CN113283628A - Information recommendation method and device, electronic equipment and readable storage medium - Google Patents
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Abstract
The embodiment of the disclosure provides an information recommendation method, an information recommendation device, an electronic device and a readable storage medium, wherein the method comprises the following steps: receiving a target order of a user terminal, wherein the target order comprises a target vehicle type combination; calculating the estimated order receiving time of each vehicle type in the target vehicle type combination; determining at least two time sub-barrels according to the estimated order receiving duration of each vehicle type, and estimating the order receiving probability of each vehicle type in each time sub-barrel; determining the estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket; and generating recommendation information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination. The embodiment of the disclosure determines the estimated order receiving time of the whole target vehicle type combination, generates the recommendation information based on the estimated order receiving time of the target vehicle type combination, and improves the accuracy of the estimated order receiving time and the effectiveness of the generated recommendation information.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of computer processing, and in particular relates to an information recommendation method and device, an electronic device and a readable storage medium.
Background
With the rapid development of the internet industry, more and more users prefer to use taxi-taking software to take taxi. In general, after receiving a taxi taking order sent by a user terminal, a taxi taking platform pre-estimates the pre-estimated order receiving time of each taxi type selected by a user according to the supply and demand characteristics of each taxi type in the current time period, and informs the user of the pre-estimated order receiving time of each taxi type.
However, for a single vehicle model, the number of available vehicles in the area where the user is located is limited in a certain period of time, and even during a rush hour of driving, there is a case where there is no certain vehicle model available in the area. According to the method for calculating the estimated waiting time according to a single vehicle type, the accuracy of a calculation result is greatly influenced by the number of vehicles in the current area, so that the estimated order receiving time length recommended to a user is inaccurate, and other recommendation information generated according to the estimated order receiving time length is also inaccurate.
Disclosure of Invention
The embodiment of the disclosure provides an information recommendation method, an information recommendation device, electronic equipment and a readable storage medium, which can solve the problems that the estimated order receiving duration is inaccurate and the recommendation information determined according to the estimated order receiving duration is also inaccurate in the prior art.
According to a first aspect of embodiments of the present disclosure, there is provided an information recommendation method, the method including:
receiving a target order of a user terminal, wherein the target order comprises a target vehicle type combination;
calculating the estimated order receiving time of each vehicle type in the target vehicle type combination;
determining at least two time sub-barrels according to the estimated order receiving duration of each vehicle type, and estimating the order receiving probability of each vehicle type in each time sub-barrel;
determining the estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket;
and generating recommendation information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination.
According to a second aspect of embodiments of the present disclosure, there is provided an information recommendation apparatus including:
the target order receiving module is used for receiving a target order of the user terminal, and the target order comprises a target vehicle type combination;
the first estimated order receiving duration calculation module is used for calculating the estimated order receiving duration of each vehicle type in the target vehicle type combination;
the order receiving probability pre-estimation module is used for determining at least two time sub-barrels according to the pre-estimated order receiving duration of each vehicle type and pre-estimating the order receiving probability of each vehicle type in each time sub-barrel;
the second pre-estimated order receiving duration calculation module is used for determining the pre-estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket;
and the recommendation information generation module is used for generating recommendation information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic apparatus including:
the information recommendation system comprises a processor, a memory and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the information recommendation method.
According to a fourth aspect of embodiments of the present disclosure, there is provided a readable storage medium, wherein instructions, when executed by a processor of an electronic device, enable the electronic device to perform the aforementioned information push recommendation method.
The embodiment of the disclosure provides an information recommendation method, an information recommendation device, an electronic device and a readable storage medium, wherein the method comprises the following steps: receiving a target order of a user terminal, wherein the target order comprises a target vehicle type combination; calculating the estimated order receiving time of each vehicle type in the target vehicle type combination; determining at least two time sub-barrels according to the estimated order receiving duration of each vehicle type, and estimating the order receiving probability of each vehicle type in each time sub-barrel; determining the estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket; and generating recommendation information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination. According to the embodiment of the recommendation method and the recommendation device, the target vehicle type combination is taken as a whole, the estimated order receiving duration of the target vehicle type combination is determined, then the recommendation information is generated based on the estimated order receiving duration of the target vehicle type combination, and compared with the prior art that the estimated order receiving duration of a single vehicle type is calculated and the recommendation information is determined according to the estimated order receiving duration of the single vehicle type, the accuracy of the estimated order receiving duration is improved, and the effectiveness of the generated recommendation information is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments of the present disclosure will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 shows a flow diagram of information recommendation method steps in one embodiment of the present disclosure;
fig. 2 shows a schematic structural diagram of an information recommendation device in an embodiment of the present disclosure;
FIG. 3 shows a block diagram of an electronic device in an embodiment of the disclosure.
Detailed Description
Technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present disclosure, belong to the protection scope of the embodiments of the present disclosure.
Example one
Referring to fig. 1, a flowchart illustrating steps of an information recommendation method in an embodiment of the present disclosure is shown, specifically as follows:
And 102, calculating the estimated order receiving time of each vehicle type in the target vehicle type combination.
