CN112785392A - Position recommendation method and device and electronic equipment - Google Patents
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Abstract
The embodiment of the invention discloses a position recommendation method, a position recommendation device and electronic equipment. Therefore, a plurality of recommendation points can be provided for the target user terminal for selection aiming at a more complex target position, so that the target recommendation points can better meet the user requirements.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a position recommendation method and device and electronic equipment.
Background
In the field of logistics, network appointment and the like which need to reach a target position, a target point is often determined according to the target position provided by a user so as to be reached by a task execution party. For example, in the field of car booking, the server needs the starting address provided by the passenger to determine the destination point of the passenger, but the destination point recommended by the server sometimes does not meet the requirement of the passenger, for example, the passenger needs to spend much cost (such as long distance, need to cross the way to reach, etc.) to reach the destination point, resulting in poor experience of the passenger.
Disclosure of Invention
In view of this, embodiments of the present invention provide a position recommendation method and apparatus, and an electronic device, so as to provide multiple recommendation points for a target user terminal to select for a more complex target position, so that the target recommendation points better meet user requirements, and user experience is improved.
In a first aspect, an embodiment of the present invention provides a location recommendation method, where the method includes:
acquiring target task information, wherein the target task information comprises a target position;
in response to detecting that the target position meets a predetermined condition, acquiring a plurality of recommendation points;
pushing a plurality of recommendation points to a target user terminal so that a target user determines a target recommendation point;
the preset condition satisfaction state of the target position is determined according to the abnormal parameter corresponding to the target position, and the abnormal parameter is used for representing the historical task proportion that the historical recommendation point corresponding to the target position does not meet the preset requirement.
In a second aspect, an embodiment of the present invention provides a position recommendation apparatus, where the apparatus includes:
the information acquisition unit is configured to acquire target task information, wherein the target task information comprises a target position, and the target position is a target starting address or a target reaching address;
a recommended point acquisition unit configured to acquire a plurality of recommended points in response to detection that the target position satisfies a predetermined condition;
the first pushing unit is configured to push a plurality of recommendation points to a target user terminal so that a target user determines a target recommendation point;
the preset condition satisfaction state of the target position is determined according to the abnormal parameter corresponding to the target position, and the abnormal parameter is used for representing the historical task proportion that the historical recommendation point corresponding to the target position does not meet the preset requirement.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, where the memory is used to store one or more computer program instructions, where the one or more computer program instructions are executed by the processor to implement the method according to the first aspect of the embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements the method according to the first aspect of the embodiment of the present invention.
In a fifth aspect, embodiments of the present invention provide a computer program product, which when run on a computer causes the computer to perform the method according to the first aspect of embodiments of the present invention.
The method and the device for determining the target recommendation point of the target user terminal acquire the target task information comprising the target position, respond to the fact that the target position meets the preset conditions, acquire the plurality of recommendation points, and push the plurality of recommendation points to the target user terminal so that the target user can determine the target recommendation point, wherein the preset conditions meeting state of the target position is determined according to the abnormal parameters corresponding to the target position. Therefore, a plurality of recommendation points can be provided for the target user terminal for selection aiming at a more complex target position, so that the target recommendation points can better meet the user requirements.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a location recommendation method of an embodiment of the present invention;
FIG. 2 is a flowchart of a method for determining the satisfaction of a predetermined condition at a target location according to an embodiment of the present invention;
FIG. 3 is a flow chart of an exception parameter acquisition method of an embodiment of the present invention;
FIG. 4 is a flowchart of another method for determining a state where a predetermined condition for a target location is satisfied according to an embodiment of the present invention;
FIGS. 5 and 6 are schematic interface diagrams of a target user terminal according to an embodiment of the present invention;
FIG. 7 is a schematic interface diagram of a target task execution end according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a position recommendation device of an embodiment of the present invention;
fig. 9 is a schematic diagram of an electronic device of an embodiment of the invention.
Detailed Description
The present invention will be described below based on examples, but the present invention is not limited to only these examples. In the following detailed description of the present invention, certain specific details are set forth. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details. Well-known methods, procedures, components and circuits have not been described in detail so as not to obscure the present invention.
Further, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.
Unless the context clearly requires otherwise, throughout the description, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, what is meant is "including, but not limited to".
In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the following embodiments, a network appointment as an example is mainly described in detail, it should be understood that the embodiments of the present invention are not limited to being applied to a network appointment application scenario, and other application scenarios that require a target recommendation point to be determined based on a target location, such as a logistics field, may all adopt the location recommendation method of the present embodiment.
