CN107748792B - Data retrieval method and device and terminal - Google Patents
Data retrieval method and device and terminal Download PDFInfo
- Publication number
- CN107748792B CN107748792B CN201711059897.5A CN201711059897A CN107748792B CN 107748792 B CN107748792 B CN 107748792B CN 201711059897 A CN201711059897 A CN 201711059897A CN 107748792 B CN107748792 B CN 107748792B
- Authority
- CN
- China
- Prior art keywords
- retrieval
- data
- suppliers
- supplier
- classification
- 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.)
- Active
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
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
- G06F16/90348—Query processing by searching ordered data, e.g. alpha-numerically ordered data
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
A data retrieval method comprises receiving retrieval priority constraints input by a demander, wherein the retrieval priority constraints comprise a plurality of retrieval conditions with different priorities; the multiple suppliers are sequenced according to the multiple retrieval conditions and data provided by the multiple suppliers to obtain a retrieval sequence, the data provided by the multiple suppliers have preset dimension classification and preset label value classification, and the retrieval conditions comprise the preset dimension classification and the preset label value classification; receiving an inquiry request sent by a demand party, wherein the inquiry request comprises a main body identifier; and sequentially searching the data provided by the plurality of suppliers according to the searching sequence to obtain the data matched with the main body identification. The technical scheme of the invention improves the data retrieval efficiency.
Description
Technical Field
The present invention relates to the field of data circulation technologies, and in particular, to a data retrieval method, an apparatus, and a terminal.
Background
As data becomes an important production material, data is increasingly circulated across subjects and industries. Data flow techniques are gradually evolving in practice.
The prior art can realize the manual aggregation, splicing and completion of data.
However, the data processing efficiency of the prior art is relatively low. Especially for heterogeneous multi-source data, the prior art cannot automatically regulate the data. The multi-source data is low in regular quality, high in data access cost and inflexible in data retrieval.
Disclosure of Invention
The invention solves the technical problem of how to improve the data retrieval efficiency.
In order to solve the above technical problem, an embodiment of the present invention provides a data retrieval method, where the data retrieval method includes: receiving retrieval priority constraints input by a demand side, wherein the retrieval priority constraints comprise a plurality of retrieval conditions with different priorities; the multiple suppliers are sequenced according to the multiple retrieval conditions and data provided by the multiple suppliers to obtain a retrieval sequence, the data provided by the multiple suppliers have preset dimension classification and preset label value classification, and the retrieval conditions comprise the preset dimension classification and the preset label value classification; receiving an inquiry request sent by a demand party, wherein the inquiry request comprises a main body identifier; and sequentially searching the data provided by the plurality of suppliers according to the searching sequence to obtain the data matched with the main body identification.
Optionally, the sorting the multiple suppliers according to the retrieval priority constraint and data provided by the multiple suppliers includes: receiving a requirement field input by the requiring party; determining the plurality of suppliers that provide the demand field; and sorting the plurality of suppliers according to the matching of the data provided by the plurality of suppliers and the plurality of retrieval conditions and the priority order of the plurality of retrieval conditions.
Optionally, the sorting the suppliers according to the matching degree of the data provided by the suppliers and the retrieval conditions and the priority order of the retrieval conditions includes: matching the data provided by the supplier with the retrieval conditions according to the high-low order of the priorities of the plurality of retrieval conditions to obtain a matching result; and determining the sequence position of the supplier according to the priority of the retrieval condition matched by the supplier in the matching result, wherein the higher the priority of the retrieval condition matched by the supplier is, the higher the sequence position of the supplier is.
Optionally, the sequentially retrieving the data provided by the plurality of suppliers according to the retrieval order includes: and matching the subject identification and the subject identification in the data provided by each supplier according to the retrieval sequence, and outputting the data comprising the subject identification.
Optionally, the data retrieval method further includes: if the data matched with the main body identification is obtained, stopping retrieval; or, if the set stop condition is reached, the search is stopped.
Optionally, the receiving of the retrieval priority constraint input by the demander comprises: and normalizing the source data provided by the plurality of suppliers to obtain normalized data, wherein the normalized data has the preset dimension classification and the preset label value classification.
Optionally, the receiving of the retrieval priority constraint input by the demander comprises: receiving standardized data provided by the plurality of suppliers, wherein the standardized data is provided with the preset dimension classification and the preset label value classification.
Optionally, before receiving the retrieval priority constraint input by the demander, the method further includes: and performing semantic analysis on the standardized data, and classifying preset dimension classifications and preset label value classifications in the standardized data into corresponding fields.