And 103, determining at least two time sub-barrels according to the estimated order receiving duration of each vehicle type, and estimating the order receiving probability of each vehicle type in each time sub-barrel.
And 104, determining the estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket.
And 105, generating recommendation information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination.
The target order is generated by the user terminal according to the boarding place and the target position selected by the user and the selected target vehicle type combination. After the user selects the taxi taking journey, the user terminal can display the available vehicle type list for the user to select, determines the target vehicle type combination according to the selection operation of the user, and generates a target order after receiving the order placing instruction.
The estimated order receiving time is the estimated time between the order placing of the user and the order receiving of the driver. The time bucket is the time period in the estimated order receiving time. For example, the estimated order taking time is 1 minute, then the estimated order taking time may be divided into 4 time buckets: time sub-bucket T1, time sub-bucket T2, time sub-bucket T3, and time sub-bucket T4, wherein time sub-bucket T1 corresponds to a time period between 0s-30s, time sub-bucket T2 corresponds to a time period between 31s-60s, and so on, time sub-bucket T3 corresponds to a time period between 61s-90s, and time sub-bucket T2 corresponds to a time period between 91s-120 s. In practical application, the time sub-buckets may be divided according to actual requirements, the estimated time duration may be averagely divided into a plurality of time sub-buckets, or different time durations may be allocated to different time sub-buckets, which is not specifically limited in the embodiments of the present disclosure.
In implementations provided by the present disclosure, the target vehicle type combination includes at least one vehicle type. After receiving a target order form of a user terminal, a server pre-estimates the pre-estimated order receiving time of each vehicle type in the vehicle type combination according to the supply and demand characteristics of the vehicle in the area where the boarding place selected by the user is located, the road condition of the area, the weather and other factors, and then divides the time into barrels according to the pre-estimated order receiving time of each vehicle type. Specifically, after the estimated order receiving time of each vehicle type is obtained, the estimated order receiving time of each vehicle type is compared, the vehicle type with the maximum estimated order receiving time in the target vehicle type combination is determined, and the estimated order receiving time of the vehicle type is divided into at least two time barrels.
And after the time sub-barrels are determined, the order taking probability of each vehicle type in each time sub-barrel is estimated. Specifically, the order taking probability of a certain vehicle type in each time sub-bucket is estimated according to factors such as supply and demand characteristics, current road conditions, weather and the like of the certain vehicle type in a time period corresponding to each time sub-bucket. For example, for the order taking probability of the vehicle type s in the time bucket T1, an order taking probability prediction model of a single vehicle type can be established based on deep learning, and then information such as supply and demand characteristics, current road conditions, weather and the like of the vehicle type s in the region of the getting-on place of the target order in the time period corresponding to the time bucket T1 is input into the order taking probability prediction model of the single vehicle type, so that the order taking probability of the vehicle type s in the time bucket T1 is obtained.
The method comprises the steps of taking a target vehicle type combination as a whole, and determining the whole pre-estimated order receiving duration of the target vehicle type combination. Therefore, the information recommendation method provided by the disclosure further analyzes the estimated order receiving duration of a single vehicle type and the order receiving probability of each vehicle type in each time bucket, so as to determine the estimated order receiving duration of the target vehicle type combination. For example, the order receiving probability of each vehicle type in the target vehicle type combination in each time bucket is compared, and the time period corresponding to the time bucket of the order receiving probability is determined to be the estimated order receiving duration of the target vehicle type combination.
After the estimated order receiving duration of the target vehicle type combination is determined, the recommendation information for the target order can be generated according to the estimated order receiving duration. For example, under the condition that the estimated order receiving time exceeds a preset threshold value, other candidate vehicle types except the target vehicle type combination are recommended to the user; or, in the case that the estimated order receiving time exceeds the estimated threshold value, recommending available nearby cabin-changing vehicles to the user, and the like. Therefore, the embodiment of the present invention is not particularly limited, and the recommendation information for the target order is generated according to the estimated order receiving duration of the target vehicle type combination.
According to the embodiment provided by the disclosure, the target vehicle type combination is taken as a whole, the estimated order receiving time of the target vehicle type combination is determined, then the recommendation information is generated based on the estimated order receiving time of the target vehicle type combination, and compared with the prior art that the estimated order receiving time of a single vehicle type is calculated and the recommendation information is determined according to the estimated order receiving time of the single vehicle type, the accuracy of the estimated order receiving time can be improved, and the effectiveness of the generated recommendation information is further improved.
In an optional embodiment of the present disclosure, the determining, in step 104, an estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket includes:
and step S11, calculating the order taking probability of the target vehicle type combination in each time sub-bucket according to the order taking probability of each vehicle type in each time sub-bucket.
And step S12, sequentially comparing the order taking probability of the target vehicle type combination in each time sub-bucket with a preset probability threshold according to the time sequence of the time sub-buckets.
And step S13, if the order receiving probability of the target vehicle type combination in at least one time sub-bucket is matched with the preset probability threshold, stopping comparison, and determining the time length corresponding to the time sub-bucket as the estimated order receiving time length of the target vehicle type combination.