Fig. 1 is a flowchart of a location recommendation method according to an embodiment of the present invention. As shown in fig. 1, the position recommendation method according to the embodiment of the present invention includes the following steps:
step S110, target task information is obtained. Wherein the target task information includes a target location. Optionally, taking a network appointment application scenario as an example, the target location may be a real-time location where the user initiates a target task, or may be a target starting address or a target reaching address of the target task. Optionally, in this embodiment, the target location is a Point Of Interest (POI) such as a cell, a school, an office building, a park, a mall, and a hospital.
Step S120, in response to detecting that the target position satisfies a predetermined condition, acquiring a plurality of recommendation points. And determining the state of the preset condition satisfaction of the target position according to the abnormal parameter corresponding to the target position. The abnormal parameters are used for representing the historical task proportion that the historical recommendation points corresponding to the target position do not meet the preset requirements. Optionally, if the user reaches the historical recommendation point from the target location, or the cost parameter of reaching the target location from the historical recommendation point is greater than or equal to the predetermined cost threshold, the historical recommendation point does not meet the predetermined requirement. Wherein, the cost parameter is characterized according to the time and/or the actual movement distance of the user from the target position to the historical recommendation point. For example, if the historical recommended point is reached from the target position by passing a cross road, the time and the actual moving distance are long, and the cost parameter is also large. Optionally, the plurality of recommended points are determined according to coordinate information (e.g., longitude and latitude coordinates) of the target location, the surrounding environment information, and a historical task record corresponding to the target location.
Step S130, pushing a plurality of recommendation points to the target user terminal so that the target user can determine the target recommendation points.
The method and the device for determining the target recommendation point of the target user terminal acquire the target task information comprising the target position, respond to the fact that the target position meets the preset conditions, acquire the plurality of recommendation points, and push the plurality of recommendation points to the target user terminal so that the target user can determine the target recommendation point, wherein the preset conditions meeting state of the target position is determined according to the abnormal parameters corresponding to the target position. Therefore, a plurality of recommendation points can be provided for the target user terminal for selection aiming at a more complex target position, so that the target recommendation points can better meet the user requirements.
In an alternative implementation, the step of determining that the predetermined condition of the target position satisfies the state includes: and acquiring abnormal parameters corresponding to the target position, and determining that the target position meets a preset condition in response to the fact that the abnormal parameters corresponding to the target position are greater than or equal to corresponding parameter thresholds. Therefore, in the embodiment, only when the abnormal parameter of the target position is greater than or equal to the parameter threshold, that is, the probability that the recommended point does not meet the requirement is high, the plurality of recommended points are recommended to the target user terminal, so that the target user can select the target recommended point which is convenient to reach, thereby avoiding pushing the target recommended point with a high cost parameter to the target user, and avoiding disturbing the target user and increasing the operation burden of the target user when the abnormal parameter of the target position is less than the parameter threshold, that is, the probability that the recommended point does not meet the requirement is low. Thus, the user experience can be improved.
In another alternative implementation, the target location has a corresponding category label, each category label having a corresponding parameter threshold. For example, POIs having a large traffic volume such as train stations and bus stops have the same category label, and each cell has the same category label. Optionally, the obtained target location information includes a category label of the target location and a corresponding parameter threshold. In other optional implementation manners, an association relationship between the category label and the corresponding parameter threshold is pre-stored, the information of the target location includes the location coordinate and the category label, and the corresponding parameter threshold is obtained by querying according to the category label of the target location. The storage and acquisition process of the parameter threshold is not limited in this embodiment.
Fig. 2 is a flowchart of a method for determining a state where a predetermined condition of a target location is satisfied according to an embodiment of the present invention. As shown in fig. 2, in the present embodiment, the step of determining that the predetermined condition of the target position satisfies the state includes:
step S210, obtaining an abnormal parameter corresponding to the target position. Optionally, the abnormal parameter corresponding to the target position is determined according to the historical task information of each target corresponding to the target position.
Step S220, determining a corresponding parameter threshold according to the category label of the target location. In an alternative implementation manner, the parameter threshold corresponding to each category label is determined according to the POI feature of the category. Optionally, the abnormal parameters corresponding to the POIs in each category are larger overall, the corresponding parameter threshold values are larger, the abnormal parameters corresponding to the POIs are smaller overall, and the corresponding parameter threshold values are smaller.
Step S230, in response to detecting that the abnormal parameter is greater than or equal to the corresponding parameter threshold, determining that the target position satisfies the predetermined condition.
The embodiment configures corresponding parameter thresholds for different types of tags so as to adapt to different POI characteristics, thereby further improving the accuracy of obtaining the target positions of multiple recommendation points to be pushed, and further improving the user experience.
Fig. 3 is a flowchart of an abnormal parameter acquiring method according to an embodiment of the present invention. As shown in fig. 3, in this embodiment, acquiring the abnormal parameter corresponding to the target position includes the following steps:
step S211, a target history task set corresponding to the target position is acquired. Taking a network appointment vehicle as an example, a starting address or an arrival address of a task is obtained as a target historical task set of the target position.
