CN108923938B - Channel selection method and equipment - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications
- H04L12/1453—Methods or systems for payment or settlement of the charges for data transmission involving significant interaction with the data transmission network
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- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/22—Payment schemes or models
- G06Q20/28—Pre-payment schemes, e.g. "pay before"
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- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0613—Electronic shopping [e-shopping] using intermediate agents
- G06Q30/0617—Representative agent
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- H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications
- H04L12/1485—Tariff-related aspects
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications
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Abstract
Description
Technical Field
The invention relates to the technical field of internet traffic ordering application, in particular to a channel selecting method and equipment.
Background
The popularization rate of the current smart phone is very high, the demand on data traffic is very large, and people usually recharge the phone fee or the traffic through the internet. Therefore, the flow service is in explosive growth, the ordering support platform of the flow recharging service is accessed to a plurality of suppliers, and for flow retail sellers, a flow ordering supply channel with the best quality needs to be found more quickly and accurately.
The methods provided in the prior art are time consuming and often fail to accurately find an order-supply channel of best quality. The optimization of resource allocation is influenced to a certain extent, the use experience of consumers is also influenced, and the optimal scheme cannot be obtained and used to realize flow ordering.
Disclosure of Invention
In view of the above, it is desirable to provide a data channel selecting method and apparatus for addressing at least one of the above-mentioned problems.
A data channel selection method, adapted to be executed in a computing device, comprising the steps of:
acquiring a plurality of data channels to be determined, acquiring channel product information according to the data channels, and generating a plurality of product data lists corresponding to the data channels one by one;
sequencing each product data list according to a preset format, and giving each product data in the product data list a priority;
and traversing the product data in the data channel according to the selection priority, judging that the product data meet a preset screening condition, and determining an application data channel corresponding to a product data list.
In one embodiment, the predetermined screening condition comprises at least one of:
the region attribute in the product data meets a predetermined region attribute;
the category attribute in the product data meets a predetermined category attribute;
the ratio attribute in the product data satisfies a predetermined ratio attribute.
In one embodiment, the step of acquiring a number of data channels to be determined includes:
and acquiring attribute information of the data channel before a preset time interval according to the channel template, wherein the attribute information comprises product price, ordering success rate and average consumed time.
In one embodiment, the preset format includes:
the price parameter in the product data corresponds to a preset price value interval;
ordering time in the product data corresponds to a preset time interval;
the ordering success rate in the product data corresponds to a preset probability interval;
the preset price value interval, the preset time interval and the preset probability interval respectively correspond to preset priority weights.
In one embodiment, after the step of determining the application data channel corresponding to the product data list, the method further includes:
sending an ordering request to a target data set according to the application data channel and acquiring returned result information;
and according to the returned result information, confirming that the application data channel is a fault channel, and deleting the fault channel.
Further, the step of confirming that the application data channel is a failure channel specifically includes:
and reading the time information in the returned result information, judging that the time information exceeds a preset time threshold value, and confirming that the application data channel is a fault channel.
Further, the step of deleting the failed channel further comprises:
according to a preset time period, resending a test request to the fault channel at a preset frequency;
and acquiring a response request corresponding to the test request, judging that the response request meets preset state parameters, and recovering the fault channel to be a normal application data channel.
The invention correspondingly provides a data channel selecting device, which comprises:
the acquisition module is used for acquiring a plurality of data channels to be determined, acquiring channel product information according to the data channels and generating a plurality of product data lists corresponding to the data channels one by one;
the sorting module is used for sorting each product data list according to a preset format and giving each product data in the product data list a priority;
and the determining module is used for traversing the product data in the data channel according to the selection priority, judging that the product data meets a preset screening condition, and determining an application data channel corresponding to a product data list.
The invention also provides data channel selecting equipment, which comprises a processor and a memory for storing executable instructions of the processor; wherein the processor is configured to:
acquiring a plurality of data channels to be determined, acquiring channel product information according to the data channels, and generating a plurality of product data lists corresponding to the data channels one by one;
sequencing each product data list according to a preset format, and giving each product data in the product data list a priority;
and traversing the product data in the data channel according to the selection priority, judging that the product data meet a preset screening condition, and determining an application data channel corresponding to a product data list.
The data channel selection method and the data channel selection equipment provided by the invention can flexibly obtain the most appropriate data channel under different situations by screening the flow booking data channel and selecting the optimal data channel according to the conditions, thereby improving the success rate of flow booking and improving the use experience of consumers.
Drawings
FIG. 1 is a flow chart of a data channel selection method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a data channel selecting device according to an embodiment of the present invention.