The embodiment of the invention also discloses a data retrieval device, which comprises: the retrieval priority constraint receiving module is suitable for receiving retrieval priority constraints input by a demand party, and the retrieval priority constraints comprise a plurality of retrieval conditions with different priorities; the ordering module is suitable for ordering the multiple suppliers according to the multiple retrieval conditions and data provided by the multiple suppliers to obtain a retrieval sequence, the data provided by the multiple suppliers has a preset dimension classification and a preset label value classification, and the retrieval conditions comprise the preset dimension classification and the preset label value classification; the query request receiving module is suitable for receiving a query request sent by a demand party, and the query request comprises a main body identifier; and the retrieval module is suitable for sequentially retrieving the data provided by the plurality of suppliers according to the retrieval sequence so as to obtain the data matched with the main body identification.
Optionally, the sorting module includes: the requirement field receiving unit is suitable for receiving a requirement field input by the requiring party; a supplier determination unit adapted to determine the plurality of suppliers providing the demand field; the ordering unit is suitable for ordering the suppliers according to the matching of the data provided by the suppliers and the retrieval conditions and the priority order of the retrieval conditions.
Optionally, the sorting unit includes: the matching subunit is suitable for matching the data provided by the supplier with the retrieval conditions according to the high-low order of the priorities of the plurality of retrieval conditions to obtain a matching result; the ordering subunit is adapted to determine the order position of the supplier according to the priority of the search condition matched by the supplier in the matching result, and the higher the priority of the search condition matched by the supplier is, the higher the order position of the supplier is.
Optionally, the retrieval module matches the subject identifier and the subject identifier in the data provided by each supplier according to the retrieval sequence, and outputs the data including the subject identifier.
Optionally, the data retrieval apparatus further includes: the first stopping module is suitable for stopping retrieval when the data matched with the main body identification is obtained; and the second stopping module is suitable for stopping retrieval when the set stopping condition is reached.
Optionally, the data retrieval apparatus further includes: the preprocessing module is suitable for carrying out standardization processing on source data provided by the plurality of suppliers to obtain standardized data, and the standardized data is provided with the preset dimension classification and the preset label value classification.
Optionally, the data retrieval apparatus further includes: a normalized data receiving module adapted to receive normalized data provided by the plurality of suppliers, the normalized data having the preset dimension classification and the preset label value classification.
Optionally, the data retrieval apparatus further includes: and the data access module is suitable for performing semantic analysis on the standardized data and classifying preset dimensionality classification and preset label value classification in the standardized data into corresponding fields.
The embodiment of the invention also discloses a storage medium, wherein computer instructions are stored on the storage medium, and the steps of the data retrieval method are executed when the computer instructions are executed.
The embodiment of the invention also discloses a terminal which comprises a memory and a processor, wherein the memory is stored with a computer instruction capable of running on the processor, and the processor executes the steps of the data retrieval method when running the computer instruction.
Compared with the prior art, the technical scheme of the embodiment of the invention has the following beneficial effects:
the technical scheme of the invention receives retrieval priority constraints input by a demand side, wherein the retrieval priority constraints comprise a plurality of retrieval conditions with different priorities; the multiple suppliers are sequenced according to the multiple retrieval conditions and data provided by the multiple suppliers to obtain a retrieval sequence, the data provided by the multiple suppliers have preset dimension classification and preset label value classification, and the retrieval conditions comprise the preset dimension classification and the preset label value classification; receiving an inquiry request sent by a demand party, wherein the inquiry request comprises a main body identifier; and sequentially searching the data provided by the plurality of suppliers according to the searching sequence to obtain the data matched with the main body identification. In the technical scheme of the invention, because the data and the retrieval conditions provided by a plurality of suppliers have the preset dimension classification and the preset label value classification, the retrieval can be carried out aiming at a plurality of retrieval conditions of a demand side, the condition that the retrieval can be carried out only aiming at a single data source in the prior art is avoided, and the retrieval efficiency is improved; in addition, the suppliers can be sequenced by utilizing the retrieval conditions and retrieved according to the retrieval sequence, so that flexible routing retrieval can be performed according to the retrieval strategy customized by the demander, the data purchasing cost of the demander is reduced, and the data retrieval flexibility is realized; the requirement of the demander for searching the priority can be met, so that the demander can obtain the required data, and the user experience is improved.
Further, the source data provided by the plurality of suppliers may be standardized to obtain standardized data, and the standardized data has the preset dimension classification and the preset label value classification; or, receiving standardized data provided by the plurality of suppliers, wherein the standardized data is provided with the preset dimension classification and the preset label value classification. According to the technical scheme, automatic filtering and cleaning and automatic standardization and normalization can be achieved for heterogeneous multi-source data, so that data provided by a supplier can be unified in the aspects of dimension, label, expression mode and the like, and flexible retrieval of the data is further achieved.