And for the target vehicle type combination, n vehicle types are included, and the value of n is a positive integer. Assuming that the order taking probability of the vehicle type s in the time bucket Ti is Ps, the order taking probability of the target vehicle type combination in the time bucket Ti is as follows:
respectively calculating the order receiving probability of the target vehicle type combination in each time bucket according to the formula (1), then sequentially comparing the order receiving probability of the target vehicle type combination in each time bucket with a preset probability threshold value according to the time sequence of the time buckets, namely the sequence of the time periods corresponding to the time buckets, stopping comparison as long as the order receiving probability of the target vehicle type combination in one time bucket is matched with the preset probability threshold value, namely is greater than or equal to the preset probability threshold value, and taking the time length corresponding to the time bucket as the estimated order receiving time length of the target vehicle type combination. For example, 4 time buckets are determined according to the estimated order receiving duration of each vehicle type in the target vehicle type combination: time bucket T1, time bucket T2, time bucket T3, and time bucket T4. Wherein, the order receiving probability of the target vehicle type combination in the time bucket T1 is PT1And the probability of order taking of the target vehicle type combination in the time bucket T1 is PT2And the probability of order taking of the target vehicle type combination in the time bucket T1 is PT3And the probability of order taking of the target vehicle type combination in the time bucket T1 is PT4The preset probability threshold is P. Sequentially comparing the order-meeting probability of the target vehicle type combination in each time sub-bucket with a preset probability threshold value according to the sequence from T1 to T4, and assuming PT1Less than P, PT2If the time is greater than P, the order taking probability of the target vehicle type combination in the time bucket T3 and the time bucket T4 does not need to be compared with a preset probability threshold, the duration corresponding to the time bucket T2 is directly determined to be the estimated order taking duration of the target vehicle type combination, for example, the time period between 31s and 60s corresponding to the time bucket T2, then the estimated order taking duration of the target vehicle type combination is determined to be 31s to 60s, or in order to further improve the estimation accuracy, the most corresponding to the time bucket can be usedAnd the large time is taken as the estimated order receiving time of the target vehicle type combination, and the estimated order receiving time of the target vehicle type combination is determined to be 60 s.
In an optional embodiment of the disclosure, the method further comprises:
and step S21, estimating the cabin change acceptance rate of the user according to the information of other vehicle types except the target vehicle type combination, the estimated order receiving duration of the target vehicle type combination and the historical taxi taking record of the user terminal.
Step S22, if the user cabin changing acceptance rate is larger than a preset acceptance rate threshold value, judging whether an cabin changeable vehicle matched with the target order exists, wherein the vehicle type of the cabin changeable vehicle does not belong to the target vehicle type combination.
Step S23, if the interchangeable cabin vehicle matched with the target order exists, determining a vehicle type label of the interchangeable cabin vehicle, and sending a cabin exchange inquiry message to the user terminal, wherein the cabin exchange inquiry message carries the vehicle type label of the interchangeable cabin vehicle.
And step S24, locking the interchangeable cabin vehicle and sending an order success notice to the user terminal under the condition of receiving the cabin exchange instruction sent by the user terminal, wherein the order success notice carries the vehicle identification of the interchangeable cabin vehicle.
In the embodiment provided by the disclosure, the cabin change acceptance rate of the user can be judged in the process that the user waits for the order to be taken by the driver, if the cabin change acceptance rate of the user is larger than the preset acceptance rate threshold value, the user is searched whether the cabin-changeable vehicle with the vehicle type not in the target vehicle type combination exists nearby, and if the cabin-changeable vehicle is searched, a cabin change inquiry message is sent to the user, and if a cabin change instruction is received, the cabin-changeable vehicle is locked for the user.
Specifically, the vehicle supply and demand characteristics of the area where the getting-on place is located in the target order are analyzed, and information of other vehicle types except the target vehicle type combination is determined, for example, the number of currently available vehicles of a certain vehicle type, the estimated price of the vehicle type for the target order, the distance from the getting-on place, and the like. After the information of other vehicle types is determined, the cabin change acceptance rate of the user is comprehensively estimated by combining the estimated order receiving time of the target vehicle type combination, the historical taxi taking record of the user terminal and the like. For example, the taxi taking price interval of the user is determined according to the historical taxi taking records and is compared with the estimated prices of other vehicle types, if the two are matched, and the estimated order receiving time of the target vehicle type combination exceeds the preset time threshold, the possibility that the user accepts the cabin change is estimated to be higher, namely the cabin change acceptance rate of the user is higher.
Further, in order to obtain a more accurate user cabin change acceptance rate, a user cabin change rate estimation model can be built based on a neural network model, then information of other vehicle types, estimated order receiving duration of a target vehicle type combination, historical taxi taking records of a user terminal and the like are input into the user cabin change rate estimation model to obtain the user cabin change acceptance rate, then the user cabin change acceptance rate is compared with a preset acceptance rate threshold value, and whether cabin change vehicles matched with a target order exist or not is judged under the condition that the user cabin change acceptance rate is larger than the preset acceptance rate threshold value.
