Route book recommendation method and device, equipment and computer readable storage medium

Abstract

The application discloses a road book recommendation method and device, equipment and a computer readable storage medium, and belongs to the technical field of data processing. The method obtains historical portrait data and historical operation data of a user; determines a recommendation value corresponding to each of a plurality of reference road books based on the historical portrait data and the historical operation data; and recommends at least one reference road book from the plurality of reference road books that meets a recommendation condition. The user portrait data is obtained based on historical road book data of the user, and the historical operation data is obtained based on at least one of historical click data or historical search data of the user. The method makes the recommended road book meet the travel habits of the user and also considers the active intention of the user, thereby further improving the accuracy of the recommended data and improving the recommendation efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a route book recommendation method and device, equipment and a computer readable storage medium. BACKGROUND

[0002] A route book refers to a detailed plan for a trip, generally including travel arrangements, traffic information, time information, scenic spot recommendations, expense information, etc., and is an important preparation for self-driving travel. The route book is generally made by experienced travel experts or travel agencies and is a product of the current custom tourism market.

[0003] Currently, users generally search for target route books in an existing route book database through keywords. Therefore, a route book recommendation method is needed to actively recommend route books that meet user habits to the user and improve the accuracy of the recommended route books. SUMMARY

[0004] The present application provides a route book recommendation method, device, equipment and computer readable storage medium, which can improve the accuracy of the recommended route books.

[0005] In a first aspect, a route book recommendation method is provided, which includes:

[0006] Obtaining historical portrait data and historical operation data of a user, wherein the user portrait data is obtained based on historical route book data of the user, and the historical operation data is obtained based on at least one of historical click data or historical search data of the user;

[0007] Obtaining a plurality of reference route books, determining a recommendation value corresponding to each of the plurality of reference route books based on the historical portrait data and the historical operation data;

[0008] Recommending at least one reference route book in the plurality of reference route books that meets a recommendation condition.

[0009] In a possible implementation, the obtaining of the plurality of reference route books includes:

[0010] Obtaining search data of the user, and obtaining a plurality of reference route books matching the search data in a route book database; or

[0011] Obtaining a plurality of reference route books matching the historical portrait data in the route book database.

[0012] In a possible implementation, the historical portrait data includes at least one of a value or a weight corresponding to at least one label and an attribute, and the at least one label includes days, mileage, region, season, festival, scenic spot number, price, or play duration.

[0013] The determining of the recommended values corresponding to the plurality of reference route books respectively based on the historical image data and the historical operation data comprises:

[0014] For any reference route book in the plurality of reference route books, the any reference route book is matched with the attributes of the at least one label to obtain a target label with a matching success;

[0015] The recommended value corresponding to the any reference route book is obtained based on at least one of a value or a weight corresponding to the target label and the historical operation data.

[0016] In a possible implementation, when the number of the target labels is a plurality, for any target label, the historical operation data comprises at least one of an operation number or an operation time for an attribute corresponding to the any target label;

[0017] The obtaining of the recommended value corresponding to the any reference route book based on at least one of the value or the weight corresponding to the target label and the historical operation data comprises:

[0018] The recommended value corresponding to the any target label is obtained based on at least one of the value and the weight corresponding to the any target label, at least one of the operation number or the operation time, and at least one of a number decay factor or a time decay factor.

[0019] The recommended value corresponding to the any reference route book is obtained according to the recommended values corresponding to the plurality of target labels respectively.

[0020] In a possible implementation, the obtaining of the recommended value corresponding to the any target label based on at least one of the value and the weight corresponding to the any target label, at least one of the operation number or the operation time, and at least one of a number decay factor or a time decay factor comprises:

[0021] The recommended value corresponding to the any target label is obtained according to the following formula based on at least one of the value and the weight corresponding to the any target label, at least one of the operation number or the operation time, and at least one of a number decay factor or a time decay factor:

[0022] Score(i)=(C*weigh+α*num)β;

[0023] Wherein, the Score(i) represents the recommended value corresponding to any target label, the C represents the value corresponding to any target label, the weigh represents the weight corresponding to any target label, the a represents the times decay factor, the num represents the operation times, and the b represents the time decay factor, which is obtained based on the operation time.