Furthermore, semantic analysis is carried out on the standardized data, and preset dimension classification and preset label value classification in the standardized data are divided into corresponding fields. According to the technical scheme, multi-source data single-inlet access is realized in an automatic-analysis data integration mode, so that the access cost can be reduced, and the access efficiency is improved; the workload of the data circulation organization side can be reduced.
Drawings
FIG. 1 is a flow chart of a data retrieval method according to an embodiment of the present invention;
FIG. 2 is a flowchart of one embodiment of step S102 of FIG. 1;
FIG. 3 is a partial flow diagram of another data retrieval method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a comparison of source data and normalized data according to an embodiment of the present invention;
FIG. 5 is a graph illustrating comparison of source data with normalized data according to another embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a data retrieval apparatus according to an embodiment of the present invention;
FIG. 7 is a block diagram illustrating one embodiment of the order module 602 of FIG. 6;
fig. 8 is a schematic structural diagram of another data retrieval device according to an embodiment of the present invention.
Detailed Description
As described in the background, the data processing efficiency of the prior art is relatively low. Especially for heterogeneous multi-source data, the prior art cannot automatically regulate the data. The multi-source data is low in regular quality, high in data access cost and inflexible in data retrieval.
In the technical scheme of the invention, because the data and the retrieval conditions provided by a plurality of suppliers have the preset dimension classification and the preset label value classification, the retrieval can be carried out aiming at a plurality of retrieval conditions of a demand side, the condition that the retrieval can be carried out only aiming at a single data source in the prior art is avoided, and the retrieval efficiency is improved; in addition, the suppliers can be sequenced by utilizing the retrieval conditions and retrieved according to the retrieval sequence, so that flexible routing retrieval can be performed according to the retrieval strategy customized by the demander, the data purchasing cost of the demander is reduced, and the data retrieval flexibility is realized; the requirement of the demander for searching the priority can be met, so that the demander can obtain the required data, and the user experience is improved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Fig. 1 is a flowchart of a data retrieval method according to an embodiment of the present invention.
The data retrieval method shown in fig. 1 may include the steps of:
step S101: receiving retrieval priority constraints input by a demand side, wherein the retrieval priority constraints comprise a plurality of retrieval conditions with different priorities;
step S102: sorting the plurality of suppliers according to the plurality of retrieval conditions and data provided by the plurality of suppliers to obtain a retrieval order;
the data provided by the plurality of suppliers has a preset dimension classification and a preset label value classification, and the retrieval condition comprises the preset dimension classification and the preset label value classification;
step S103: receiving an inquiry request sent by a demand party, wherein the inquiry request comprises a main body identifier;
step S104: and sequentially searching the data provided by the plurality of suppliers according to the searching sequence to obtain the data matched with the main body identification.
Before retrieving data, the demander can formulate a retrieval priority constraint according to the requirement, namely a plurality of retrieval conditions. The higher the demand for the search condition, the higher the priority of the search condition. The claimant may enter the retrieval constraint priority. In a specific implementation of step S101, the retrieval constraint priority is received.
Specifically, the demander may determine the retrieval priority constraint at multiple levels, such as a rule constraint, a budget constraint, a quality constraint, and a performance constraint. Wherein, the rule constraint can comprise a circulation forbidding object constraint and an authorization mode constraint; budget constraints may include unit price constraints, pricing means constraints, and single ID budget threshold constraints; the quality constraint may comprise a quality floor constraint; the performance constraints may include latency constraints and concurrency constraints. It should be understood by those skilled in the art that the manner of determining the retrieval priority constraint is not limited to the above, and the demander may increase the policy category according to the needs of business development.
For example, the demander may determine that the search condition is a price constraint, may select a price interval, or select a price first; the demander can determine that the retrieval condition is quality constraint and can select quality priority; the demander can determine that the retrieval condition is coverage constraint, and can select full population high coverage priority or designated area high coverage priority; the demander can determine that the search condition specifies a supplier or a supplier range; the demander can determine that the retrieval condition is time constraint, and can select the latest update priority or specify a time range; the demand party can determine the retrieval condition as the pricing mode constraint, and can select hit charging or inquiry charging.
The demander can determine a plurality of retrieval conditions according to the service requirement of the demander and carries out priority sequencing on the retrieval conditions. Further, for the unordered search condition, a preset order may be set, and the search condition is ranked after the selected order, thereby forming a complete search priority constraint.
In one embodiment of the present invention, please refer to table 1. Table 1 shows one retrieval priority constraint for a requestor. The retrieval priority constraint comprises six retrieval conditions, and the six retrieval conditions are unit price constraint, single ID budget threshold constraint, quality constraint, delay constraint, concurrency constraint and pricing mode constraint in sequence according to the priority order. The retrieval priority constraint indicates that the demand of the demander is the highest, and data provided by the supplier with low price is preferentially selected in subsequent retrieval.