And under the condition that the cabin-changeable vehicle is determined to exist, determining a vehicle type label of the cabin-changeable vehicle, wherein the vehicle type label comprises at least one of a vehicle type brand, estimated order receiving time, the number of people in line, order receiving probability and estimated price. And sending a cabin change inquiry message to the user terminal, wherein the message comprises the fact that the Liu master is willing to receive you and whether to use the vehicle, and the like, and the cabin change inquiry message carries the vehicle type tag of the cabin-changeable vehicle. A cabin change instruction sending button can be arranged in a display interface of the cabin change inquiry message, and after the user terminal receives the triggering operation of the user for the cabin change instruction sending button, a cabin change instruction is sent to the server side. The cabin change instruction sending button can be any area in a display interface of the cabin change inquiry message, and the cabin change instruction sending button can trigger the user terminal to send the cabin change instruction to the server side after receiving the triggering operation of the user. And the server locks the interchangeable cabin vehicle and sends an order sending success notice to the user terminal under the condition that the server receives the cabin exchange instruction sent by the user terminal, so that the user can directly take the adjacent interchangeable cabin vehicle without waiting for receiving an order of the candidate vehicle in the target vehicle type combination for a long time. The order sending success notice carries a vehicle type label, such as a license plate number, of the interchangeable cabin vehicle, so that a user can determine the interchangeable cabin vehicle according to the received vehicle type label.
In an optional embodiment of the present disclosure, the generating, according to the estimated order receiving duration of the target vehicle type combination in step 105, recommendation information for the target order includes:
step S31, if the estimated order receiving time of the target vehicle type combination is larger than a preset threshold, judging whether a candidate vehicle type matched with the target order exists, wherein the candidate vehicle type does not belong to the target vehicle type combination.
And step S32, if the candidate vehicle type matched with the target order exists, determining the estimated order taking duration and the order taking probability of the candidate vehicle type.
And step S33, generating a recommended vehicle type list aiming at the target order according to the estimated order taking duration and the order taking probability of the candidate vehicle type.
If the estimated order receiving time of the target vehicle type combination is larger than the preset threshold, in order to avoid the situation that a user cancels an order due to no driver receiving the order for a long time, the method and the device can judge whether a candidate vehicle type matched with the target order exists according to the vehicle supply and demand characteristics of the area where the boarding place of the target order is located. It should be noted that the candidate vehicle type does not belong to the target vehicle type combination. And if the candidate vehicle type exists, further determining the estimated order receiving duration and the order receiving probability of the candidate vehicle type, and generating a recommended vehicle type list aiming at the target order according to the estimated order receiving duration and the order receiving probability of the candidate vehicle type. For example, if the estimated order receiving time of the candidate vehicle type is judged to be smaller than the estimated order receiving time of the target vehicle type combination, and/or the order receiving probability of the candidate vehicle type is judged to be larger than the order receiving probability of the target vehicle type combination, the candidate vehicle type is added into the recommended vehicle type list. And sequencing all candidate vehicle types in the candidate vehicle type list according to the estimated order receiving duration and/or the order receiving probability of the candidate vehicle types. In addition, vehicle type labels of the candidate vehicle types, such as vehicle type brands, estimated order receiving duration, number of queuing people, order receiving probability, estimated price and the like, can be added to the candidate vehicle type list to help users make a better decision.
In an optional embodiment of the disclosure, the method further comprises:
and step S41, sending the recommended vehicle type list to the user terminal.
And step S42, receiving the target vehicle type selected in the recommended vehicle type list sent by the user terminal.
And step S43, adding the target vehicle type to the target vehicle type combination.
After the server generates a recommended vehicle type list aiming at the target order, the recommended vehicle type list is sent to the user terminal, the user terminal displays the recommended vehicle type list to the user, and the selection operation of the user aiming at the recommended vehicle type list is received. The user terminal determines a target vehicle type according to the selection operation aiming at the recommended vehicle type list, sends the target vehicle type to the server, adds the target vehicle type to a target vehicle type combination by the server, and determines an order dispatching driver based on the adjusted target vehicle type combination.
In the method and the device, when the estimated order taking duration of the target vehicle type combination is larger than the preset threshold value, the vehicle type list is recommended to the user, the target vehicle type is determined from the recommended vehicle type list according to the selection operation of the user, and the target vehicle type is added to the target vehicle type combination, so that the number of available vehicle types is increased, and the order taking probability of the target vehicle type combination is improved.
In an optional embodiment of the disclosure, the method further comprises:
step S51, if response information of a first candidate vehicle to the target order is received, estimating an order forming power of the first candidate vehicle, where a vehicle type of the first candidate vehicle belongs to the target vehicle type combination.
Step S52, if the dispatching success rate of the first candidate vehicle is less than a preset success rate threshold, determining whether response information of a second candidate vehicle to the target order is received within a preset time period, where a vehicle type of the second candidate vehicle belongs to the target vehicle type combination.
Step S53, if the response information of the second candidate vehicle is received within a preset time period, the order forming power of the second candidate vehicle is estimated.
And step S54, comparing the dispatching power of the first candidate vehicle with the dispatching power of the second candidate vehicle to obtain a comparison result.
And step S55, determining the target vehicle and the vehicle identification of the target vehicle according to the comparison result.
Step S56, sending an order successfully sending notice to the user terminal, wherein the order successfully sending notice carries the vehicle identification of the target vehicle.
