CN114528498A - Information recommendation method and device, electronic equipment and storage medium - Google Patents

Information recommendation method and device, electronic equipment and storage medium Download PDF

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Publication number
CN114528498A
CN114528498A CN202111611971.6A CN202111611971A CN114528498A CN 114528498 A CN114528498 A CN 114528498A CN 202111611971 A CN202111611971 A CN 202111611971A CN 114528498 A CN114528498 A CN 114528498A
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China
Prior art keywords
user
time
departure
recommended
predicted
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Inventor
韩雅娟
裴静
郭梦丹
陈宪涛
王嘉群
徐濛
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Beijing Baidu Netcom Science and Technology Co Ltd
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Beijing Baidu Netcom Science and Technology Co Ltd
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Priority to CN202111611971.6A priority Critical patent/CN114528498A/en
Publication of CN114528498A publication Critical patent/CN114528498A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/02—Reservations, e.g. for tickets, services or events
    • G06Q50/40—

Abstract

The disclosure provides an information recommendation method and device, electronic equipment and a storage medium, and relates to the technical field of computers, in particular to the technical fields of intelligent transportation, big data technology and the like. The specific implementation scheme is as follows: acquiring historical taxi appointment data of a user and real-time taxi appointment data of a current place of the user; according to the historical car booking data and the real-time car booking data, the recommended departure time of the user from a departure place to a destination place is predicted; providing the recommended invoice time to the user.

Description

Information recommendation method and device, electronic equipment and storage medium
Technical Field
The present disclosure relates to the field of computer technology, and more particularly to the field of intelligent transportation and big data technology.
Background
Generally, when a user uses an application program to order a car, problems of difficulty in ordering the car, long waiting time for taking the car, and the like may exist, and for example, it is often difficult for the user to call the car in a rush hour, abnormal weather conditions, and the like. Therefore, selecting the appropriate car booking time is particularly important for ensuring the success rate of car booking.
At present, car booking operation is initiated actively by a user, car booking time is also determined by the user, and after the user starts car booking service, a car booking platform or a car booking application program directly carries out operation of calling a car.
Disclosure of Invention
The disclosure provides an information recommendation method, an information recommendation device, an electronic device and a storage medium.
According to an aspect of the present disclosure, there is provided an information recommendation method, including:
acquiring historical car booking data of a user and real-time car booking data of a current place of the user;
predicting recommended departure time of the user from a departure place to a destination place according to the historical taxi appointment data and the real-time taxi appointment data;
providing the recommended invoice time to the user.
According to another aspect of the present disclosure, there is provided an apparatus for information recommendation, including:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring historical car booking data of a user and real-time car booking data of a current place of the user;
the prediction unit is used for predicting recommended departure time of the user from a departure place to a destination place according to the historical car booking data and the real-time car booking data;
and the recommending unit is used for providing the recommended order issuing time for the user.
According to still another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of the aspects and any possible implementation described above.
According to yet another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the above-described aspect and any possible implementation.
According to yet another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method of the aspect and any possible implementation as described above.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a schematic diagram according to a first embodiment of the present disclosure;
FIG. 2 is a schematic diagram according to a second embodiment of the present disclosure;
FIG. 3 is a schematic diagram according to a third embodiment of the present disclosure;
fig. 4 is a block diagram of an electronic device for implementing a method of information recommendation of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It is to be understood that the described embodiments are only a few, and not all, of the disclosed embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It should be noted that the terminal device involved in the embodiments of the present disclosure may include, but is not limited to, a mobile phone, a Personal Digital Assistant (PDA), a wireless handheld device, a Tablet Computer (Tablet Computer), and other intelligent devices; the display device may include, but is not limited to, a personal computer, a television, and the like having a display function.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Generally, when a user uses an application program to make a car appointment, problems of difficulty in making the car appointment, long waiting time for taking a car and the like may exist, for example, the user often has difficulty in getting the car appointment in rush hours, abnormal weather conditions and the like, or the user often has a long waiting time for taking the car behind the car. In addition, in the car booking process of the user, no matter the user waits for too long time to pick up the car at the road or the driver waits for the passenger for a long time, bad experience can be brought to the driver and the passenger. Therefore, it is important to select an appropriate car reservation time.
At present, car booking operation is initiated actively by a user, car booking time is also determined by the user, after the user starts car booking service, a car booking platform or a car booking application program directly carries out operation of calling a car, and the car booking platform or the car booking application program does not carry out related suggestion or prompt on car booking opportunity.