TABLE 1
In particular implementations, multiple suppliers may provide data that is required by a demander. In order to retrieve the optimal data required by the demand side, in the specific implementation of step S102, a plurality of suppliers may be ranked. The retrieved order is an order in which a plurality of suppliers are retrieved.
For example, for suppliers A, B and C, the query unit prices for the data they provide are 0.2, 0.5, and 0.1 units/time, in that order. The retrieval condition for which the requester has the highest priority is a unit price constraint. Then the retrieval order resulting from sorting suppliers A, B and C is supplier C, supplier a, and supplier B.
Further, in order to achieve more convenient ordering of suppliers, the data provided by the suppliers has a preset dimension classification and a preset label value classification, and the retrieval condition includes the preset dimension classification and the preset label value classification. That is, data provided by a plurality of suppliers and retrieval conditions can be matched in data format to avoid failure in data retrieval. For example, the retrieval condition includes dimension "unit price", and if the data provided by the supplier includes dimension "unit price", data retrieval can be realized; if the data provided by the supplier comprises the dimension of 'total price', the data provided by the supplier does not match with the retrieval condition in the data format, and the data retrieval cannot be carried out.
After completing the ordering of the suppliers, in a specific implementation of step S103, a query request of the demander is received, and the demander can indicate the subject identification of the demand data in the query request. For example, if the query request includes identity ID0001, it indicates that the data required by the demander is the relevant data of the individual with identity ID 0001.
Further, in step S104, the data provided by the plurality of suppliers may be sequentially retrieved in the retrieval order to obtain data matching the subject identifier. That is, if the data provided by the supplier includes the subject identification, the data is output to the demander.
In the technical scheme of the invention, because the data and the retrieval conditions provided by a plurality of suppliers have the preset dimension classification and the preset label value classification, the retrieval can be carried out aiming at a plurality of retrieval conditions of a demand side, the condition that the retrieval can be carried out only aiming at a single data source in the prior art is avoided, and the retrieval efficiency is improved; in addition, the suppliers can be sequenced by utilizing the retrieval conditions and retrieved according to the retrieval sequence, so that flexible routing retrieval can be performed according to the retrieval strategy customized by the demander, the data purchasing cost of the demander is reduced, and the data retrieval flexibility is realized; the requirement of the demander for searching the priority can be met, so that the demander can obtain the required data, and the user experience is improved.
In a specific application scenario of the present invention, the data retrieval method shown in fig. 1 may be applied to a third party platform other than a supplier and a demander, such as a data transaction platform. And the third-party platform sorts all suppliers providing the data requested by the demanders according to the retrieval priority constraint of the demanders. After the retrieval sequence of the supplier is scheduled, the demander initiates a query request, inputs a query ID and sends an authorization file to the third-party platform, and then the third-party platform automatically requests data from the supplier in sequence according to the established retrieval sequence until a result required by the demander is obtained or a stop condition (such as a single ID budget threshold) specified by a retrieval priority constraint is reached, and the query is stopped.
In a preferred embodiment of the invention, the data provided by the supplier is credit investigation data. The retrieval method can retrieve the credit investigation data matched with the main body identification proposed by the demand side. The demander can check the credit status of the user pointed by the main body identification according to the acquired credit investigation data so as to judge whether to give credit to the user or not, and determine credit limit, credit period, interest rate and the like.
The embodiment of the invention can realize effective single-point access inquiry, and can realize flexible routing retrieval according to rule constraint, budget constraint, quality constraint, performance constraint and the like customized by a data demander by providing uniform format of data by a data supplier.
Referring to fig. 2, step S102 may include the following steps:
step S201: receiving a requirement field input by the requiring party;
step S202: determining the plurality of suppliers that provide the demand field;
step S203: and sorting the plurality of suppliers according to the matching of the data provided by the plurality of suppliers and the plurality of retrieval conditions and the priority order of the plurality of retrieval conditions.
In this embodiment, the demander may notify the third party platform of the data required by the demander through the requirement field. Since the third party platform can know the fields provided by each supplier, the supplier providing the data required by the demander can be determined by comparing the field of the demand with the fields provided by the suppliers.
For example, the requirement field entered by the requester is field B. The supplier providing the field B comprises a supplier I, a supplier II and a supplier III.
Further, step S203 may include the steps of: matching the data provided by the supplier with the retrieval conditions according to the high-low order of the priorities of the plurality of retrieval conditions to obtain a matching result; and determining the sequence position of the supplier according to the priority of the retrieval condition matched by the supplier in the matching result, wherein the higher the priority of the retrieval condition matched by the supplier is, the higher the sequence position of the supplier is.