[0024] In a possible implementation, the recommending the at least one reference travel book in the plurality of reference travel books whose recommended value meets the recommended condition comprises:

[0025] The at least one reference travel book in the plurality of reference travel books whose recommended value is greater than a recommended threshold value or whose recommended value is ranked in the top N positions in the order of recommended values is displayed in the order of recommended values, where N is a positive integer.

[0026] In a possible implementation, after the recommending the at least one reference travel book in the plurality of reference travel books whose recommended value meets the recommended condition, the method further comprises:

[0027] Generating a plurality of custom travel books based on the historical portrait data, any custom travel book in the plurality of custom travel books matches the attribute corresponding to each label in the at least one label included in the historical portrait data, and the distance between the location of the first scenic spot included in any custom travel book in the plurality of custom travel books and the location of the user satisfies a distance condition;

[0028] The plurality of custom travel books are recommended.

[0029] The second aspect also provides a travel book recommendation device, which comprises:

[0030] A first obtaining module is configured to obtain historical portrait data and historical operation data of a user, wherein the user portrait data is obtained based on historical travel book data of the user, and the historical operation data is obtained based on at least one of historical click data or historical search data of the user;

[0031] A second obtaining module is configured to obtain a plurality of reference travel books;

[0032] A determining module is configured to determine recommended values corresponding to the plurality of reference travel books respectively based on the historical portrait data and the historical operation data;

[0033] A recommending module is configured to recommend at least one reference travel book in the plurality of reference travel books whose recommended value meets a recommended condition.

[0034] In a possible implementation, the second acquisition module is configured to acquire search data of the user, and acquire a plurality of reference travel notes matching the search data in a travel note database; or acquire a plurality of reference travel notes matching the historical portrait data in the travel note database.

[0035] In a possible implementation, the historical portrait data includes at least one of a value or a weight corresponding to at least one label and an attribute, and the at least one label includes a day, a mileage, a region, a season, a festival, a number of scenic spots, a price, or a play duration.

[0036] The determination module is configured to, for any one of the plurality of reference travel notes, match the any one of the plurality of reference travel notes with the attribute of the at least one label to obtain a target label that matches successfully, and acquire a recommended value corresponding to the any one of the plurality of reference travel notes based on at least one of a value or a weight corresponding to the target label and the historical operation data.

[0037] In a possible implementation, when the number of target labels is a plurality, for any one of the target labels, the historical operation data includes at least one of an operation number or an operation time for an attribute corresponding to the any one of the target labels.

[0038] The determination module is configured to acquire a recommended value corresponding to the any one of the target labels based on at least one of a value and a weight corresponding to the any one of the target labels, at least one of an operation number or an operation time, at least one of a number decay factor or a time decay factor, and acquire a recommended value corresponding to the any one of the plurality of reference travel notes according to recommended values corresponding to a plurality of target labels respectively.

[0039] In a possible implementation, the determination module is configured to acquire a recommended value corresponding to the any one of the target labels according to the following formula based on at least one of a value and a weight corresponding to the any one of the target labels, at least one of an operation number or an operation time, at least one of a number decay factor or a time decay factor.

[0040] Score(i)=(C*weigh+α*num)β;

[0041] wherein the Score(i) represents the recommended value corresponding to the any one of the target labels, the C represents the value corresponding to the any one of the target labels, the weigh represents the weight corresponding to the any one of the target labels, the α represents the number decay factor, the num represents the operation number, the β represents the time decay factor, and the time decay factor is acquired based on the operation time.

[0042] In a possible implementation, the recommendation module is configured to display, in the order of the recommendation values, at least one reference travel book in the plurality of reference travel books, wherein a recommendation value of the at least one reference travel book is greater than a recommendation threshold value or a recommendation value of the at least one reference travel book is in a top N position in the order of the recommendation values, N being a positive integer.

[0043] In a possible implementation, the apparatus further includes:

[0044] The customization module is configured to generate a plurality of customized travel books based on the historical portrait data, wherein any customized travel book in the plurality of customized travel books matches an attribute corresponding to each of at least one label included in the historical portrait data, and a distance between a location of a first scenic spot included in any customized travel book in the plurality of customized travel books and a location of the user satisfies a distance condition.

[0045] The recommendation module is further configured to recommend the plurality of customized travel books.

[0046] In a third aspect, a computer device is further provided. The computer device includes a processor and a memory. The memory stores at least one program code. The at least one program code is loaded and executed by the processor, so that the computer device implements the travel book recommendation method according to any one of the preceding aspects.