Therefore, it is highly desirable to provide an information recommendation method, which can provide suggestions or prompts based on car appointment occasions for users, thereby reducing the waiting time of the users and improving the intelligence and reliability of car appointment service applications.
Fig. 1 is a schematic diagram according to a first embodiment of the present disclosure, as shown in fig. 1.
101. The method comprises the steps of obtaining historical car booking data of a user and real-time car booking data of a place where the user is located currently.
102. And predicting the recommended order issuing time of the user from the departure place to the destination place according to the historical car booking data and the real-time car booking data.
103. Providing the recommended invoice time to the user.
And providing car appointment prompting information corresponding to the recommended issuing time to the user according to the recommended issuing time provided to the user.
It should be noted that the user may include a passenger using the appointment client. The taxi booking can comprise instant taxi booking and scheduled taxi booking, namely booking taxi booking.
It should be noted that the historical taxi appointment data of the user may include, but is not limited to taxi appointment preference information of the user, trip route information of the user, and historical departure time.
It should be noted that the real-time car-booking data may include, but is not limited to, the current number of available single vehicles at the user's departure location, the number of car-booking persons, and the distance between the vehicle and the user's departure location.
It should be noted that the order issuing time may refer to a time when the user issues an order based on the car booking client.
It should be noted that part or all of the execution subjects of 101 to 103 may be an application located at the local terminal, or may also be a functional unit such as a plug-in or Software Development Kit (SDK) set in the application located at the local terminal, or may also be a processing engine located in a server on the network side, or may also be a distributed system located on the network side, for example, a processing engine or a distributed system in a car-booking platform on the network side, which is not particularly limited in this embodiment.
It is to be understood that the application may be a native application (native app) installed on the local terminal, or may also be a web page program (webApp) of a browser on the local terminal, which is not limited in this embodiment.
Therefore, by acquiring historical car booking data of a user and real-time car booking data of the current place of the user, and then predicting recommended departure time of the user from a departure place to a destination place according to the historical car booking data and the real-time car booking data, the recommended departure time can be provided for the user.
Optionally, in a possible implementation manner of this embodiment, before 102, the car appointment query information provided by the user may be further obtained, and then the departure location and the destination location may be determined according to the car appointment query information provided by the user.
In this implementation, the car appointment query information provided by the user may include a departure point and a destination point input by the user and the issuing operation information triggered by the user.
In a specific implementation process of the implementation manner, when the user has a car appointment behavior, car appointment query information of the user can be acquired, and a departure place and a destination place inquired by the user can be acquired according to the car appointment query information provided by the user.
In the specific implementation process, if the user confirms the booking, the order issuing operation information triggered by the user can be acquired. The issuing operation information may include an issuing instruction and an issuing time. The billing time may be an instant billing time.
In this way, when the user makes a car appointment query, car appointment query information such as a departure point and a destination point to be queried can be acquired, and the departure point and the destination point in the car appointment query information can be directly determined through the car appointment query information provided by the user. Therefore, when the user has car appointment behaviors, the recommended departure time from the departure point to the destination point of the user can be predicted based on the determined departure point and the determined destination point, and the pertinence and the accuracy of the predicted recommended departure time are improved.
Optionally, in a possible implementation manner of this embodiment, before 102, the vehicle appointment preference information of the user may be further obtained according to the historical vehicle appointment data, and then the departure location and the destination location may be predicted according to the vehicle appointment preference information of the user.
In this implementation, the user's appointment preference information may include historical departure and destination points, the type of vehicle selected by the user, and the consumption price range selected by the user, among others.
In a specific implementation process of this implementation, when a user does not have a car-booking behavior, car-booking preference information of the user may be obtained according to the historical car-booking data, and then a historical departure location and a destination location of the user may be obtained according to the obtained car-booking preference information of the user, so as to predict a departure location and a destination location corresponding to the car-booking behavior of the user in a predetermined time.
In this implementation, the car appointment behavior at the predetermined time may include a predetermined car appointment behavior, a commute car appointment behavior on or off duty, and a car appointment behavior in a multi-vehicle combination travel mode.
In this way, the departure point and the destination point corresponding to the car-booking behavior of the user in the predetermined time can be predicted according to the car-booking preference information of the user obtained based on the historical car-booking data. Therefore, when the user does not have car appointment behaviors, the recommended departure time from the departure point to the destination point of the user can be predicted based on the predicted departure point and the predicted destination point, and the pertinence and the accuracy of the predicted recommended departure time are improved.