Step S212, determining cost parameters of the target historical tasks according to the target positions and the recommendation points corresponding to the target historical tasks. In an optional implementation manner, the cost parameter of the target historical task is obtained according to an actual movement distance and/or an actual movement time from the target position to a recommended point corresponding to the target historical task.
Step S213, calculating a ratio of the number of target historical tasks with the cost parameter greater than or equal to the cost threshold to the total number of target historical tasks in the historical task set, to obtain an abnormal parameter corresponding to the target position. That is to say, in this embodiment, if the cost parameter of the target historical task is greater than or equal to the cost threshold, the recommended point corresponding to the target historical task is not in accordance with the predetermined requirement (for example, the user is unsatisfied due to the need of reaching across roads or being too far away). Alternatively, the cost threshold may be determined based on feedback information from the user (e.g., evaluation of the order or complaint information, etc.).
In an alternative implementation, the abnormal parameters of each POI may be predetermined through steps S211-S213. Optionally, the abnormal parameters of each POI are periodically updated in real time. For example, every predetermined time (e.g., 1 week, 1 month, etc.), the abnormal parameters of each POI are updated according to the historical task records of the POI in the previous N months (N is greater than 1).
Fig. 4 is a flowchart of another method for determining that a predetermined condition of a target position is satisfied according to an embodiment of the present invention. As shown in fig. 4, in the present embodiment, the step of determining that the predetermined condition of the target position satisfies the state includes:
step S310, abnormal parameters corresponding to historical positions corresponding to a plurality of historical tasks are obtained. That is, the abnormality parameter for each POI location (each history location) is acquired. Optionally, the foregoing steps S211 to S213 are adopted to determine the abnormal parameters of the positions of the POIs, which is not described herein again. It should be understood that the historical location in the present embodiment is also location information used in the historical task.
Step S320, sorting the historical positions according to the abnormal parameters of the historical positions. Optionally, the historical positions are sorted from large to small according to the abnormal parameters. In other alternative implementations, the historical locations may also be sorted from small to large according to the anomaly parameter.
And step S330, determining an abnormal position set based on the sequencing result and the corresponding preset flow. Wherein the predetermined flow rate characterizes a ratio of a number of historical locations in the set of abnormal locations to a total number of historical locations. Alternatively, the predetermined flow rate may be determined based on the feedback information of the user and the total number of historical locations.
Optionally, the historical position number M in the abnormal position set is f (the predetermined flow rate p is the total historical position number M). Where f (×) is a rounding function, which may be rounded by rounding, rounded up, or rounded down, and this embodiment is not limited thereto. Therefore, in step S320, when sorting according to the abnormal parameter from large to small, for example, sorting by using a bubble method, the first m history positions are acquired to be an abnormal position set, and it is not necessary to continue the sorting operation for the subsequent history positions, so as to reduce the amount of calculation.
Step S340, determining that the target position meets the predetermined condition at least according to the relationship between the target position and the abnormal position set. Optionally, in response to detecting that the target position is located in the abnormal position set, it is determined that the target position satisfies a predetermined condition.
Therefore, in this embodiment, when the abnormal parameter of the target position is large, multiple recommendation points are recommended to the target user terminal, so that the target user can select a target recommendation point which is convenient to reach, that is, the target recommendation point with a large cost parameter is prevented from being pushed to the target user, and the situation that when the abnormal parameter of the target position is small, the target user is disturbed, and the operation burden of the target user is increased is also avoided. Thus, the user experience can be improved.
In another optional implementation manner, the step S320 of having a corresponding category label for each historical location may specifically include: and respectively sequencing the historical positions belonging to the same category according to the abnormal parameters of the historical positions, and acquiring sequencing results corresponding to the labels of the categories. Optionally, each category label has a corresponding predetermined flow parameter. Step S330 may specifically include: and determining an abnormal position set corresponding to each class label based on the sequencing result of each class label and the preset flow parameter corresponding to each class label. The step S340 may specifically include: and determining that the target position meets a preset condition in response to detecting that the target position is located in the abnormal position set corresponding to the class label to which the target position belongs. Therefore, the historical positions of different types of labels are sorted, the corresponding preset flow parameters are configured based on the characteristics of the labels of the different types, the accuracy of obtaining the target positions of the plurality of recommendation points to be pushed is further improved, and the user experience is further improved.