[0047] In a fourth aspect, a computer readable storage medium is further provided. The computer readable storage medium stores at least one program code. The at least one program code is loaded and executed by a processor, so that a computer implements the travel book recommendation method according to any one of the preceding aspects.

[0048] In a fifth aspect, a computer program product or a computer program is further provided. The computer program product or the computer program includes computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium. The processor executes the computer instructions, so that the computer device performs the travel book recommendation method according to any one of the preceding aspects.

[0049] The technical solutions provided in the present application can bring at least the following beneficial effects:

[0050] The technical solutions provided in the present application are based on historical portrait data of a user to filter reference travel books for the user for recommendation. The recommended travel books are based on historical data of the user and are more in line with travel habits of the user. In addition, the historical operation data of the user is used to determine a recommendation value, so that the recommended travel books take into account the active intention of the user, further improving the accuracy of the recommended data and improving the recommendation efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort based on these drawings.

[0052] Figure 1 is a schematic diagram of an implementation environment of a route book recommendation method provided by an embodiment of the present application;

[0053] Figure 2 is a flowchart of a route book recommendation method provided by an embodiment of the present application;

[0054] Figure 3 is a schematic diagram of a route book recommendation model provided by an embodiment of the present application;

[0055] Figure 4 is a schematic diagram of a route book recommendation device provided by an embodiment of the present application;

[0056] Figure 5 is a structural schematic diagram of a computer device provided by an embodiment of the present application;

[0057] Figure 6 is a structural schematic diagram of a server provided by an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the drawings.

[0059] With the prevalence of self-driving travel mode, the demand for obtaining route books in advance is increasing. Therefore, the present application provides a route book recommendation method, which can actively recommend route books meeting the user's demand for the user according to the user's historical portrait data and historical search data. First, the implementation environment of the route book recommendation method provided by the present application is briefly introduced.

[0060] Referring to Figure 1The implementation environment includes a terminal 101. Optionally, the terminal 101 is installed with an application client, and the application client is used to run a route book recommendation method provided in the embodiments of the present application. The application client can be any application client that provides route books, for example, the application client can be a map application client or a travel application client. The application client includes a display interface, for example, when a user opens the application client, at least one reference route book obtained according to the route book recommendation method provided in the embodiments of the present application is actively recommended through the display interface; or when the user inputs search data through the display interface, at least one reference route book obtained according to the route book recommendation method provided in the embodiments of the present application is actively recommended through the display interface.

[0061] Optionally, the implementation environment further includes a server 102, and the terminal 101 is connected to the server 102 in a wired or wireless manner. The server 102 stores user historical route book data, historical click data, historical search data, and the like.

[0062] In the embodiments of the present application, the server 102 obtains user historical portrait data and historical operation data according to user historical route book data, historical click data, and historical search data, and the terminal 101 pulls the user historical portrait data and historical operation data from the server 102, so as to determine at least one reference route book for recommendation according to the user historical portrait data and historical operation data. Alternatively, the terminal 101 pulls user historical route book data, historical click data, and historical search data from the server 102, and obtains user historical portrait data and historical operation data according to the user historical route book data, historical click data, and historical search data.

[0063] In a possible implementation manner, the terminal 101 can be any electronic product that can perform human-computer interaction with a user through one or more of a keyboard, a touchpad, a touch screen, a remote controller, voice interaction, a handwriting device, and the like, for example, a personal computer (PC), a smart phone, a personal digital assistant (PDA), a wearable device, a pocket PC (PPC), a tablet computer, a smart car machine, and the like. The server 102 can be a standalone physical server, or a server cluster or a distributed system formed by multiple physical servers, or a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and basic cloud computing services such as big data and artificial intelligence platforms.

[0064] Those skilled in the art shall understand that the terminal 101 and the server 102 are only examples, other existing or future computer devices can also be applicable to the present application and shall be included in the protection scope of the present application, and are hereby included by reference.

[0065] Based on the above Figure 1 As shown in the implementation environment, Figure 2 As shown in the implementation environment,

[0066] Step 201, obtaining historical portrait data and historical operation data of a user, the historical portrait data of the user is obtained based on historical route book data of the user, and the historical operation data is obtained based on at least one of historical click data or historical search data of the user.