For example, the highest priority search condition of the demand side is unit price first and the unit price is less than 0.5 yuan/time. For suppliers one, two and three, the query unit price of the data provided by the suppliers is 0.2 yuan/time, 0.5 yuan/time and 0.1 yuan/time in sequence. If the query unit price of the data provided by the second supplier does not match with the search condition, the second supplier can be eliminated, and the search sequence obtained by sorting the first supplier and the third supplier is the third supplier and the first supplier.
Preferably, the method shown in fig. 1 may further comprise the steps of: if the data matched with the main body identification is obtained, stopping retrieval; or, if the set stop condition is reached, the search is stopped.
In this embodiment, if data matching the subject identifier is retrieved from the data provided by the supplier, the data is provided to the demander, and the retrieval is stopped. Alternatively, the requesting party may set a predetermined stop condition in advance, and stop the search process when the set stop condition is reached during the search process. For example, setting the stop condition as a single ID budget threshold value, since a budget is generated every query, when the cumulative budget for a query for a single ID reaches the single ID budget threshold value, the search for that ID is stopped.
In another specific application scenario of the invention, the retrieval priority constraints input by the demander respectively comprise unit price priority, single ID budget threshold and delay threshold according to the priority; the retrieval order is supplier three and supplier one. After receiving a query request of a demand side, carrying out first retrieval on data provided by a third supplier side, and if data matched with the main body identification is obtained, stopping retrieval; if the data matched with the main body identification is not obtained, determining whether the budget after the first retrieval is completed exceeds a single ID budget threshold, and if so, stopping the retrieval; otherwise, determining whether the time delay after the first retrieval is finished exceeds a time delay threshold value, and if so, stopping the retrieval; otherwise, the second retrieval is continued to be performed on the data provided by the first provider, and the first retrieval process is referred to in the subsequent process, which is not described herein again.
In a preferred embodiment of the present invention, a process of preprocessing the data of the supplier may be further included before the data retrieval. Referring to fig. 1 and fig. 3, before step S101, the following steps may be further included:
step S301: and normalizing the source data provided by the plurality of suppliers to obtain normalized data, wherein the normalized data has the preset dimension classification and the preset label value classification.
In this embodiment, the process of standardizing the source data provided by the multiple suppliers may be performed by a third-party platform. Because source data provided by a plurality of suppliers may have different key values and/or tag values, which brings inconvenience to subsequent retrieval, the embodiment of the present invention performs standardization processing on the source data, so that the data provided by a plurality of suppliers has uniform dimensions and tag values.
It should be noted that the preset dimension classification and the preset label value classification may be preset.
Step S302: receiving standardized data provided by the plurality of suppliers, wherein the standardized data is provided with the preset dimension classification and the preset label value classification.
In this embodiment, the process of standardizing the source data provided by the multiple suppliers may be performed at the suppliers, and the suppliers send the standardized data obtained by the preprocessing to the third-party platform. Specifically, the apparatus for normalizing the source data may be deployed at a front-end of the provider.
For example, please refer to fig. 4 and 5 together. As shown in fig. 4, the provider providing field a has provider one and provider two. But the data formats provided by vendor one and vendor two for field a are not uniform. In this embodiment, through step S301 or step S302, the data provided by the first supplier and the second supplier are unified as "001: is "and" 002: NO ".
As shown in fig. 5, the suppliers providing the field B include supplier one, supplier two and supplier three. However, the data formats provided by the field B are not uniform by the supplier one, the supplier two and the supplier three, and different intervals are divided for the values of the data. In this embodiment, through step S301 or step S302, the data provided by the first supplier and the second supplier are unified as "00: data found "," 01: [0, 100] "and" 02: (100, ∞) ".
Step S303 may also be included before step S101: and performing semantic analysis on the standardized data, and classifying preset dimension classifications and preset label value classifications in the standardized data into corresponding fields.
According to the embodiment of the invention, multi-source data single-inlet access is realized in an automatic analysis data integration mode, so that the access cost can be reduced, and the access efficiency is improved; the workload of the data circulation organization side can be reduced.
In this embodiment, the standardized data may be accessed to the third party platform through an Application Programming Interface (API). The third-party platform can realize automatic and uniform interface packaging through an automatic semantic analysis component based on machine learning, so that a data demand party can conveniently carry out data query requests to a plurality of suppliers in a single-inlet interface access mode. It is understood that for purposes of this patent, multiple sub-interfaces may be handled by the requesting party or manually encapsulated. However, these alternatives can greatly reduce the efficiency of data retrieval, increase the access cost of the demander, and greatly increase the workload of the data circulation organizer.