When waiting for the candidate vehicle order receiving corresponding to the target vehicle type combination, if the response message of the first candidate vehicle to the target order is received, the method and the device estimate the order dispatching success rate of the first candidate vehicle before dispatching the order according to the first candidate vehicle. Specifically, the dispatching distance, the receiving route, the estimated receiving time length, the historical performance record and other information of the first candidate vehicle are determined, and the dispatching success rate of the first candidate vehicle is estimated comprehensively.
And if the dispatching success power of the first candidate vehicle is larger than or equal to the preset success rate threshold, locking the first candidate vehicle, and generating a dispatching success notice according to the first candidate vehicle type. And if the order forming power of the first candidate vehicle is smaller than the preset success rate threshold, continuously judging whether a second candidate vehicle responds to the target order within a preset time period, if so, estimating the order forming power of the second candidate vehicle, comparing the order forming power with the order forming power of the first candidate vehicle, taking the maximum value of the two, and determining the candidate vehicle corresponding to the maximum value as the target vehicle. For example, the dispatch power of the first candidate vehicle is S1, the dispatch power of the second candidate vehicle is S2, and if S1 is greater than or equal to S2, the first candidate vehicle is determined to be the target vehicle; and if the S1 is smaller than the S2, determining the second candidate vehicle as the target vehicle, determining the candidate vehicle with the highest dispatching success rate as the target vehicle within the preset time, and increasing the dispatching success rate.
After the target vehicle is determined, further determining a vehicle identifier of the target vehicle, such as a license plate number, a vehicle type, a color and the like, and sending an order success notification carrying the vehicle identifier of the target vehicle to the user terminal, so that the user can identify the target vehicle according to the order success notification received by the user terminal.
It should be noted that, in the present disclosure, information transmission between the server and the user terminal may be directly based on a communication link between the server and the user terminal, or a Computer Assisted Personal access (CAPI) may transmit a message of the server to the user terminal, so as to improve data transmission efficiency and ensure validity and integrity of transmitted data. In this regard, the present disclosure is not particularly limited.
In an optional embodiment of the disclosure, the method further comprises:
and generating prompt information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination, wherein the prompt information comprises at least one of order receiving countdown, estimated order receiving time period and order receiving probability.
In the embodiment provided by the disclosure, in addition to generating the recommendation information according to the estimated order taking duration of the target vehicle type combination, prompt information for a target order can be generated, such as order taking countdown, estimated order taking time period, order taking probability and the like, so that a user can conveniently arrange waiting time. And different prompt messages can be generated according to the estimated order receiving duration of the target vehicle type combination. For example, if the estimated order receiving duration of the target vehicle type combination is smaller than a first threshold, if the estimated order receiving duration is 30s, an order receiving countdown which is decreased in seconds is generated; and if the estimated order receiving time of the target vehicle type combination is greater than the first threshold and less than or equal to the second threshold, if the estimated order receiving time t is less than or equal to 5 minutes after 30 seconds, displaying the order receiving countdown which is decreased by minutes, and the like.
In summary, the embodiments of the present disclosure provide an information recommendation method, where a target vehicle type combination is taken as a whole, an estimated order pickup duration of the target vehicle type combination is determined, and then recommendation information is generated based on the estimated order pickup duration of the target vehicle type combination, and compared with the prior art in which the estimated order pickup duration of a single vehicle type is calculated and the recommendation information is determined according to the estimated order pickup duration of a single vehicle type, the embodiments of the present disclosure improve accuracy of the estimated order pickup duration, and further improve effectiveness of the generated recommendation information.
Example two
Referring to fig. 2, a block diagram of an information recommendation apparatus in an embodiment of the present disclosure is shown, specifically as follows:
a target order receiving module 201, configured to receive a target order of a user terminal, where the target order includes a target vehicle type combination;
a first estimated order receiving duration calculation module 202, configured to calculate an estimated order receiving duration of each vehicle type in the target vehicle type combination;
the order receiving probability pre-estimating module 203 is used for determining at least two time sub-barrels according to the pre-estimated order receiving duration of each vehicle type and pre-estimating the order receiving probability of each vehicle type in each time sub-barrel;
a second estimated order receiving duration calculation module 204, configured to determine an estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket;
and the recommendation information generating module 205 is configured to generate recommendation information for the target order according to the estimated order pickup duration of the target vehicle type combination.
In an optional embodiment of the present disclosure, the second predicted order receiving duration calculating module 204 includes:
the order taking probability calculation submodule is used for calculating the order taking probability of the target vehicle type combination in each time sub-bucket according to the order taking probability of each vehicle type in each time sub-bucket;
the order taking probability comparison submodule is used for sequentially comparing the order taking probability of the target vehicle type combination in each time sub-bucket with a preset probability threshold according to the time sequence of the time sub-buckets;
and the pre-estimated order receiving duration determining submodule is used for stopping comparison if the order receiving probability of the target vehicle type combination in at least one time sub-bucket is matched with the preset probability threshold value, and determining the duration corresponding to the time sub-bucket as the pre-estimated order receiving duration of the target vehicle type combination.