For example, the historical locations corresponding to the category label a include POI _ a1, POI _ a2, …, and POI _ aM1, the predetermined flow parameter corresponding to the category label a is Pa, and the historical location number ma in the abnormal location set is f (Pa × M1). The historical positions corresponding to the category label B comprise POI _ B1, POI _ B2, … and POI _ bM2, the predetermined flow parameter corresponding to the category label a is Pb, and the historical position number mb in the abnormal position set is f (Pb M2). Rounding up is adopted in the present embodiment, and ma is 3 and mb is 4. And calculating abnormal parameters of the historical positions POI _ a1, POI _ a2, … and POI _ aM1, and sorting the historical positions POI _ a1, POI _ a2, … and POI _ aM1 from small to large according to the abnormal parameters, wherein the sorting result is that the POI _ a3, the POI _ a1, the POI _ a2, the POI _ aM1 and … show that the abnormal position set corresponding to the category label A is { POI _ a3, POI _ a1 and POI _ a2 }. And calculating abnormal parameters of the historical positions POI _ B1, POI _ B2, … and POI _ bM2, and sorting the historical positions POI _ B1, POI _ B2, … and POI _ bM2 from small to large according to the abnormal parameters, wherein the sorting result is that the abnormal position sets corresponding to the category label B are { POI _ B2, POI _ B1, POI _ B3 and POI _ B4} if the sorting result is that the POI _ B2, the POI _ B1, the POI _ B3, the POI _ B4 and the POI _ bM …. Assuming that the target position is POI _ a3, the target position is located in the abnormal position set corresponding to the category label a, and the target position satisfies the predetermined condition.
In another optional implementation manner, step S340 may specifically include: in response to detecting that the target position is located in the abnormal position set and the abnormal parameter corresponding to the target position is greater than or equal to the corresponding parameter threshold, determining that the target position meets the predetermined condition. Therefore, in the embodiment, the position of the target position in the abnormal parameter sorting result and the preset parameter threshold are simultaneously referred to determine whether the target task terminal sends the multiple recommendation points, so that the positioning accuracy of the target position needing the multiple recommendation points is further improved, the user without the multiple recommendation points is prevented from being disturbed, and the user experience is further improved.
In another optional implementation manner, each historical location has a corresponding category label, and step S340 may specifically include: and determining that the target position meets a preset condition in response to the fact that the target position is detected to be located in the abnormal position set corresponding to the class label to which the target position belongs and the abnormal parameter corresponding to the target position is larger than or equal to a preset parameter threshold value. Therefore, the positioning accuracy of the target position needing multiple recommendation points can be further improved, the disturbance of the user without the multiple recommendation points is avoided, and the user experience is further improved.
In another optional implementation manner, each historical location has a corresponding category label, and step S340 may specifically include: and in response to the fact that the target position is detected to be located in the corresponding abnormal position set, and the abnormal parameter corresponding to the target position is larger than or equal to the parameter threshold corresponding to the class label to which the target position belongs, determining that the target position meets the preset condition. Therefore, the positioning accuracy of the target position needing multiple recommendation points can be further improved, the disturbance of the user without the multiple recommendation points is avoided, and the user experience is further improved.
In another optional implementation manner, each historical location has a corresponding category label, and step S340 may specifically include: and determining that the target position meets a preset condition in response to the fact that the target position is detected to be located in the abnormal position set corresponding to the class label to which the target position belongs and the abnormal parameter corresponding to the target position is larger than or equal to the parameter threshold corresponding to the class label to which the target position belongs. Therefore, the positioning accuracy of the target position needing multiple recommendation points can be further improved, the disturbance of the user without the multiple recommendation points is avoided, and the user experience is further improved.
It should be understood that, in this embodiment, whether the target position satisfies the predetermined condition may be determined in real time after the target position is acquired based on any implementation manner described above, abnormality parameters of each historical position (for example, each POI) may also be determined in advance, whether the target position satisfies the predetermined condition may also be determined in real time by using any implementation manner described above based on the acquired abnormality parameters of the target position, an abnormal position set that needs to push a plurality of recommendation points may also be determined in advance based on any implementation manner described above, and whether the predetermined condition is satisfied is determined by determining whether the target position is located in the abnormal position set after the target position is acquired, which is not limited in this embodiment.
In an optional implementation manner, the location recommendation method according to the embodiment of the present invention further includes:
and responding to the detected target position not meeting the preset condition, acquiring a target recommendation point, and pushing the target recommendation point to a target user terminal and/or a task execution terminal. Therefore, when the road condition of the target position is simple or the target position has a basically fixed parking position, the target user with the target recommendation point is prevented from being disturbed, unnecessary operation burden is brought to the target user, and the user experience is improved.
In an optional implementation manner, the location recommendation method according to the embodiment of the present invention further includes: and responding to the fact that the target user terminal is pre-bound with the corresponding target recommendation point, and pushing the target recommendation point to the target user terminal. For example, in the field of online taxi appointment, in the historical task record of the target user, the taxi position is basically fixed, or the ratio of taxies on the same position is greater than or equal to a threshold value, the position is determined as the target recommendation point corresponding to the target user terminal. Therefore, the target user with the target recommendation point can be further prevented from being disturbed, unnecessary operation burden is brought to the target user, and the user experience is improved.