Detailed Description
To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
An embodiment of the present invention provides a data channel selecting method, which is suitable for being executed in a computing device, as shown in fig. 1, and includes the following steps S100 to S300:
step S100: the method comprises the steps of obtaining a plurality of data channels to be determined, obtaining channel product information according to the data channels, and generating a plurality of product data lists corresponding to the data channels one to one. The selection is performed within a certain data channel range, and first, data channels to be determined need to be obtained, and the data channels can be used for subscribing the traffic service. Specifically, attribute information of a data channel before a preset time interval is obtained according to a channel template, wherein the attribute information comprises product price, ordering success rate and average time consumption, for example, relevant information of all channel products in the previous day is obtained according to the channel template: product price, successful ordering times, successful ordering rate, average time consumption and the like. Each data channel corresponds to channel product information, namely product attributes in the channel, including price, application field, application geographic position, data category and the like. The product quantity contained in each data channel may be different, and the product attribute of each product may also be different, so that according to the one-to-one correspondence relationship of the data channels, the product data list corresponding to the data channels is generated, and selection is performed according to the product information listed in the product data list, so as to determine the data channel which best meets the requirements.
Step S200: and sequencing each product data list according to a preset format, and giving each product data in the product data list a priority. The preset format comprises one or more of the following:
1. the price parameter in the product data corresponds to a preset price value interval;
2. ordering time in the product data corresponds to a preset time interval;
3. the ordering success rate in the product data corresponds to a preset probability interval.
And the preset price value interval, the preset time interval and the preset probability interval respectively correspond to preset priority weights. For example, the preset price value interval has (1,3) and (3,5), where (1,3) corresponds to a preset priority weight of 3, and (3,5) corresponds to a preset priority weight of 1, the lower the price, the higher the corresponding preset priority weight. Correspondingly, the shorter the ordering time is, the higher the priority weight is, the greater the ordering success rate is, and the higher the priority weight is. The product data in the product data list are sequenced through preset format processing, the product data in a certain sequence range are prioritized, the product data for selection is determined according to the priority, and the data channel for selection is further determined.
Step S300: and according to the product data in the traversal data channel with the selected priority, judging that the product data meets a preset screening condition, and determining an application data channel corresponding to the product data list. According to the selection priority determined in step S200, traversing the product data in the data channel corresponding to the selection priority, and determining whether the product data meets a predetermined screening condition, where the predetermined screening condition is often from the customer data, and includes at least one of the following conditions:
1. the region attributes in the product data satisfy the predetermined region attributes. Such as traffic data, can be used within a certain geographical area.
2. The category attribute in the product data satisfies the predetermined category attribute. Namely whether the used network is the network meeting the requirements of the client.
3. The ratio attribute in the product data satisfies a predetermined ratio attribute. I.e. whether the proportion of the product data category meets the customer requirements.
As a preferred scheme, after the step of determining the application data channel corresponding to the product data list, the method further includes:
and sending an ordering request to the target data set according to the application data channel and acquiring returned result information. And sending an order request to a specific target terminal to judge whether the target terminal is in an effective state. After sending the request, the target terminal typically sends a return result message, which includes status information, time information, and the like of the target terminal.
And according to the returned result information, confirming that the application data channel is a fault channel, and deleting the fault channel. If the application data channel can be judged to have a fault according to the state information or the time information, deleting the fault channel from the screened application data channel, for example, reading the time information in the returned result information, judging that the time information exceeds a preset time threshold value, and confirming that the application data channel is the fault channel.
Of course, the deleted information should remain in the system for subsequent use. For example, it is further preferable that the step of deleting the failed channel further includes:
according to a preset time period, resending a test request to the fault channel at a preset frequency;
and acquiring a response request corresponding to the test request, judging that the response request meets preset state parameters, and recovering the fault channel to be a normal application data channel.
The testing is carried out again at certain time intervals, the fault states in some fault channels are temporary, and the optimal and available data channels are selected from the selected application data channels, so that the efficiency can be further improved.
The present invention correspondingly provides a data channel selecting apparatus, as shown in fig. 2, including:
theacquisition module 10 is configured to acquire a plurality of data channels to be determined, acquire channel product information according to the data channels, and generate a plurality of product data lists corresponding to the data channels one to one.
The sortingmodule 20 is configured to sort each product data list according to a preset format, and give each product data in the product data list a priority.
The determiningmodule 30 is configured to determine the application data channel according to a predetermined filtering condition.
Based on the idea of a computer system, the invention also provides data channel selection equipment, which comprises a processor and a memory for storing executable instructions of the processor; wherein the processor is configured to implement steps S100-S300:
step S100: the method comprises the steps of obtaining a plurality of data channels to be determined, obtaining channel product information according to the data channels, and generating a plurality of product data lists corresponding to the data channels one to one.
Step S200: and sequencing each product data list according to a preset format, and giving each product data in the product data list a priority.
Step S300: and according to the product data in the traversal data channel with the selected priority, judging that the product data meets a preset screening condition, and determining an application data channel corresponding to the product data list.
The apparatuses or modules illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.
One skilled in the art will recognize that one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. Especially, for the server device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for relevant points, refer to part of the description of the method embodiment.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The above description is only exemplary of the preferred embodiment of one or more embodiments of the present disclosure, and is not intended to limit the present disclosure, so that any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (6)
1. A data channel selection method adapted to be executed in a computing device, comprising the steps of:
acquiring a plurality of data channels to be determined, acquiring channel product information according to the data channels, and generating a plurality of product data lists corresponding to the data channels one by one;
sequencing each product data list according to a preset format, and giving each product data in the product data list a priority;
traversing the product data in the data channel according to the selection priority, judging that the product data meet a preset screening condition, and determining an application data channel corresponding to a product data list;
the preset format comprises:
the price parameter in the product data corresponds to a preset price value interval;
ordering time in the product data corresponds to a preset time interval;
the ordering success rate in the product data corresponds to a preset probability interval;
the preset price value interval, the preset time interval and the preset probability interval respectively correspond to preset priority weights;
the predetermined screening condition includes at least one of: the region attribute in the product data meets a predetermined region attribute; the category attribute in the product data meets a predetermined category attribute; the proportion attribute in the product data meets a preset proportion attribute;
the step of obtaining a plurality of data channels to be determined comprises: and acquiring attribute information of the data channel before a preset time interval according to the channel template, wherein the attribute information comprises product price, ordering success rate and average consumed time.
2. The method of claim 1, wherein the step of determining the application data channel corresponding to the product data list further comprises:
sending an ordering request to a target data set according to the application data channel and acquiring returned result information;
and according to the returned result information, confirming that the application data channel is a fault channel, and deleting the fault channel.
3. The method according to claim 2, wherein the step of confirming that the application data channel is a failure channel specifically comprises:
and reading the time information in the returned result information, judging that the time information exceeds a preset time threshold value, and confirming that the application data channel is a fault channel.
4. The method of claim 2, wherein the step of deleting the failed channel is further followed by:
according to a preset time period, resending a test request to the fault channel at a preset frequency;
and acquiring a response request corresponding to the test request, judging that the response request meets preset state parameters, and recovering the fault channel to be a normal application data channel.
5. A data channel selection apparatus, comprising:
the acquisition module is used for acquiring a plurality of data channels to be determined, acquiring channel product information according to the data channels and generating a plurality of product data lists corresponding to the data channels one by one;
the sorting module is used for sorting each product data list according to a preset format and giving each product data in the product data list a priority; the determining module is used for traversing the product data in the data channel according to the selection priority, judging that the product data meet a preset screening condition, and determining an application data channel corresponding to a product data list;
the preset format comprises:
the price parameter in the product data corresponds to a preset price value interval;
ordering time in the product data corresponds to a preset time interval;
the ordering success rate in the product data corresponds to a preset probability interval;
the preset price value interval, the preset time interval and the preset probability interval respectively correspond to preset priority weights;
the predetermined screening condition includes at least one of: the region attribute in the product data meets the preset region attribute, the category attribute in the product data meets the preset category attribute, and the proportion attribute in the product data meets the preset proportion attribute;
the acquiring a plurality of data channels to be determined comprises: and acquiring attribute information of the data channel before a preset time interval according to the channel template, wherein the attribute information comprises product price, ordering success rate and average consumed time.
6. A data channel selection device comprising a processor and a memory for storing processor-executable instructions; wherein the processor is configured to:
acquiring a plurality of data channels to be determined, acquiring channel product information according to the data channels, and generating a plurality of product data lists corresponding to the data channels one by one;
sequencing each product data list according to a preset format, and giving each product data in the product data list a priority;
traversing the product data in the data channel according to the selection priority, judging that the product data meet a preset screening condition, and determining an application data channel corresponding to a product data list;
the preset format comprises:
the price parameter in the product data corresponds to a preset price value interval;
ordering time in the product data corresponds to a preset time interval;
the ordering success rate in the product data corresponds to a preset probability interval;
the preset price value interval, the preset time interval and the preset probability interval respectively correspond to preset priority weights;
the predetermined screening condition includes at least one of: the region attribute in the product data meets the preset region attribute, the category attribute in the product data meets the preset category attribute, and the proportion attribute in the product data meets the preset proportion attribute;
the acquiring a plurality of data channels to be determined comprises: and acquiring attribute information of the data channel before a preset time interval according to the channel template, wherein the attribute information comprises product price, ordering success rate and average consumed time.
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