In an optional embodiment of the disclosure, the apparatus further comprises:
the user cabin change acceptance rate pre-estimating module is used for pre-estimating the user cabin change acceptance rate according to the information of other vehicle types except the target vehicle type combination, the pre-estimated order receiving duration of the target vehicle type combination and the historical taxi taking record of the user terminal;
the interchangeable cabin vehicle judging module is used for judging whether an interchangeable cabin vehicle matched with the target order exists or not if the user cabin exchange acceptance rate is larger than a preset acceptance rate threshold value, and the vehicle type of the interchangeable cabin vehicle does not belong to the target vehicle type combination;
the cabin change inquiry message sending module is used for determining a vehicle type label of the cabin change vehicle and sending a cabin change inquiry message to the user terminal if the cabin change vehicle matched with the target order exists, wherein the cabin change inquiry message carries the vehicle type label of the cabin change vehicle;
and the cabin change determining module is used for locking the cabin changeable vehicle and sending an order success notice to the user terminal under the condition of receiving a cabin change instruction sent by the user terminal, wherein the order success notice carries the vehicle identification of the cabin changeable vehicle.
In an optional embodiment of the present disclosure, the vehicle type tag includes at least one of a vehicle type brand, an estimated order receiving time, a number of people in line, an order receiving probability, and an estimated price.
In an optional embodiment of the present disclosure, the recommendation information generating module 205 includes:
the candidate vehicle type judging module is used for judging whether a candidate vehicle type matched with the target order exists or not if the estimated order receiving time of the target vehicle type combination is larger than a preset threshold value, wherein the candidate vehicle type does not belong to the target vehicle type combination;
the order receiving information determining module is used for determining the estimated order receiving duration and the order receiving probability of the candidate vehicle type if the candidate vehicle type matched with the target order exists;
and the recommended vehicle type list generating module is used for generating a recommended vehicle type list aiming at the target order according to the estimated order receiving duration and the order receiving probability of the candidate vehicle type.
In an optional embodiment of the disclosure, the apparatus further comprises:
the recommended vehicle type list sending module is used for sending the recommended vehicle type list to the user terminal;
the target vehicle type receiving module is used for receiving a target vehicle type selected from the recommended vehicle type list and sent by the user terminal;
and the target vehicle type adding module is used for adding the target vehicle type into the target vehicle type combination.
In an optional embodiment of the disclosure, the apparatus further comprises:
the first order forming power estimation module is used for estimating the order forming power of a first candidate vehicle if response information of the first candidate vehicle to the target order is received, wherein the vehicle type of the first candidate vehicle belongs to the target vehicle type combination;
a second candidate vehicle determination module, configured to determine whether response information of a second candidate vehicle to the target order is received within a preset time period if the order dispatching success rate of the first candidate vehicle is smaller than a preset success rate threshold, where a vehicle type of the second candidate vehicle belongs to the target vehicle type combination;
the second order component power estimation module is used for estimating the order component power of the second candidate vehicle if the response information of the second candidate vehicle is received within a preset time period;
the dispatching power comparison module is used for comparing the dispatching power of the first candidate vehicle with the dispatching power of the second candidate vehicle to obtain a comparison result;
the target vehicle determining module is used for determining a target vehicle and a vehicle identifier of the target vehicle according to the comparison result;
and the order notification sending module is used for sending an order success notification to the user terminal, wherein the order success notification carries the vehicle identifier of the target vehicle.
In an optional embodiment of the disclosure, the apparatus further comprises:
and the prompt information generation module is used for generating prompt information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination, wherein the prompt information comprises at least one of order receiving countdown, estimated order receiving time period and order receiving probability.
In summary, the embodiments of the present disclosure provide an information recommendation apparatus, where a target vehicle type combination is taken as a whole, an estimated order pickup duration of the target vehicle type combination is determined, and then recommendation information is generated based on the estimated order pickup duration of the target vehicle type combination, and compared with the prior art in which the estimated order pickup duration of a single vehicle type is calculated and the recommendation information is determined according to the estimated order pickup duration of a single vehicle type, the accuracy of the estimated order pickup duration is improved in the embodiments of the present disclosure, and further, the effectiveness of the generated recommendation information is improved.
The second embodiment is an embodiment of the apparatus corresponding to the first embodiment, and the detailed description may refer to the first embodiment, which is not repeated herein.
An embodiment of the present disclosure also provides an electronic device, referring to fig. 3, including: a processor 301, a memory 302 and a computer program 3021 stored on the memory 302 and executable on the processor, the processor 301 implementing the information recommendation method of the foregoing embodiments when executing the program.
Embodiments of the present disclosure also provide a readable storage medium, and instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the information recommendation method of the foregoing embodiments.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. In addition, embodiments of the present disclosure are not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the embodiments of the present disclosure as described herein, and any descriptions of specific languages are provided above to disclose the best modes of the embodiments of the present disclosure.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the disclosure may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the disclosure, various features of the embodiments of the disclosure are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that is, claimed embodiments of the disclosure require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of an embodiment of this disclosure.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
The various component embodiments of the disclosure may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in a document processing apparatus according to embodiments of the present disclosure. Embodiments of the present disclosure may also be implemented as an apparatus or device program for performing a portion or all of the methods described herein. Such programs implementing embodiments of the present disclosure may be stored on a computer readable medium or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit embodiments of the disclosure, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Embodiments of the disclosure may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The above description is only for the purpose of illustrating the preferred embodiments of the present disclosure and is not to be construed as limiting the embodiments of the present disclosure, and any modifications, equivalents, improvements and the like that are made within the spirit and principle of the embodiments of the present disclosure are intended to be included within the scope of the embodiments of the present disclosure.