In another optional implementation manner, the position recommendation method according to the embodiment of the present invention further includes: and receiving a target recommendation point sent by the target user terminal, and sending the target recommendation point to the target task execution end.
Fig. 5 and 6 are interface diagrams of a target user terminal according to an embodiment of the present invention. FIG. 7 is a schematic interface diagram of a target task execution end according to an embodiment of the present invention. In this embodiment, after it is determined that the target position meets the predetermined condition, the acquired plurality of recommendation points are pushed to the target user terminal for interface display. As shown in fig. 5, in the target user terminal interface 5, the target position is 51, and the plurality of recommendation points include a recommendation point 52 and a recommendation point 53. In response to detecting that the target recommendation point selected by the user is the recommendation point 53, for example, by touching the recommendation point 53 in the interface 5 for selection, the user terminal interface is controlled to display only the target recommendation point 53 selected by the user, as shown in fig. 6, and at the same time, the coordinate information of the target recommendation point 53 selected by the user is sent to the server.
In this embodiment, the server receives the target recommendation point 53 sent by the target user terminal, sends the target recommendation point 53 to the target task execution end, and the target task execution end displays the target recommendation point 53 on its interface 7, as shown in fig. 7.
It should be appreciated that the interface displays of fig. 5-7 are merely exemplary and do not characterize the interface displays of the target user terminal and the task execution end in a particular application scenario.
Fig. 8 is a schematic diagram of a position recommendation device according to an embodiment of the present invention. As shown in fig. 8, the position recommendation device 8 of the embodiment of the present invention includes an information acquisition unit 81, a recommendation point acquisition unit 82, and a push unit 83.
The information acquiring unit 81 is configured to acquire target task information including a target position, which is a target start address or a target reached address. The recommended point acquisition unit 82 is configured to acquire a plurality of recommended points in response to detecting that the target position satisfies a predetermined condition. The pushing unit 83 is configured to push a plurality of recommendation points to the target user terminal so that the target user determines the target recommendation point. The preset condition satisfaction state of the target position is determined according to the abnormal parameter corresponding to the target position, and the abnormal parameter is used for representing the historical task proportion that the historical recommendation point corresponding to the target position does not meet the preset requirement.
In an alternative implementation manner, the position recommending device 8 further includes a first state determining unit, and the first state determining unit includes a first parameter acquiring subunit and a first state determining subunit. The first parameter acquiring subunit is configured to acquire an abnormal parameter corresponding to the target position. The first state determination subunit is configured to determine that the target position satisfies the predetermined condition in response to detecting that the anomaly parameter is greater than or equal to a corresponding parameter threshold.
In an optional implementation, the target location has a corresponding category label with a corresponding parameter threshold, and the first state determining subunit is further configured to determine that the target location satisfies the predetermined condition in response to detecting that the abnormal parameter is greater than or equal to the parameter threshold corresponding to the category label to which the target location belongs.
In an optional implementation manner, the position recommending apparatus 8 further includes a second state determining unit, where the second state determining unit includes a second parameter obtaining subunit, a sorting subunit, an abnormal position set determining subunit, and a second state determining subunit.
The second parameter acquiring subunit is configured to acquire abnormal parameters corresponding to the history positions corresponding to the plurality of history tasks respectively. And the sorting subunit is configured to sort the historical positions according to the abnormal parameters of the historical positions. And the abnormal position set determining subunit is configured to determine an abnormal position set based on the sequencing result and corresponding predetermined flow, wherein the predetermined flow represents the ratio of the historical position number to the historical position total number in the abnormal position set. A second state determination subunit configured to determine that the target position satisfies the predetermined condition at least according to a relationship between the target position and the abnormal position set.
In an alternative implementation, each of the historical locations has a corresponding category label. The sorting subunit includes a sorting module. The sorting module is configured to sort the historical positions belonging to the same category label according to the abnormal parameters of the historical positions, and obtain sorting results corresponding to the category labels.
In an optional implementation manner, each of the category labels has a corresponding predetermined traffic, and the abnormal position set determining subunit is further configured to determine the abnormal position set of each category label based on the sorting result corresponding to each category label and the predetermined traffic parameter corresponding to each category label.
In an alternative implementation, the second state determination subunit includes a first state determination module. A first state determination module configured to determine that the target location satisfies the predetermined condition in response to detecting that the target location is in the set of abnormal locations.
In an alternative implementation, the second state determining subunit includes a second state determining module. The second state determination module is configured to determine that the target position satisfies the predetermined condition in response to detecting that the target position is in the abnormal position set and that an abnormal parameter corresponding to the target position is greater than or equal to a corresponding parameter threshold.