As shown in fig. 6, the data retrieval device 60 may include:
the retrieval priority constraint receiving module 601 is adapted to receive retrieval priority constraints input by a demander, where the retrieval priority constraints include a plurality of retrieval conditions with different priorities;
the sorting module 602 is adapted to sort the multiple suppliers according to the multiple retrieval conditions and data provided by the multiple suppliers, so as to obtain a retrieval order, where the data provided by the multiple suppliers has a preset dimension classification and a preset label value classification, and the retrieval conditions include the preset dimension classification and the preset label value classification;
the query request receiving module 603 is adapted to receive a query request sent by a demander, where the query request includes a subject identifier;
the retrieving module 604 is adapted to sequentially retrieve the data provided by the plurality of suppliers according to the retrieval order to obtain the data matching the subject identification.
In the embodiment of the invention, because the data and the retrieval conditions provided by the plurality of suppliers have the preset dimension classification and the preset label value classification, the retrieval can be carried out aiming at the plurality of retrieval conditions of the demander, the condition that the retrieval can be carried out only aiming at a single data source in the prior art is avoided, and the retrieval efficiency is improved; in addition, the suppliers can be sequenced by utilizing the retrieval conditions and retrieved according to the retrieval sequence, so that flexible routing retrieval can be performed according to the retrieval strategy customized by the demander, the data purchasing cost of the demander is reduced, and the data retrieval flexibility is realized; the requirement of the demander for searching the priority can be met, so that the demander can obtain the required data, and the user experience is improved.
Preferably, as shown in fig. 7, the sorting module 602 may include: a requirement field receiving unit 6021 adapted to receive a requirement field input by the requiring party; a supplier determination unit 6022 adapted to determine the plurality of suppliers providing the requirement field; the ranking unit 6023 is adapted to rank the plurality of suppliers according to the matching of the data provided by the plurality of suppliers with the plurality of retrieval conditions and the order of priority of the plurality of retrieval conditions.
Further, the ordering unit 6023 may include a matching subunit (not shown) adapted to match the data provided by the supplier with the retrieval conditions in order of the priorities of the plurality of retrieval conditions to obtain a matching result; a sorting subunit (not shown), adapted to determine the order position of the supplier according to the priority of the search condition matched by the supplier in the matching result, wherein the higher the priority of the search condition matched by the supplier is, the higher the order position of the supplier is.
As shown in fig. 8, the data retrieval device 60 may further include: a first stopping module 605 adapted to stop retrieving when data matching the subject identifier is acquired;
alternatively, the second stopping module 606 is adapted to stop the retrieval when the set stopping condition is reached.
Further, the data retrieving device 60 may further include: a preprocessing module 607 adapted to perform a normalization process on the source data provided by the plurality of suppliers to obtain normalized data, wherein the normalized data has the preset dimension classification and the preset label value classification.
A normalized data receiving module 608 adapted to receive normalized data provided by the plurality of suppliers, the normalized data having the preset dimension classification and the preset label value classification
The data access module 609 is adapted to perform semantic analysis on the standardized data, and classify preset dimension classifications and preset label values in the standardized data into corresponding fields.
For more details of the operation principle and the operation mode of the data retrieval device 60, reference may be made to the related descriptions in fig. 1 to 5, which are not described herein again.
The embodiment of the invention also discloses a storage medium, on which computer instructions are stored, and when the computer instructions are operated, the steps of the data retrieval method shown in fig. 1, fig. 2 or fig. 3 can be executed. The storage medium may include ROM, RAM, magnetic or optical disks, etc.
The embodiment of the invention also discloses a terminal which can comprise a memory and a processor, wherein the memory is stored with computer instructions capable of running on the processor. The processor, when executing the computer instructions, may perform the steps of the data retrieval method shown in fig. 1, 2 or 3. The terminal includes, but is not limited to, a server, a computer, a tablet computer and other terminal devices.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (13)
1. A method of data retrieval, comprising:
receiving retrieval priority constraints input by a demand side, wherein the retrieval priority constraints comprise a plurality of retrieval conditions with different priorities;
the multiple suppliers are sequenced according to the multiple retrieval conditions and data provided by the multiple suppliers to obtain a retrieval sequence, the data provided by the multiple suppliers have preset dimension classification and preset label value classification, and the retrieval conditions comprise the preset dimension classification and the preset label value classification;
receiving an inquiry request sent by a demand party, wherein the inquiry request comprises a main body identifier;
sequentially searching the data provided by the plurality of suppliers according to the searching sequence to obtain the data matched with the main body identification;
if the data matched with the main body identification is obtained, stopping retrieval;
or, if the set stop condition is reached, the search is stopped.