The above description is only a specific implementation of the embodiments of the present disclosure, but the scope of the embodiments of the present disclosure is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the embodiments of the present disclosure, and all the changes or substitutions should be covered by the scope of the embodiments of the present disclosure. Therefore, the protection scope of the embodiments of the present disclosure shall be subject to the protection scope of the claims.
Claims (18)
1. An information recommendation method, characterized in that the method comprises:
receiving a target order of a user terminal, wherein the target order comprises a target vehicle type combination;
calculating the estimated order receiving time of each vehicle type in the target vehicle type combination;
determining at least two time sub-barrels according to the estimated order receiving duration of each vehicle type, and estimating the order receiving probability of each vehicle type in each time sub-barrel;
determining the estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket;
and generating recommendation information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination.
2. The method of claim 1, wherein the determining the estimated order taking duration of the target vehicle type combination according to the order taking probability of each vehicle type in each time bucket comprises:
calculating the order receiving probability of the target vehicle type combination in each time sub-bucket according to the order receiving probability of each vehicle type in each time sub-bucket;
sequentially comparing the order receiving probability of the target vehicle type combination in each time sub-bucket with a preset probability threshold according to the time sequence of the time sub-buckets;
and if the order receiving probability of the target vehicle type combination in at least one time sub-bucket is matched with the preset probability threshold, stopping comparison, and determining the time length corresponding to the time sub-bucket as the estimated order receiving time length of the target vehicle type combination.
3. The method of claim 1, further comprising:
estimating the cabin change acceptance rate of the user according to the information of other vehicle types except the target vehicle type combination, the estimated order receiving duration of the target vehicle type combination and the historical taxi taking record of the user terminal;
if the user cabin changing acceptance rate is larger than a preset acceptance rate threshold value, judging whether an cabin changeable vehicle matched with the target order exists or not, wherein the vehicle type of the cabin changeable vehicle does not belong to the target vehicle type combination;
if the interchangeable cabin vehicle matched with the target order exists, determining a vehicle type label of the interchangeable cabin vehicle, and sending an exchange cabin inquiry message to the user terminal, wherein the exchange cabin inquiry message carries the vehicle type label of the interchangeable cabin vehicle;
and under the condition of receiving a cabin changing instruction sent by the user terminal, locking the cabin changeable vehicle, and sending an order successful notification to the user terminal, wherein the order successful notification carries the vehicle identifier of the cabin changeable vehicle.
4. The method of claim 3, wherein the vehicle type tag comprises at least one of a vehicle type brand, an estimated order pickup time, a number of people in line, an order pickup probability, and an estimated price.
5. The method according to claim 1, wherein the generating recommendation information for the target order according to the estimated order taking duration of the target vehicle type combination comprises:
if the estimated order receiving time of the target vehicle type combination is larger than a preset threshold value, judging whether a candidate vehicle type matched with the target order exists or not, wherein the candidate vehicle type does not belong to the target vehicle type combination;
if the candidate vehicle type matched with the target order exists, determining the estimated order receiving duration and the order receiving probability of the candidate vehicle type;
and generating a recommended vehicle type list aiming at the target order according to the estimated order receiving duration and the order receiving probability of the candidate vehicle type.
6. The method of claim 5, further comprising:
sending the recommended vehicle type list to the user terminal;
receiving a target vehicle type selected in the recommended vehicle type list and sent by the user terminal;
adding the target vehicle type to the target vehicle type combination.
7. The method of claim 1, further comprising:
if response information of a first candidate vehicle for the target order is received, estimating the order dispatching success rate of the first candidate vehicle, wherein the vehicle type of the first candidate vehicle belongs to the target vehicle type combination;
if the order dispatching success rate of the first candidate vehicle is smaller than a preset success rate threshold, judging whether response information of a second candidate vehicle for the target order is received within a preset time period, wherein the vehicle type of the second candidate vehicle belongs to the target vehicle type combination;
if response information of the second candidate vehicle is received within a preset time period, the order dispatching success rate of the second candidate vehicle is estimated;
comparing the dispatching power of the first candidate vehicle with the dispatching power of the second candidate vehicle to obtain a comparison result;
determining a target vehicle and a vehicle identifier of the target vehicle according to the comparison result;
and sending an order sending success notification to the user terminal, wherein the order sending success notification carries the vehicle identification of the target vehicle.
8. The method of claim 1, further comprising:
and generating prompt information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination, wherein the prompt information comprises at least one of order receiving countdown, estimated order receiving time period and order receiving probability.