In an optional implementation manner, the first parameter obtaining subunit includes a historical task set determining module, a cost parameter determining module, and a parameter determining module. The historical task set determining module is configured to obtain a target historical task set corresponding to the target position. The cost parameter determination module is configured to determine a cost parameter of each of the target historical tasks according to the recommended point of the target position corresponding to each of the target historical tasks. The parameter determination module is configured to calculate a ratio of the number of target historical tasks of which the cost parameter is greater than or equal to a cost threshold value to the total number of target historical tasks in the historical task set so as to determine an abnormal parameter corresponding to the target position.
In an alternative implementation, the position recommendation device 8 further comprises a second pushing unit. The second pushing unit is configured to respond to the target user terminal being pre-bound with the corresponding target recommendation point, and push the target recommendation point to the target user terminal.
In an alternative implementation, the position recommendation device 8 further includes a receiving unit and a transmitting unit. And the receiving unit is configured to receive the target recommendation point sent by the target user terminal. And the sending unit is configured to send the target recommendation point to a target task execution end.
The method and the device for determining the target recommendation point of the target user terminal acquire the target task information comprising the target position, respond to the fact that the target position meets the preset conditions, acquire the plurality of recommendation points, and push the plurality of recommendation points to the target user terminal so that the target user can determine the target recommendation point, wherein the preset conditions meeting state of the target position is determined according to the abnormal parameters corresponding to the target position. Therefore, a plurality of recommendation points can be provided for the target user terminal for selection aiming at a more complex target position, so that the target recommendation points can better meet the user requirements.
Fig. 9 is a schematic diagram of an electronic device of an embodiment of the invention. As shown in fig. 9, the electronic device 9 is a general-purpose data processing apparatus comprising a general-purpose computer hardware structure including at least a processor 91 and a memory 92. The processor 91 and the memory 92 are connected by a bus 93. The memory 92 is adapted to store instructions or programs executable by the processor 91. The processor 91 may be a stand-alone microprocessor or may be a collection of one or more microprocessors. Thus, the processor 91 implements the processing of data and the control of other devices by executing instructions stored by the memory 92 to perform the method flows of embodiments of the present invention as described above. The bus 93 connects the above components together, and also connects the above components to a display controller 94 and a display device and an input/output (I/O) device 95. Input/output (I/O) devices 95 may be a mouse, keyboard, modem, network interface, touch input device, motion sensing input device, printer, and other devices known in the art. Typically, the input/output devices 95 are coupled to the system through an input/output (I/O) controller 96.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, apparatus (device) or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may employ a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations of methods, apparatus (devices) and computer program products according to embodiments of the application. It will be understood that each flow in the flow diagrams can be implemented by computer program instructions.
These computer program instructions may 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.
These computer program instructions may also be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows.
Another embodiment of the invention relates to a computer program product for causing a computer to perform some or all of the above method embodiments when the computer program product runs on a computer.
Another embodiment of the invention is directed to a non-transitory storage medium storing a computer-readable program for causing a computer to perform some or all of the above-described method embodiments.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be accomplished by specifying the relevant hardware through a program, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The embodiment of the invention discloses a TS1 and a position recommendation method, wherein the method comprises the following steps:
acquiring target task information, wherein the target task information comprises a target position;
in response to detecting that the target position meets a predetermined condition, acquiring a plurality of recommendation points;
pushing a plurality of recommendation points to a target user terminal so that a target user determines a target recommendation point;
the preset condition satisfaction state of the target position is determined according to the abnormal parameter corresponding to the target position, and the abnormal parameter is used for representing the historical task proportion that the historical recommendation point corresponding to the target position does not meet the preset requirement.
TS2, the method according to TS1, wherein the step of determining that the predetermined condition of the target location satisfies the status comprises:
acquiring abnormal parameters corresponding to the target position;
in response to detecting that the anomaly parameter is greater than or equal to a corresponding parameter threshold, determining that the target location satisfies the predetermined condition.
TS3, the method of TS2, the target location having a corresponding category label with a corresponding parameter threshold;
in response to detecting that the anomaly parameter is greater than or equal to a corresponding parameter threshold, determining that the target location satisfies the predetermined condition comprises:
and determining that the target position meets the predetermined condition in response to detecting that the abnormal parameter is greater than or equal to a parameter threshold corresponding to a class label to which the target position belongs.
TS4, the method according to TS1, wherein the step of determining that the predetermined condition of the target location satisfies the status comprises:
acquiring abnormal parameters of historical positions corresponding to a plurality of historical tasks;
sorting each historical position according to the abnormal parameters of each historical position;
determining an abnormal position set based on the sequencing result and a corresponding preset flow parameter, wherein the preset flow parameter represents the ratio of the number of the historical positions in the abnormal position set to the total number of the historical positions;
and determining that the target position meets the preset condition at least according to the relation between the target position and the abnormal position set.
TS5, each of the historical locations having a corresponding category label according to the method of TS 4;
sorting each historical position according to the abnormal parameter of each historical position comprises:
and respectively sequencing the historical positions belonging to the same class label according to the abnormal parameters of the historical positions, and acquiring the sequencing result corresponding to each class label.
TS6, each of said category labels having a corresponding predetermined flow parameter according to the method of TS 5;
determining the set of abnormal locations based on the ranking results and the corresponding predetermined flow parameters comprises:
and determining an abnormal position set of each class label based on the sorting result corresponding to each class label and the preset flow parameter corresponding to each class label.
TS7, the method of any one of TS4-TS6, wherein determining that the target position satisfies the predetermined condition based at least on a relationship of the target position to the set of abnormal positions comprises:
in response to detecting that the target location is in the set of abnormal locations, determining that the target location satisfies the predetermined condition.
TS8, the method of any one of TS4-TS6, wherein determining that the target position satisfies the predetermined condition based at least on a relationship of the target position to the set of abnormal positions comprises:
in response to detecting that the target position is located in the abnormal position set and an abnormal parameter corresponding to the target position is greater than or equal to a corresponding parameter threshold, determining that the target position meets the predetermined condition.
TS9, according to the method of TS2, obtaining the abnormal parameter corresponding to the target position includes:
acquiring a target historical task set corresponding to the target position;
determining a cost parameter of each target historical task according to the target position and a recommendation point corresponding to each target historical task;
and calculating the ratio of the number of the target historical tasks with the cost parameter being greater than or equal to a cost threshold value to the total number of the target historical tasks in the historical task set to obtain an abnormal parameter corresponding to the target position.
TS10, the method of TS1, the method further comprising:
and responding to the fact that the target user terminal is pre-bound with the corresponding target recommendation point, and pushing the target recommendation point to the target user terminal.
TS11, the method of TS1, the method further comprising:
receiving a target recommendation point sent by the target user terminal;
and sending the target recommendation point to a target task execution end.
The embodiment of the invention discloses TS12 and a position recommending device, wherein the device comprises:
the information acquisition unit is configured to acquire target task information, wherein the target task information comprises a target position, and the target position is a target starting address or a target reaching address;
a recommended point acquisition unit configured to acquire a plurality of recommended points in response to detection that the target position satisfies a predetermined condition;
the first pushing unit is configured to push a plurality of recommendation points to a target user terminal so that a target user determines a target recommendation point;
the preset condition satisfaction state of the target position is determined according to the abnormal parameter corresponding to the target position, and the abnormal parameter is used for representing the historical task proportion that the historical recommendation point corresponding to the target position does not meet the preset requirement.
TS13, the apparatus of TS12, the apparatus further comprising a first state determining unit comprising:
a first parameter obtaining subunit, configured to obtain an abnormal parameter corresponding to the target position;
a first state determination subunit configured to determine that the target position satisfies the predetermined condition in response to detecting that the anomaly parameter is greater than or equal to a corresponding parameter threshold.
TS14, the apparatus of TS13, the target location having a corresponding category label with a corresponding parameter threshold;
the first state determination subunit is further configured to determine that the target position satisfies the predetermined condition in response to detecting that the abnormal parameter is greater than or equal to a parameter threshold corresponding to a category tag to which the target position belongs.
TS15, the apparatus according to TS12, the apparatus further comprising a second state determining unit comprising:
a second parameter obtaining subunit, configured to obtain abnormal parameters of history positions corresponding to the plurality of history tasks;
a sorting subunit configured to sort each of the historical positions according to the abnormality parameter of each of the historical positions;
an abnormal position set determining subunit, configured to determine an abnormal position set based on the sorting result and a corresponding predetermined traffic parameter, where the predetermined traffic parameter represents a ratio of the number of historical positions to the total number of historical positions in the abnormal position set;
a second state determination subunit configured to determine that the target position satisfies the predetermined condition at least according to a relationship between the target position and the abnormal position set.
TS16, the apparatus of TS15, each of the historical locations having a corresponding category label;
the sorting subunit includes:
and the sorting module is configured to sort the historical positions belonging to the same category label according to the abnormal parameters of the historical positions and obtain sorting results corresponding to the category labels.
TS17, the apparatus of TS16, each said category label having a corresponding predetermined flow parameter;
the abnormal position set determining subunit is further configured to determine an abnormal position set of each category label based on the sorting result corresponding to each category label and the predetermined flow parameter corresponding to each category label.
TS18, the apparatus according to any one of TS15-TS17, the second state determining subunit comprising:
a first state determination module configured to determine that the target location satisfies the predetermined condition in response to detecting that the target location is in the set of abnormal locations.