2. The data retrieval method of claim 1, wherein the ordering the plurality of providers according to the retrieval priority constraints and data provided by the plurality of providers comprises:
receiving a requirement field input by the requiring party;
determining the plurality of suppliers that provide the demand field;
and sorting the plurality of suppliers according to the matching of the data provided by the plurality of suppliers and the plurality of retrieval conditions and the priority order of the plurality of retrieval conditions.
3. The data retrieval method of claim 2, wherein the sorting the plurality of suppliers according to the matching degree of the data provided by the plurality of suppliers to the plurality of retrieval conditions and the order of the priorities of the plurality of retrieval conditions comprises:
matching the data provided by the supplier with the retrieval conditions according to the high-low order of the priorities of the plurality of retrieval conditions to obtain a matching result;
and determining the sequence position of the supplier according to the priority of the retrieval condition matched by the supplier in the matching result, wherein the higher the priority of the retrieval condition matched by the supplier is, the higher the sequence position of the supplier is.
4. The data retrieval method of claim 1, wherein the sequentially retrieving the data provided by the plurality of suppliers in the retrieval order comprises:
and matching the subject identification and the subject identification in the data provided by each supplier according to the retrieval sequence, and outputting the data comprising the subject identification.
5. The data retrieval method of claim 1, wherein the receiving of the retrieval priority constraint input by the requestor comprises, before:
normalizing the source data provided by the plurality of suppliers to obtain normalized data, wherein the normalized data has the preset dimension classification and the preset label value classification;
or, receiving standardized data provided by the plurality of suppliers, wherein the standardized data is provided with the preset dimension classification and the preset label value classification.
6. The data retrieval method of claim 5, further comprising:
and performing semantic analysis on the standardized data, and classifying preset dimension classifications and preset label value classifications in the standardized data into corresponding fields.
7. A data retrieval device, comprising:
the retrieval priority constraint receiving module is suitable for receiving retrieval priority constraints input by a demand party, and the retrieval priority constraints comprise a plurality of retrieval conditions with different priorities;
the ordering module is suitable for ordering the multiple suppliers according to the multiple retrieval conditions and data provided by the multiple suppliers to obtain a retrieval sequence, the data provided by the multiple suppliers has a preset dimension classification and a preset label value classification, and the retrieval conditions comprise the preset dimension classification and the preset label value classification;
the query request receiving module is suitable for receiving a query request sent by a demand party, and the query request comprises a main body identifier;
the retrieval module is suitable for sequentially retrieving the data provided by the plurality of suppliers according to the retrieval sequence so as to obtain the data matched with the main body identification;
the first stopping module is suitable for stopping retrieval when the data matched with the main body identification is obtained;
and the second stopping module is suitable for stopping retrieval when the set stopping condition is reached.
8. The data retrieval device of claim 7 wherein the ranking module comprises:
the requirement field receiving unit is suitable for receiving a requirement field input by the requiring party;
a supplier determination unit adapted to determine the plurality of suppliers providing the demand field;
the ordering unit is suitable for ordering the suppliers according to the matching of the data provided by the suppliers and the retrieval conditions and the priority order of the retrieval conditions.
9. The data retrieval device of claim 8 wherein the sorting unit comprises:
the matching subunit is suitable for matching the data provided by the supplier with the retrieval conditions according to the high-low order of the priorities of the plurality of retrieval conditions to obtain a matching result;
the ordering subunit is adapted to determine the order position of the supplier according to the priority of the search condition matched by the supplier in the matching result, and the higher the priority of the search condition matched by the supplier is, the higher the order position of the supplier is.
10. The data retrieval device of claim 7, wherein the retrieval module matches the subject identifier and the subject identifier in the data provided by each supplier in the retrieval order, and outputs the data including the subject identifier.
11. The data retrieval device of claim 7, further comprising:
the preprocessing module is suitable for carrying out standardization processing on source data provided by the plurality of suppliers to obtain standardized data, and the standardized data is provided with the preset dimension classification and the preset label value classification;
or, the standardized data receiving module is suitable for receiving standardized data provided by the plurality of suppliers, and the standardized data is provided with the preset dimension classification and the preset label value classification.
12. The data retrieval device of claim 11, further comprising:
and the data access module is suitable for performing semantic analysis on the standardized data and classifying preset dimensionality classification and preset label value classification in the standardized data into corresponding fields.