9. An information recommendation apparatus, characterized in that the apparatus comprises:
the target order receiving module is used for receiving a target order of the user terminal, and the target order comprises a target vehicle type combination;
the first estimated order receiving duration calculation module is used for calculating the estimated order receiving duration of each vehicle type in the target vehicle type combination;
the order receiving probability pre-estimation module is used for determining at least two time sub-barrels according to the pre-estimated order receiving duration of each vehicle type and pre-estimating the order receiving probability of each vehicle type in each time sub-barrel;
the second pre-estimated order receiving duration calculation module is used for determining the pre-estimated order receiving duration of the target vehicle type combination according to the order receiving probability of each vehicle type in each time bucket;
and the recommendation information generation module is used for generating recommendation information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination.
10. The apparatus of claim 9, wherein the second predicted order receiving duration calculating module comprises:
the order taking probability calculation submodule is used for calculating the order taking probability of the target vehicle type combination in each time sub-bucket according to the order taking probability of each vehicle type in each time sub-bucket;
the order taking probability comparison submodule is used for sequentially comparing the order taking probability of the target vehicle type combination in each time sub-bucket with a preset probability threshold according to the time sequence of the time sub-buckets;
and the pre-estimated order receiving duration determining submodule is used for stopping comparison if the order receiving probability of the target vehicle type combination in at least one time sub-bucket is matched with the preset probability threshold value, and determining the duration corresponding to the time sub-bucket as the pre-estimated order receiving duration of the target vehicle type combination.
11. The apparatus of claim 9, further comprising:
the user cabin change acceptance rate pre-estimating module is used for pre-estimating the user cabin change acceptance rate according to the information of other vehicle types except the target vehicle type combination, the pre-estimated order receiving duration of the target vehicle type combination and the historical taxi taking record of the user terminal;
the interchangeable cabin vehicle judging module is used for judging whether an interchangeable cabin vehicle matched with the target order exists or not if the user cabin exchange acceptance rate is larger than a preset acceptance rate threshold value, and the vehicle type of the interchangeable cabin vehicle does not belong to the target vehicle type combination;
the cabin change inquiry message sending module is used for determining a vehicle type label of the cabin change vehicle and sending a cabin change inquiry message to the user terminal if the cabin change vehicle matched with the target order exists, wherein the cabin change inquiry message carries the vehicle type label of the cabin change vehicle;
and the cabin change determining module is used for locking the cabin changeable vehicle and sending an order success notice to the user terminal under the condition of receiving a cabin change instruction sent by the user terminal, wherein the order success notice carries the vehicle identification of the cabin changeable vehicle.
12. The apparatus of claim 11, wherein the vehicle type tag comprises at least one of a vehicle type brand, an estimated order pickup time, a number of people in line, an order pickup probability, and an estimated price.
13. The apparatus of claim 9, wherein the recommendation information generation module comprises:
the candidate vehicle type judging module is used for judging whether a candidate vehicle type matched with the target order exists or not if the estimated order receiving time of the target vehicle type combination is larger than a preset threshold value, wherein the candidate vehicle type does not belong to the target vehicle type combination;
the order receiving information determining module is used for determining the estimated order receiving duration and the order receiving probability of the candidate vehicle type if the candidate vehicle type matched with the target order exists;
and the recommended vehicle type list generating module is used for generating a recommended vehicle type list aiming at the target order according to the estimated order receiving duration and the order receiving probability of the candidate vehicle type.
14. The apparatus of claim 13, further comprising:
the recommended vehicle type list sending module is used for sending the recommended vehicle type list to the user terminal;
the target vehicle type receiving module is used for receiving a target vehicle type selected from the recommended vehicle type list and sent by the user terminal;
and the target vehicle type adding module is used for adding the target vehicle type into the target vehicle type combination.
15. The apparatus of claim 9, further comprising:
the first order forming power estimation module is used for estimating the order forming power of a first candidate vehicle if response information of the first candidate vehicle to the target order is received, wherein the vehicle type of the first candidate vehicle belongs to the target vehicle type combination;
a second candidate vehicle determination module, configured to determine whether response information of a second candidate vehicle to the target order is received within a preset time period if the order dispatching success rate of the first candidate vehicle is smaller than a preset success rate threshold, where a vehicle type of the second candidate vehicle belongs to the target vehicle type combination;
the second order component power estimation module is used for estimating the order component power of the second candidate vehicle if the response information of the second candidate vehicle is received within a preset time period;
the dispatching power comparison module is used for comparing the dispatching power of the first candidate vehicle with the dispatching power of the second candidate vehicle to obtain a comparison result;
the target vehicle determining module is used for determining a target vehicle and a vehicle identifier of the target vehicle according to the comparison result;
and the order notification sending module is used for sending an order success notification to the user terminal, wherein the order success notification carries the vehicle identifier of the target vehicle.
16. The apparatus of claim 9, further comprising:
and the prompt information generation module is used for generating prompt information aiming at the target order according to the estimated order receiving duration of the target vehicle type combination, wherein the prompt information comprises at least one of order receiving countdown, estimated order receiving time period and order receiving probability.
17. An electronic device, comprising:
processor, memory and computer program stored on the memory and executable on the processor, characterized in that the processor implements the information recommendation method according to any one of claims 1 to 8 when executing the program.
18. A readable storage medium, characterized in that instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the information recommendation method according to any one of method claims 1 to 8.
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