TS19, the apparatus according to any one of TS15-TS17, the second state determining subunit comprising:
a second state determination module configured to determine that the target location satisfies the predetermined condition in response to detecting that the target location is in the abnormal location set and that an abnormal parameter corresponding to the target location is greater than or equal to a corresponding parameter threshold.
TS20, the apparatus of TS13, the first parameter obtaining subunit comprising:
a historical task set determining module configured to obtain a target historical task set corresponding to the target position;
a cost parameter determination module configured to determine a cost parameter of each of the target historical tasks according to the target position and a recommendation point corresponding to each of the target historical tasks;
and the parameter determination module is configured to calculate a ratio of the number of target historical tasks of which the cost parameter is greater than or equal to a cost threshold value to the total number of target historical tasks in the historical task set to obtain an abnormal parameter corresponding to the target position.
TS21, the apparatus of TS12, the apparatus further comprising:
the second pushing unit is configured to respond to the fact that the target user terminal is detected to be pre-bound with the corresponding target recommendation point, and push the target recommendation point to the target user terminal.
TS22, the apparatus of TS12, the apparatus further comprising:
a receiving unit configured to receive a target recommendation point transmitted by the target user terminal;
and the sending unit is configured to send the target recommendation point to a target task execution end.
An embodiment of the invention discloses a TS23, an electronic device, comprising a memory and a processor, the memory for storing one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of TS1-TS 11.
The embodiment of the invention discloses a TS24 and a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and when the computer program is executed by a processor, the method of any one of TS1-TS11 is realized.
The embodiment of the invention discloses a TS25 and a computer program product, which is characterized in that when the computer program product runs on a computer, the computer is caused to execute the method as set forth in any one of TS1-TS 11.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for location recommendation, the method comprising:
acquiring target task information, wherein the target task information comprises a target position;
in response to detecting that the target position meets a predetermined condition, acquiring a plurality of recommendation points;
pushing a plurality of recommendation points to a target user terminal so that a target user determines a target recommendation point;
the preset condition satisfaction state of the target position is determined according to the abnormal parameter corresponding to the target position, and the abnormal parameter is used for representing the historical task proportion that the historical recommendation point corresponding to the target position does not meet the preset requirement.
2. The method according to claim 1, wherein the step of determining that the predetermined condition of the target position satisfies the status comprises:
acquiring abnormal parameters of historical positions corresponding to a plurality of historical tasks;
sorting each historical position according to the abnormal parameters of each historical position;
determining an abnormal position set based on the sequencing result and a corresponding preset flow parameter, wherein the preset flow parameter represents the ratio of the number of the historical positions in the abnormal position set to the total number of the historical positions;
and determining that the target position meets the preset condition at least according to the relation between the target position and the abnormal position set.
3. The method of claim 2, wherein each of the historical locations has a corresponding category label;
sorting each historical position according to the abnormal parameter of each historical position comprises:
and respectively sequencing the historical positions belonging to the same class label according to the abnormal parameters of the historical positions, and acquiring the sequencing result corresponding to each class label.
4. The method of claim 3, wherein each of the category labels has a corresponding predetermined flow parameter;
determining the set of abnormal locations based on the ranking results and the corresponding predetermined flow parameters comprises:
and determining an abnormal position set of each class label based on the sorting result corresponding to each class label and the preset flow parameter corresponding to each class label.
5. The method according to any one of claims 2-4, wherein determining that the target location satisfies the predetermined condition based at least on the relationship of the target location to the set of abnormal locations comprises:
in response to detecting that the target location is in the set of abnormal locations, determining that the target location satisfies the predetermined condition.
6. The method according to any one of claims 2-4, wherein determining that the target location satisfies the predetermined condition based at least on the relationship of the target location to the set of abnormal locations comprises:
in response to detecting that the target position is located in the abnormal position set and an abnormal parameter corresponding to the target position is greater than or equal to a corresponding parameter threshold, determining that the target position meets the predetermined condition.
7. A location recommendation device, the device comprising:
the information acquisition unit is configured to acquire target task information, wherein the target task information comprises a target position, and the target position is a target starting address or a target reaching address;
a recommended point acquisition unit configured to acquire a plurality of recommended points in response to detection that the target position satisfies a predetermined condition;
the first pushing unit is configured to push a plurality of recommendation points to a target user terminal so that a target user determines a target recommendation point;
the preset condition satisfaction state of the target position is determined according to the abnormal parameter corresponding to the target position, and the abnormal parameter is used for representing the historical task proportion that the historical recommendation point corresponding to the target position does not meet the preset requirement.
8. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method of any of claims 1-6.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 6.
10. A computer program product, characterized in that, when the computer program product is run on a computer, it causes the computer to perform the method according to any of claims 1-6.
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