13. A terminal comprising a memory and a processor, the memory having stored thereon computer instructions executable on the processor, wherein the processor, when executing the computer instructions, performs the steps of the data retrieval method of any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711059897.5A CN107748792B (en) | 2017-11-01 | 2017-11-01 | Data retrieval method and device and terminal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711059897.5A CN107748792B (en) | 2017-11-01 | 2017-11-01 | Data retrieval method and device and terminal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107748792A CN107748792A (en) | 2018-03-02 |
| CN107748792B true CN107748792B (en) | 2020-11-27 |
Family
ID=61253469
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711059897.5A Active CN107748792B (en) | 2017-11-01 | 2017-11-01 | Data retrieval method and device and terminal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107748792B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108573026B (en) * | 2018-03-14 | 2021-01-19 | 上海数据交易中心有限公司 | Data circulation method and device, storage medium and server |
| CN108920581B (en) * | 2018-06-25 | 2021-05-04 | 上海数据交易中心有限公司 | Data circulation method and device, storage medium and server |
| CN109544329B (en) * | 2018-10-09 | 2023-09-05 | 创新先进技术有限公司 | Method, device and system for matching |
| CN109145011B (en) * | 2018-11-01 | 2023-07-18 | 上海数据交易中心有限公司 | Data retrieval method and device and terminal |
| CN110704545B (en) * | 2019-09-12 | 2022-06-07 | 上海数禾信息科技有限公司 | Data calling method and device for data source provider |
| CN111563774A (en) * | 2020-05-08 | 2020-08-21 | 上海腾暨物联网科技有限公司 | Method and system for constructing coal price index prediction and supply-demand relation index |
| CN112346876B (en) * | 2020-12-04 | 2023-04-18 | 山东鲁软数字科技有限公司 | Channel distribution method and system with autonomous learning characteristic |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020070A (en) * | 2011-09-22 | 2013-04-03 | 联想(北京)有限公司 | Searching method and electronic terminal |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101685456B (en) * | 2008-09-26 | 2013-08-28 | 华为技术有限公司 | Search method, system and device |
| US8209313B2 (en) * | 2009-01-28 | 2012-06-26 | Rovi Technologies Corporation | Structuring and searching data in a hierarchical confidence-based configuration |
| CN106203140B (en) * | 2016-07-15 | 2019-03-26 | 上海数据交易中心有限公司 | Data circulation method, device and terminal based on data structure |
| CN106815313A (en) * | 2016-12-21 | 2017-06-09 | 上海数据交易中心有限公司 | The data system for the distribution of commodities and method |
| CN106709760A (en) * | 2016-12-21 | 2017-05-24 | 上海数据交易中心有限公司 | Single data based data price evaluation method and device |
| CN107229730A (en) * | 2017-06-08 | 2017-10-03 | 北京奇虎科技有限公司 | Data query method and device |
-
2017
- 2017-11-01 CN CN201711059897.5A patent/CN107748792B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020070A (en) * | 2011-09-22 | 2013-04-03 | 联想(北京)有限公司 | Searching method and electronic terminal |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107748792A (en) | 2018-03-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107748792B (en) | Data retrieval method and device and terminal | |
| CN108595157B (en) | Block chain data processing method, device, equipment and storage medium | |
| US11036552B2 (en) | Cognitive scheduler | |
| CN110995459B (en) | Abnormal object identification method, device, medium and electronic equipment | |
| US20200057958A1 (en) | Identification and application of hyperparameters for machine learning | |
| CN110930221B (en) | Abnormal order processing method, storage medium and computer equipment | |
| CN109033101A (en) | Label recommendation method and device | |
| CN111048215B (en) | Medical video production method and system based on CRM | |
| JP6621945B2 (en) | Service dispatch system and method based on user behavior | |
| WO2020107864A1 (en) | Information processing method, device, service equipment and computer readable storage medium | |
| US20150302088A1 (en) | Method and System for Providing Personalized Content | |
| CN112330382B (en) | Item recommendation method, device, computing equipment and medium | |
| CN110909040B (en) | Business delivery auxiliary method and device and electronic equipment | |
| CN110515929B (en) | Book display method, computing device and storage medium | |
| CN116226531A (en) | Intelligent recommendation method for financial products of small and micro enterprises and related products | |
| CN114491220A (en) | Object processing method, device, equipment and medium | |
| CN112785180A (en) | Business operation management system and method with autonomous prompt function | |
| US11615089B1 (en) | System, method, and computer program for converting a natural language query to a structured database query | |
| US8918406B2 (en) | Intelligent analysis queue construction | |
| WO2019222908A1 (en) | Automatic selection of request handler using trained classification model | |
| CN114757534A (en) | Intelligent attendance scheduling and evaluation method, attendance scheduling device and system | |
| CN113971241A (en) | Library book searching method and intelligent book searching robot | |
| US11625400B2 (en) | Optimal query scheduling for resource utilization optimization | |
| CN103020276A (en) | Method and device for searching social contact objects | |
| CN116187714B (en) | Task intelligent distribution method, system, terminal and medium based on definable rule |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |