station" in suzhou city, Jiangsu province. Partitioning the object address data by address levels, the address levels including at least one of: province, city, district, town, street, road, number, cell, ridge, layer, unit, house number, others, where "others" may refer to a more specific address level than house number, e.g., the address level of "station 215" in the address "room number 306, station number 215" may be "others". The separation may be performed using regular expressions. During the partitioning process, some outliers can be deleted, for example, when a certain address is idr _002 new village (here, idr _002 represents an address name), the "new village" can be deleted. Here, the address level is an address level in accordance with the national administrative level plan, for example, the address level of the prefecture city such as "shanghai city" is provincial level, and the address level of the "quiet area" in shanghai is city level. Marking province data, city data and region data in the object address data, for example, marking an address of a city sand head region of defense in an autonomous region of Ningxia Hui nationality as: "province: ningxia Hui nationality autonomous region city: the city district of the middle defence: a sand head ". It should be noted that, when the address normalization method is used to process the target address data, only one of the address normalization steps may be used, or multiple steps may be used, specifically, the target address data is processed into data meeting a preset address standard, where meeting the preset address standard may refer to processing the address data until the address data does not need to be processed in the address normalization step, that is, the target address data meets the processing effect of each address normalization step. It should be noted that the three steps are not necessarily performed in the order shown in fig. 4, and other execution orders may be available.

In this embodiment, by processing the object address data by using an address standardization method including a plurality of steps, the object address data can be processed into standardized data meeting a preset standard, which is beneficial to query the object address data, thereby facilitating the relationship association of the object and querying the object relationship.

In one embodiment, the address normalization method comprises processing using a user-defined Hive function.

The Hive Function Defined by the User may be a User-Defined Function (abbreviated as UDF in english) in the Hive technology.

In particular, some of the functions required for the address normalization method are implemented by means of UDF functions. Hive can be a data warehouse tool based on Hadoop, is used for data extraction, transformation and loading, and can store, inquire and analyze large-scale data stored in Hadoop. The hive data warehouse tool can map the Structured data file into a database table, provide an SQL Query function (SQL is an english abbreviation of Structured Query Language, and is called Structured Query Language overall), and convert SQL statements into MapReduce tasks to be executed (MapReduce is a name of a programming model). And Hadoop can be a distributed system infrastructure. By utilizing Hadoop, a user can develop a distributed program under the condition of not knowing distributed bottom-layer details, and the power of a cluster is fully utilized to carry out high-speed operation and storage. Hive contains some functions, but the functions cannot meet all functional requirements of users, and the UDF function is used for meeting special functional requirements of the address standardization method in the using process.

In this embodiment, a Hive function, i.e., a UDF function, which is customized by a user, is added to the address standardization method, so that the address standardization method can be better used, and a technical effect of efficiently standardizing address data can be achieved.

Wherein Hive may be a data warehouse tool based on Hadoop. And Hadoop can be a distributed system infrastructure.

Specifically, the object information data is inquired through a Hive technology, and the object information data is stored through a Hadoop technology. In the processing of the object information data, the Hive technology is used for extracting, converting and loading the data, and the Hadoop technology is used for carrying out high-speed operation and storage on the data.

In this embodiment, by using the Hive technology and the Hadoop technology when acquiring the object information data and processing the object information data, a technical effect of acquiring and processing the object information data in a fast, efficient and large-batch manner can be achieved, thereby facilitating achievement of a technical effect of querying the object relationship in a fast and efficient manner.

In an embodiment, the object information data further includes an object state, where the object state corresponds to the first data, the first data whose object state is a normal state is processed by using the preset standardization method, and the first data whose object state is not a normal state is not processed.

The normal state may refer to a state of the object being normal, so that the object relationship has a query value.

Specifically, when the object is a business, the normal state may include a persistent state, an on-business state, and the like. And screening the acquired object information data according to the object state. And processing corresponding first data by using the preset standardization method for the object information data with the object state as the normal state. And for the object information data with the object state not being the normal state, no processing is carried out. In addition, the acquired target information data can be subjected to data cleaning, namely, the data is reexamined and checked, so that repeated information is deleted, information errors are corrected, and data consistency is provided.

In this embodiment, the object information data is screened according to the object state, and only the object information data with the data state being the normal state is processed, so that the technical effects of reducing data processing amount and quickly realizing object relationship query can be achieved.

In an embodiment, the obtaining, based on the object association data, object association data corresponding to data to be queried includes:

and searching the object associated data corresponding to the data to be inquired from the object associated data by using an elastic search server.

Specifically, the object association data is pushed to an elastic search server. The user can input the data to be queried into the elastic search server, and the elastic search server searches the object associated data corresponding to the data to be queried from the object associated data. The flexible search server may refer to a search server based on a full-text search engine architecture, for example, a flexible search Engine (ES) based on Lucene (Lucene is a name of a full-text search engine architecture). ES provides a distributed multi-user capable full-text search engine.

In the embodiment, the elastic search server is used for inquiring the object associated data, so that the technical effect of quickly inquiring the object relation is achieved.

It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the present disclosure further provides an object relationship query apparatus for implementing the above-mentioned object relationship query method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more embodiments of the object relationship query device provided below may refer to the limitations on the object relationship query method in the above, and details are not described here.

In one embodiment, as shown in fig. 5, there is provided an object relationship query apparatus, including: a data acquisition module 502, a data normalization module 504, a data identification module 506, a data association module 508, and a data query module 510, wherein:

the data obtaining module 502 is configured to obtain object information data, where the object information data includes an object name and first data, and the first data includes at least one of object address data and object telephone data.

A data normalization module 504, configured to process the first data according to a preset normalization method to obtain normalized data meeting a preset standard, where the preset normalization method includes a normalization method corresponding to the first data.

A data identification module 506, configured to generate a standardized identification from the standardized data, where the standardized identification includes a unique identification of the address of the object and/or a unique identification of the phone of the object.

And a data association module 508, configured to associate the object name according to the standardized identifier to obtain object association data.

A data query module 510, configured to obtain object associated data corresponding to the data to be queried based on the object associated data.

In one embodiment, the data normalization module 504 is configured to perform at least one of the following steps when the first data comprises subject telephony data:

deleting special characters in the object telephone data;

deleting the extension number in the object telephone data;

In one embodiment, the data normalization module 504 is configured to perform at least one of the following steps when the first data includes object address data:

marking province data, city data and district data in the object address data;

formatting the similar meaning words in the object address data;

converting the Chinese number in the object address data into an Arabic number;

and deleting the special characters in the object address data.

In one embodiment, the data normalization module 504 is configured to process the object address data using a user-defined hive function.

In one embodiment, at least one of the data acquisition module 502, the data normalization module 504, the data identification module 506, the data association module 508, and the data query module 510 uses hive technology and hadoop technology in performing corresponding processing.

In an embodiment, the object information data further includes an object state, where the object state corresponds to the first data, and the data normalization module 504 is configured to process the first data whose object state is a normal state by using the preset normalization method, and not process the first data whose object state is not a normal state.

In one embodiment, the data query module 510 is configured to search the object related data corresponding to the data to be queried from the object related data by using an elastic search server.

The modules in the object relationship query device can be wholly or partially implemented by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing object information data and data obtained by processing. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an object relational query method.

Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

In an embodiment, a computer program product is provided, comprising a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present disclosure are information and data that are authorized by the user or sufficiently authorized by each party.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, databases, or other media used in the embodiments provided by the present disclosure may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases involved in embodiments provided by the present disclosure may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided in this disclosure may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic, quantum computing based data processing logic, etc., without limitation.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present disclosure, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present disclosure. It should be noted that, for those skilled in the art, various changes and modifications can be made without departing from the concept of the present disclosure, and these changes and modifications are all within the scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the appended claims.

Claims

1. An object relationship query method, the method comprising:

2. The method of claim 1, wherein when the first data comprises subject telephony data, the normalization method comprises a telephony normalization method comprising at least one of:

deleting special characters in the object telephone data;

deleting the extension number in the object telephone data;

3. The method of claim 1, wherein when the first data comprises object address data, the normalization method comprises an address normalization method, the address normalization method comprising at least one of:

marking province data, city data and district data in the object address data;

formatting the similar meaning words in the object address data;

converting the Chinese number in the object address data into an Arabic number;

and deleting the special characters in the object address data.

4. The method of claim 3, wherein the address normalization method comprises processing using a user-defined Hive function.

5. The method of claim 1, wherein the object information data is obtained and processed by a Hive technique and a Hadoop technique.

6. The method according to claim 1, wherein the object information data further includes an object status, the object status has a corresponding relationship with the first data, the first data whose object status is a normal status is processed by using the preset standardization method, and the first data whose object status is not a normal status is not processed.

7. The method according to claim 1, wherein the obtaining object associated data corresponding to data to be queried based on the object associated data comprises:

8. An object relationship query apparatus, the apparatus comprising:

9. The apparatus of claim 8, wherein the data normalization module is configured to perform at least one of the following steps when the first data comprises subject telephony data:

deleting special characters in the object telephone data;

deleting the extension number in the object telephone data;

10. The apparatus of claim 8, wherein the data normalization module is configured to perform at least one of the following steps when the first data comprises object address data:

marking province data, city data and district data in the object address data;

formatting the similar meaning words in the object address data;

converting the Chinese number in the object address data into an Arabic number;

and deleting the special characters in the object address data.

11. The apparatus of claim 10, wherein the data normalization module is configured to process the object address data using a user-defined Hive function.

12. The apparatus of claim 8, wherein at least one of the data acquisition module, the data normalization module, the data identification module, the data association module, and the data query module uses Hive and Hadoop techniques when performing corresponding processing.

13. The apparatus according to claim 8, wherein the object information data further includes an object status, the object status has a corresponding relationship with the first data, and the data normalization module is configured to process the first data whose object status is a normal status by using the preset normalization method, and not process the first data whose object status is not a normal status.

14. The apparatus of claim 8, wherein the data query module is configured to search the object related data corresponding to the data to be queried from the object related data using a flexible search server.

15. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

16. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.

17. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 7 when executed by a processor.