Optionally, in a possible implementation manner of this embodiment, in 102, specifically, an expected boarding time from the current location of the user to the departure location may be determined according to the current location of the user and the departure location, and then an expected waiting time from the user immediately issuing the order to the arrival of the vehicle at the departure location may be determined according to the historical car-booking data and the real-time car-booking data, so that a recommended ordering time from the departure location to the destination location of the user may be predicted according to the expected boarding time and the expected waiting time.
In this implementation, the predicted boarding time may be a predicted boarding time point representing the arrival at the departure location from the current location of the user, or may be a predicted boarding time interval representing the arrival at the departure location from the current location of the user, that is, a predicted time period required for boarding.
The predicted wait time may be a predicted wait time point characterizing an immediate issuance of an order by the user to the arrival of the vehicle at the departure location, or may be a predicted wait time interval, i.e., a predicted wait duration, characterizing an immediate issuance of an order by the user to the arrival of the vehicle at the departure location.
Specifically, the predicted waiting time may be determined based on the time from the user's immediate issuance of an order to the driver's order and the time from the driver's order to the arrival of the vehicle at the departure location.
In a specific implementation process of the implementation manner, under the condition that a user has a car appointment behavior, the instant order issuing time of the user can be obtained according to car appointment query information provided by the user, and the recommended order issuing time of the user from a departure place to a destination place can be obtained according to the instant order issuing time, the predicted boarding time and the predicted waiting time.
In one embodiment of the present invention, if the predicted getting-on time is greater than the predicted waiting time, the recommended departure time from the departure point to the destination point of the user may be further obtained according to the instant departure time, the predicted getting-on time, and the time interval between the predicted waiting times.
In this particular implementation, the instant issuance time may be a characteristic instant issuance time point. The recommendation issuance time may be indicative of a recommendation issuance time point or may be indicative of a recommendation issuance time interval.
In another case of this specific implementation process, if the recommended issuance time from the departure point to the destination point is obtained according to the time interval between the expected boarding time and the expected waiting time, the obtained recommended issuance time from the departure point to the destination point of the user may be the representative recommended issuance time interval.
In another case of the specific implementation process, if the recommended invoice time from the departure point to the destination point of the user is obtained according to the instant invoice time, the predicted boarding time and the predicted waiting time, the obtained recommended invoice time from the departure point to the destination point of the user may be the representative recommended invoice time point.
In another case of this specific implementation process, in an actual application scenario, if the predicted boarding time is less than the predicted waiting time under the existing car booking behavior of the user, the issuing is actually successful, that is, the driver has accepted the ticket, and therefore, the recommended departure time provided to the user can be determined according to the time interval between the predicted boarding time and the predicted waiting time.
In another embodiment, if the predicted getting-on time from the current location of the user to the departure location cannot be determined according to the current location of the user and the departure location, the predicted waiting time may be provided to the user, so that the user can determine the departure time or the car appointment time according to the predicted waiting time and the current self-demand condition.
Therefore, the recommended ordering time from the departure place to the destination place of the user can be obtained through the instant ordering time, the estimated getting-on time and the estimated waiting time which are obtained based on the taxi appointment query information provided by the user, the recommended ordering time suitable for the user can be analyzed and predicted more accurately and effectively under the condition that the user has taxi appointment behaviors, the riding waiting time of the user is reduced, the accuracy and the effectiveness of the recommended information are further improved, and the intelligence and the reliability of taxi appointment application services are further improved.
In another specific implementation process of this implementation, when the user has no car appointment behavior, the historical departure time of the user may be obtained according to the historical car appointment data, and the recommended departure time of the user from the departure point to the destination point may be obtained according to the historical departure time, the predicted boarding time, and the predicted waiting time.
In this particular implementation, the historical issuance time may be a historical issuance time point. The recommended issuance time may be a recommended issuance time point.
In a case of this specific implementation process, if the predicted boarding time is less than the predicted waiting time, the recommended departure time from the departure location to the destination location of the user may be further obtained according to the historical departure time, the predicted boarding time, and the time interval between the predicted waiting times.
It is understood that in the case where the user does not have a car appointment behavior, the car appointment behavior of the user at the predetermined time, i.e., the departure, is predicted, and the predicted boarding time being greater than the predicted waiting time may indicate that the departure may be made at the predetermined time and may be immediately offered to the vehicle, and thus, the user may not be provided with a recommended departure time.
In this way, the recommended departure time of the user from the departure place to the destination place can be obtained through the historical departure time, the predicted boarding time and the predicted waiting time which are obtained based on the historical taxi appointment data, the recommended departure time suitable for the user can be analyzed and predicted more accurately and effectively under the condition that the user does not have taxi appointment behaviors, the riding waiting time of the user is reduced, the accuracy and the effectiveness of the recommended information are further improved, and the intelligence and the reliability of taxi appointment application services are further improved.
In another specific implementation process of the implementation manner, the current location of the user may be determined specifically according to the positioning information of the mobile terminal device of the user.
Specifically, the current location of the user may be determined according to the positioning information of the mobile terminal device of the user.
For example, the current location of the user may be determined according to Global Navigation Satellite System (GNSS) positioning information and/or mobile positioning information of the mobile terminal device of the user.
Therefore, the recommended ordering time from the departure place to the destination place of the user can be predicted based on the predicted boarding time determined by the current place and the departure place of the user and the predicted waiting time determined by the historical car booking data and the real-time car booking data, the recommended ordering time suitable for the user can be predicted more accurately, the accuracy and the effectiveness of the recommended information are further improved, and the intelligence and the reliability of the car booking application service are further improved.
It should be noted that the information recommendation method of the present embodiment may be implemented by combining various specific implementation processes for determining the departure point and the destination point, which are provided in the foregoing implementation manner, with various specific implementation processes for predicting the recommendation issuance time of the user from the departure point to the destination point, which are provided in the implementation manner. For a detailed description, reference may be made to the related contents in the foregoing implementation manners, and details are not described herein.
Optionally, in a possible implementation manner of this embodiment, in 103, while the recommended departure time is provided to the user, a car appointment promoting information corresponding to the recommended departure time may be provided to the user according to the recommended departure time provided to the user.
It should be noted that the information recommendation method of the present embodiment may be implemented by combining various specific implementation processes provided in the foregoing implementation manner for predicting the recommended departure time of the user from the departure point to the destination point with a manner of providing the car appointment reminder information corresponding to the recommended departure time to the user in the implementation manner. For a detailed description, reference may be made to the related contents in the foregoing implementation manners, and details are not described herein.
In the embodiment, the recommended departure time from the departure place to the destination place of the user can be predicted by acquiring the historical taxi appointment data of the user and the real-time taxi appointment data of the current place of the user according to the historical taxi appointment data and the real-time taxi appointment data, so that the recommended departure time can be provided for the user.
In addition, with the technical solution provided in this embodiment, when a user performs a car appointment query, car appointment query information such as a departure point and a destination point to be queried may be acquired, and the departure point and the destination point in the car appointment query information may be directly determined through the car appointment query information provided by the user. Therefore, when the user has car appointment behaviors, the recommended departure time from the departure point to the destination point of the user can be predicted based on the determined departure point and the determined destination point, and the pertinence and the accuracy of the predicted recommended departure time are improved.
In addition, by adopting the technical scheme provided by the embodiment, the departure place and the destination place corresponding to the car booking behavior of the user in the preset time can be predicted according to the car booking preference information of the user obtained based on the historical car booking data. Therefore, when the user does not have car appointment behaviors, the recommended departure time from the departure point to the destination point of the user can be predicted based on the predicted departure point and the predicted destination point, and the pertinence and the accuracy of the predicted recommended departure time are improved.
In addition, by adopting the technical scheme provided by the embodiment, the recommended departure time of the user from the departure point to the destination point can be obtained by the instant departure time, the predicted boarding time and the predicted waiting time which are obtained based on the car appointment query information provided by the user, the recommended departure time suitable for the user can be analyzed and predicted more accurately and effectively under the condition that the user has car appointment behaviors, the waiting time for taking a car by the user is reduced, the accuracy and the effectiveness of the recommended information are further improved, and the intelligence and the reliability of the car appointment application service are further improved.
Furthermore, the recommended departure time of the user from the departure point to the destination point can be obtained through the historical departure time, the predicted boarding time and the predicted waiting time which are obtained based on the historical car booking data, the recommended departure time suitable for the user can be analyzed and predicted more accurately and effectively under the condition that the user does not have car booking behaviors, the waiting time for the user to take a car is shortened, the accuracy and the effectiveness of the recommended information are further improved, and therefore the intelligence and the reliability of the car booking application service are further improved.
In addition, by adopting the technical scheme provided by the embodiment, the recommended ordering time from the departure point to the destination point of the user can be predicted based on the predicted boarding time determined by the current location and departure point of the user and the predicted waiting time determined by the historical car booking data and the real-time car booking data, the recommended ordering time suitable for the user can be predicted more accurately, the accuracy and the effectiveness of the recommended information are further improved, and the intelligence and the reliability of the car booking application service are further improved.
In addition, by adopting the technical scheme provided by the embodiment, the future behavior of the user can be predicted through information such as historical behaviors of the user, and effective suggestion information can be automatically provided for the user, so that the intelligent perception of the user on the car appointment application service is improved, and the use experience of the user is optimized.
Fig. 2 is a schematic diagram according to a second embodiment of the present disclosure, as shown in fig. 2.
201. And acquiring historical car booking data of the user.
Here, the user's historical car booking data may include, but is not limited to, the user's car booking preference information, the user travel route information, and the historical departure time, i.e., the historical taxi calling time.
202. And identifying the current place of the user.
Specifically, the current location of the user may be identified according to the positioning information of the mobile terminal of the user, so as to determine whether the user currently arrives at the departure location.
For example, the current location of the user can be identified as the inside of a building, such as a residential building, an office building, a shopping mall, a subway/bus and other transportation hubs, through GNSS positioning information, such as GPS positioning information, and/or mobile positioning information of the mobile terminal of the user.
203. And acquiring real-time car booking data of the current place of the user.
In particular, the real-time car reservation data may include, but is not limited to, the current number of available single vehicles at the user's departure location, the number of car reservations, the distance between the vehicle and the user's departure location.
204. A departure location and a destination location of the user are determined.
In this embodiment, when the user has a car appointment behavior, car appointment query information provided by the user may be acquired, and the departure location and the destination location may be determined according to the car appointment query information provided by the user.
And under the condition that the user does not have car booking behaviors, obtaining car booking preference information of the user according to the historical car booking data, and predicting a departure place and a destination place according to the car booking preference information of the user.
205. And determining the predicted boarding time from the current place of the user to the departure place according to the current place of the user and the departure place.
206. And determining the predicted waiting time from the user to the vehicle arrival departure point immediately according to the historical vehicle booking data and the real-time vehicle booking data.
Therefore, after the predicted boarding time and the predicted waiting time are determined, the recommended departure time of the user from the departure point to the destination point can be determined according to different car appointment behavior conditions of the user, so that the recommendation information corresponding to the recommended departure time is provided for the user.
In this embodiment, in the case where the user has a car appointment, 207 may be performed to obtain a recommended departure time from the departure point to the destination point of the user.
Specifically, in the event that the user does not have a car appointment, 208 may be performed to obtain a recommended departure time for the user from the departure location to the destination location.
207. And acquiring the instant order issuing time of the user according to the taxi appointment query information provided by the user, so as to acquire the recommended order issuing time from the departure place to the destination place of the user according to the instant order issuing time, the predicted boarding time and the predicted waiting time.
Specifically, if the recommended invoice time is a characteristic time point, for example, 9 points, the recommended invoice time from the departure point to the destination point of the user may be obtained from the instant invoice time, the predicted boarding time, and the predicted waiting time.
Alternatively, if the recommended invoice time is indicative of a recommended invoice interval, i.e., a duration of time, e.g., 5 minutes, the recommended invoice time t may be calculated according to the following equation 1x：
tx＝t1-t2 (1)
Wherein, t1May be the expected boarding time, t2May be the expected wait time, t1＞t2。
It is understood that, in a practical application scenario, under the condition that the user has car booking behavior, if the predicted boarding time is less than the predicted waiting time, the issuing of the order is actually successful, namely, the driver takes the order, and therefore, the recommended departure time provided to the user can be determined according to the time interval between the predicted boarding time and the predicted waiting time.
208. And obtaining the historical departure time of the user according to the historical taxi appointment data, and obtaining the recommended departure time of the user from the departure place to the destination place according to the historical departure time, the predicted boarding time and the predicted waiting time.
Specifically, the recommended issuance time here may be a characterization time point. The recommended invoice time t can be calculated according to the following formula 2x：
tx＝t0-t1-t2 (2)
Wherein, t0May be a historical departure time, i.e. a predicted departure time, t1May be the expected boarding time, t2May be the expected wait time, t1＜t2。
It is understood that, in the case where the user does not have the car appointment behavior, the car appointment behavior of the user at the predetermined time, i.e., the order is predicted, and the predicted getting-on time being greater than the predicted waiting time may indicate that the order is made at the predetermined time and may be immediately offered to the vehicle, and thus, the user may not be provided with the recommended order time.
209. And providing the recommended order issuing time and the recommendation information corresponding to the recommended order issuing time for the user.
In this embodiment, recommendation information corresponding to the recommended order issuing time may be provided to the user according to the recommended order issuing time.
Optionally, according to the recommended order issuing time and the service scene, it may be determined to provide the recommended information corresponding to the recommended order issuing time and the service scene to the user, and the recommended information may be sent to the user.
Specifically, the recommendation information may include car appointment reminder information. The recommended issuance time may include at least one of an issuance time and a recommended departure time.
For example, when the user has a car booking behavior, and the expected boarding time is greater than the expected waiting time, and after the recommended departure time from the departure point to the destination point of the user is obtained, the car booking prompt information corresponding to the recommended departure time may be provided to the user according to the recommended departure time: at present, the speed of receiving driving is high, which may cause the driver to wait for a long time and advise you t after going outxAnd calling the car again after the minute.
As another example, there is a car appointment activity in the userAnd the predicted boarding time is less than the predicted waiting time, then the order has been successfully issued, i.e. the driver has taken the order, and therefore the recommended departure time from the departure point to the destination point is obtained for the user. Then, according to the recommended departure time, providing car appointment prompting information corresponding to the recommended departure time to the user: at present, you are close to a boarding point, and can wait at t for avoiding long-time waitingxThe minute then starts to go to the boarding point.
For another example, when the user has no car appointment behavior and the expected boarding time is less than the expected waiting time, after the recommended departure time from the departure point to the destination point of the user is obtained, the car appointment prompting information corresponding to the recommended departure time may be provided to the user according to the recommended departure time: at present, the waiting time for car appointment is long, and according to the appointment/past invoice time of you, you are at present, namely at txAt that time, the car reservation can be started.
It can be understood that the information recommendation method of the embodiment may be applied to a scenario that includes a car appointment application service such as a map car appointment platform, other car appointment platforms, and a car appointment application program.
By adopting the technical scheme provided by the embodiment, the recommended departure time from the departure place to the destination place of the user can be predicted by acquiring the historical taxi appointment data of the user and the real-time taxi appointment data of the current place of the user according to the historical taxi appointment data and the real-time taxi appointment data, so that the recommended departure time can be provided for the user.
In addition, the future behavior of the user is predicted based on the information such as the historical behavior of the user, and effective suggestion information can be automatically provided for the user, so that the intelligent perception of the user on the car appointment application service is improved.
It is noted that while for simplicity of explanation, the foregoing method embodiments have been described as a series of acts or combination of acts, it will be appreciated by those skilled in the art that the present disclosure is not limited by the order of acts, as some steps may, in accordance with the present disclosure, occur in other orders and concurrently. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required for the disclosure.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
Fig. 3 is a schematic diagram according to a third embodiment of the present disclosure, as shown in fig. 3. The information recommendation apparatus 300 of the present embodiment may include an acquisition unit 301, a prediction unit 302, and a recommendation unit 303. The obtaining unit 301 is configured to obtain historical car booking data of a user and real-time car booking data of a current location of the user; a prediction unit 302, configured to predict a recommended departure time from a departure point to a destination point of the user according to the historical car booking data and the real-time car booking data; a recommending unit 303, configured to provide the recommended ordering time to the user.
It should be noted that, part or all of the information recommendation apparatus in this embodiment may be an application located at the local terminal, or may also be a functional unit such as a plug-in or Software Development Kit (SDK) set in the application located at the local terminal, or may also be a processing engine located in a server on the network side, or may also be a distributed system located on the network side, for example, a processing engine or a distributed system in a vehicle-saving platform on the network side, and this embodiment is not particularly limited thereto.
It is to be understood that the application may be a native application (native app) installed on the local terminal, or may also be a web page program (webApp) of a browser on the local terminal, which is not limited in this embodiment.
Optionally, in a possible implementation manner of this embodiment, the prediction unit 302 may be further configured to obtain car appointment query information provided by the user, and determine the departure location and the destination location according to the car appointment query information provided by the user.
Optionally, in a possible implementation manner of this embodiment, the predicting unit 302 may be further configured to obtain car appointment preference information of the user according to the historical car appointment data, and predict the departure location and the destination location according to the car appointment preference information of the user.
Optionally, in a possible implementation manner of this embodiment, the predicting unit 302 may be specifically configured to determine an expected boarding time from the current location of the user to the departure location according to the current location of the user and the departure location, determine an expected waiting time from the instant issuance of the user to the arrival of the vehicle at the departure location according to the historical taxi-appointment data and the real-time taxi-appointment data, and predict a recommended issuance time from the departure location to the destination location of the user according to the expected boarding time and the expected waiting time.
Optionally, in a possible implementation manner of this embodiment, the prediction unit may be specifically configured to obtain an instant waybill time of the user according to the car appointment query information provided by the user, and obtain a recommended waybill time of the user from the departure point to the destination point according to the instant waybill time, the predicted boarding time, and the predicted waiting time.
Alternatively, the prediction unit 302 may be specifically configured to obtain the historical departure time of the user according to the historical taxi appointment data, and obtain the recommended departure time of the user from the departure point to the destination point according to the historical departure time, the predicted boarding time, and the predicted waiting time.
In this embodiment, the historical car booking data of the user and the real-time car booking data of the current location of the user are acquired by the acquisition unit, and then the determination unit predicts the recommended departure time of the user from the departure location to the destination location according to the historical car booking data and the real-time car booking data, so that the verification unit can provide the recommended departure time for the user.
In addition, with the technical solution provided in this embodiment, when a user performs a car appointment query, car appointment query information such as a departure point and a destination point to be queried may be acquired, and the departure point and the destination point in the car appointment query information may be directly determined through the car appointment query information provided by the user. Therefore, when the user has car appointment behaviors, the recommended departure time from the departure point to the destination point of the user can be predicted based on the determined departure point and the determined destination point, and the pertinence and the accuracy of the predicted recommended departure time are improved.
In addition, by adopting the technical scheme provided by the embodiment, the departure place and the destination place corresponding to the car booking behavior of the user in the preset time can be predicted according to the car booking preference information of the user obtained based on the historical car booking data. Therefore, when the user does not have car appointment behaviors, the recommended departure time from the departure point to the destination point of the user can be predicted based on the predicted departure point and the predicted destination point, and the pertinence and the accuracy of the predicted recommended departure time are improved.
In addition, by adopting the technical scheme provided by the embodiment, the recommended departure time of the user from the departure point to the destination point can be obtained by the instant departure time, the predicted boarding time and the predicted waiting time which are obtained based on the car appointment query information provided by the user, the recommended departure time suitable for the user can be analyzed and predicted more accurately and effectively under the condition that the user has car appointment behaviors, the waiting time for taking a car by the user is reduced, the accuracy and the effectiveness of the recommended information are further improved, and the intelligence and the reliability of the car appointment application service are further improved.
Furthermore, the recommended departure time of the user from the departure point to the destination point can be obtained through the historical departure time, the predicted boarding time and the predicted waiting time which are obtained based on the historical car booking data, the recommended departure time suitable for the user can be analyzed and predicted more accurately and effectively under the condition that the user does not have car booking behaviors, the waiting time for the user to take a car is shortened, the accuracy and the effectiveness of the recommended information are further improved, and therefore the intelligence and the reliability of the car booking application service are further improved.
In addition, by adopting the technical scheme provided by the embodiment, the recommended ordering time from the departure point to the destination point of the user can be predicted based on the predicted boarding time determined by the current location and departure point of the user and the predicted waiting time determined by the historical car booking data and the real-time car booking data, the recommended ordering time suitable for the user can be predicted more accurately, the accuracy and the effectiveness of the recommended information are further improved, and the intelligence and the reliability of the car booking application service are further improved.
In addition, by adopting the technical scheme provided by the embodiment, the future behavior of the user can be predicted through information such as historical behaviors of the user, and effective suggestion information can be automatically provided for the user, so that the intelligent perception of the user on the car appointment application service is improved, and the use experience of the user is optimized.
In the technical scheme of the disclosure, the personal information of the user, such as the collection, storage, use, processing, transmission, provision, disclosure and other processes of the car appointment information, the real-time position and the like of the user, all meet the regulations of relevant laws and regulations, and do not violate the good custom of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 4 shows a schematic block diagram of an example electronic device 400 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 4, the electronic device 400 includes a computing unit 401 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)402 or a computer program loaded from a storage unit 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
A number of components in the electronic device 400 are connected to the I/O interface 405, including: an input unit 406 such as a keyboard, a mouse, or the like; an output unit 407 such as various types of displays, speakers, and the like; a storage unit 408 such as a magnetic disk, optical disk, or the like; and a communication unit 409 such as a network card, modem, wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
Computing unit 401 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 401 executes the respective methods and processes described above, such as the method of information recommendation. For example, in some embodiments, the method of information recommendation may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 400 via the ROM 402 and/or the communication unit 409. When the computer program is loaded into RAM 403 and executed by computing unit 401, one or more steps of the method of information recommendation described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured by any other suitable means (e.g. by means of firmware) to perform the method of information recommendation.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims (13)

1. A method of information recommendation, comprising:
acquiring historical car booking data of a user and real-time car booking data of a current place of the user;
predicting recommended departure time of the user from a departure place to a destination place according to the historical taxi appointment data and the real-time taxi appointment data;
providing the recommended invoice time to the user.
2. The method of claim 1, wherein a recommended departure time of the user from a departure location to a destination location is predicted based on the historical car appointment data and the real-time car appointment data, the method further comprising:
obtaining taxi appointment query information provided by the user;
and determining the departure place and the destination place according to the taxi appointment inquiry information provided by the user.
3. The method of claim 1, wherein a recommended departure time of the user from a departure location to a destination location is predicted based on the historical car appointment data and the real-time car appointment data, the method further comprising:
obtaining taxi appointment preference information of the user according to the historical taxi appointment data;
and predicting the departure place and the destination place according to the taxi appointment preference information of the user.
4. The method of any of claims 1-3, wherein predicting a recommended departure time for the user from a departure location to a destination location based on the historical car booking data and the real-time car booking data comprises:
determining the predicted boarding time from the current location of the user to the departure location according to the current location of the user and the departure location;
determining the predicted waiting time from the user to the vehicle to arrive at the departure place immediately according to the historical vehicle booking data and the real-time vehicle booking data;
and predicting the recommended order issuing time of the user from the departure place to the destination place according to the predicted getting-on time and the predicted waiting time.
5. The method of claim 4, wherein predicting a recommended departure time for the user from a departure location to a destination location based on the projected boarding time and the projected wait time comprises:
acquiring the instant order issuing time of the user according to the taxi appointment query information provided by the user; obtaining the recommended order issuing time of the user from a starting place to a destination place according to the instant order issuing time, the predicted boarding time and the predicted waiting time; or
Acquiring the historical taxi booking time of the user according to the historical taxi booking data; and obtaining the recommended order issuing time of the user from a departure place to a destination place according to the historical order issuing time, the predicted boarding time and the predicted waiting time.
6. An apparatus for information recommendation, comprising:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring historical car booking data of a user and real-time car booking data of a current place of the user;
the prediction unit is used for predicting recommended departure time of the user from a departure place to a destination place according to the historical car booking data and the real-time car booking data;
and the recommending unit is used for providing the recommended order issuing time for the user.
7. The apparatus of claim 6, wherein the prediction unit is further configured to
Obtaining taxi appointment query information provided by the user;
and determining the departure place and the destination place according to the taxi appointment inquiry information provided by the user.
8. The apparatus of claim 6, wherein the prediction unit is further configured to
Obtaining taxi appointment preference information of the user according to the historical taxi appointment data;
and predicting the departure place and the destination place according to the taxi appointment preference information of the user.
9. The apparatus according to any of claims 6-8, wherein the prediction unit, in particular for
Determining the predicted boarding time from the current location of the user to the departure location according to the current location of the user and the departure location;
determining the predicted waiting time from the user to the vehicle to arrive at the departure place immediately according to the historical vehicle booking data and the real-time vehicle booking data; and
and predicting the recommended order issuing time of the user from the departure place to the destination place according to the predicted boarding time and the predicted waiting time.
10. The apparatus according to any of claims 9, wherein the prediction unit is, in particular for
Acquiring the instant order issuing time of the user according to the taxi appointment query information provided by the user; obtaining the recommended order issuing time of the user from a starting place to a destination place according to the instant order issuing time, the predicted boarding time and the predicted waiting time; or
Acquiring the historical taxi booking time of the user according to the historical taxi booking data; and obtaining the recommended order issuing time of the user from a departure place to a destination place according to the historical order issuing time, the predicted boarding time and the predicted waiting time.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
13. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-5.
CN202111611971.6A 2021-12-27 2021-12-27 Information recommendation method and device, electronic equipment and storage medium Pending CN114528498A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
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Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111611971.6A CN114528498A (en) 2021-12-27 2021-12-27 Information recommendation method and device, electronic equipment and storage medium

Publications (1)

Publication Number Publication Date
CN114528498A true CN114528498A (en) 2022-05-24

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Country Link
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