[0067] In the embodiment of the present application, the historical portrait data can represent the habit preference of the user, and the historical operation data can represent the active intention of the user. Optionally, the terminal can obtain at least one of the historical route book data, the historical click data or the historical search data of the user through the historical use data of the user, and then obtain the historical portrait data of the user based on the historical route book data of the user, and obtain the historical operation data of the user based on at least one of the historical click data or the historical search data of the user.

[0068] Alternatively, the terminal directly obtains the historical portrait data and the historical operation data of the user from the server, and the server is used to obtain at least one of the historical route book data, the historical click data or the historical search data of the user through the historical use data of the user, and then obtain the historical portrait data of the user based on the historical route book data of the user, and obtain the historical operation data of the user based on at least one of the historical click data or the historical search data of the user.

[0069] The historical route book data is the route book used by the user in a first historical time, the historical click data is the content data selected by the user through clicking in a second historical time, and the historical search data is the content data searched by the user by inputting in a third historical time. The first historical time, the second historical time and the third historical time can be flexibly adjusted according to the application scene, for example, the first historical time is within the past 5 years, the second historical time is within the past one month, and the third historical time is within the past one month.

[0070] In a possible implementation, the manner of obtaining the historical portrait data of the user based on the historical travel book data of the user can be that: the historical travel book data of the user is tagged based on the label list to obtain the attribute of the label corresponding to each historical travel book in the historical travel book data; the attribute of the label corresponding to each historical travel book is statistically analyzed to obtain the attribute of the label corresponding to the user; and the historical portrait data of the user is obtained according to at least one of the value and the weight of the attribute included in the label list.

[0071] Therefore, the historical portrait data can include at least one of the value or the weight and the attribute corresponding to at least one label, and the at least one label includes the number of days, the mileage, the region, the season, the festival, the number of scenic spots, the price or the play duration. For example, the label list can be as shown in Table 1, where the attribute type corresponding to each label can be flexibly adjusted according to the application scenario, for example, the region can be divided according to the provincial level or the municipal level.

[0072] The process of tagging the historical travel book data of the user based on the label list shown in Table 1 is that: the historical travel book data of the user is matched according to each attribute type in each attribute type of each label, and the attribute type that is successfully matched is taken as the attribute of the label of the historical user portrait of the user. For example, for the festival label, if the number of times of travel in the historical travel book data of the user on Labor Day is greater than the number of times of travel on attributes other than Labor Day in the attribute type of the festival, it is determined that the attribute of the user for the festival is Labor Day.

[0073] Table 1

[0074]

[0075] Table 2

[0076] Label Days Mileage Region Season Holiday Number of attractions Price Play duration Value 1 1 1 2 1 1 1 1 Weight 20％ 20％ 10％ 10％ 10％ 10％ 10％ 10％ Attribute 3-5 days >500km Shanghai Spring Labor Day >＝3 50-100 yuan 2-3h

[0077] For example, the obtained historical user portrait of the user can be as shown in Table 2, where the value of the label represents the score when the reference travel book hits the label, the higher the score, the higher the recommended value, and the greater the possibility of being recommended, and the weight of the label represents the importance of the label for the recommended travel book, the greater the weight, the more important. Optionally, the value and the weight of each label can be flexibly adjusted according to the application scenario. It can be understood that when the number of at least one label included in the historical portrait data is 1, the historical user portrait only needs to include the value of the label, and when the number of at least one label included in the historical portrait data is multiple, the historical user portrait includes the value of each label and the weight of each label.

[0078] In a possible implementation, the manner of obtaining the historical operation data of the user based on at least one of the historical click data or the historical search data of the user can be that, the at least one of the historical click data or the historical search data of the user is analyzed and counted according to the attribute category of each label in the label list, to obtain at least one of the operation times or the operation time of the user for each attribute of each label.

[0079] For example, if at least one of the historical click data or the historical search data of the user indicates that the user searched 3 times for the attribute category of 3-5 days in the label days 3 days ago, the historical operation data of the user includes that the operation times for 3-5 days is 3 and the operation time is 3 days ago. The operation times can represent the strength of the active intention of the user for the operation, and the greater the times, the greater the strength, that is, the operation times are positively correlated with the strength of the active intention of the user for the operation. The operation time can represent the timeliness of the operation of the user, and the longer the time, the worse the timeliness, that is, the operation time is negatively correlated with the timeliness of the operation of the user.

[0080] In step 202, a plurality of reference travel books are obtained, and recommended values corresponding to the plurality of reference travel books are determined based on the historical portrait data and the historical operation data.

[0081] In the embodiments of the present application, the manner of obtaining the plurality of reference travel books can be that, search data of the user is obtained, and a plurality of reference travel books matching the search data are obtained from a travel book database; or the manner of obtaining the plurality of reference travel books can also be that, a plurality of reference travel books matching the historical portrait data are obtained from the travel book database. The travel book database includes a large number of historical travel books, and the historical travel books in the travel book database can be obtained by experienced travel experts or travel agencies, or can be obtained by a large number of users in the use process, or can be obtained by the system according to big data.

[0082] For example, the search data can be obtained through the input information of the user, or the search data can be obtained through the selection operation of the user on the displayed label attributes, and when the search data includes attribute 1 of label 1 and attribute 2 of label 2, the historical travel books in the travel book database corresponding to attribute 1 of label 1 and attribute 2 of label 2 are taken as the plurality of reference travel books matching the search data.

[0083] For another example, when the historical portrait data includes the attributes of each of the at least one label, the historical travel books in the travel book database matching the attributes of the first number of labels in the historical portrait data are taken as the plurality of reference travel books matching the historical portrait data, wherein the first number can be the number of all labels or the number of part of the labels.

[0084] In a possible implementation, determining the recommended value corresponding to each of the plurality of reference route books based on the historical portrait data and the historical operation data comprises: for any reference route book in the plurality of reference route books, matching the reference route book with the attribute of at least one label to obtain a target label that is matched successfully; and obtaining the recommended value corresponding to the reference route book based on at least one of the value or the weight corresponding to the target label and the historical operation data.

[0085] For example, taking the historical portrait data shown in Table 2 as an example, any reference route book is matched with the attribute of each label in Table 2. If the feature of any reference route book for each label meets the corresponding attribute, the matching is successful, and the matching success is taken as a target label. The recommended value corresponding to any reference route book is obtained based on the value and the weight corresponding to the target label and the historical operation data.

[0086] Optionally, obtaining the recommended value corresponding to any reference route book based on at least one of the value or the weight corresponding to the target label and the historical operation data comprises: when the number of target labels is a plurality, for any target label, the historical operation data comprises at least one of the operation times or the operation time for the attribute corresponding to the target label; obtaining the recommended value corresponding to any target label based on at least one of the value and the weight corresponding to the target label, at least one of the operation times or the operation time, at least one of a times decay factor or a time decay factor; and obtaining the recommended value corresponding to any reference route book according to the recommended values corresponding to the plurality of target labels respectively.

[0087] For example, obtaining the recommended value corresponding to any target label based on at least one of the value and the weight corresponding to the target label, at least one of the operation times or the operation time, at least one of a times decay factor or a time decay factor comprises, but is not limited to, the following three ways.

[0088] For example, the recommended value corresponding to any target label is obtained according to the following formula (1).

[0089] Score(i)=C*weigh+α*num Formula (1)

[0090] wherein Score(i) represents the recommended value corresponding to any target label, i is a positive integer representing the serial number of the target label, C represents the value corresponding to any target label, weigh represents the weight corresponding to any target label, a represents a times decay factor, and num represents the operation times. The times decay factor can be flexibly adjusted according to the application scenario, and the embodiments of the present application are not limited. Thus, the operation times and the times decay factor are used to make the obtained recommended value not only meet the historical portrait data of the user, but also meet the active intention of the user, thereby improving the accuracy of route book recommendation.

[0091] In the second way, the recommended value corresponding to any target label is obtained based on the value and weight corresponding to the target label, the operation time, and the time decay factor. For example, the recommended value corresponding to any target label is obtained according to formula (2) as follows.

[0092] Score(i) = C * weigh * β formula (2)

[0093] wherein β represents the time decay factor, which is obtained based on the operation time. For example, the time decay factor β is (1-tim), and tim is the operation time. Thus, the recommended value obtained has high timeliness in addition to meeting the historical profile data of the user, thereby improving the accuracy of the road book recommendation.

[0094] In the third way, the recommended value corresponding to any target label is obtained based on the value and weight corresponding to the target label, the operation time, and the time decay factor. For example, the recommended value corresponding to any target label is obtained according to formula (3) as follows.

[0095] Score(i) = (C * weigh + α * num) β formula (3)

[0096] Thus, the recommended value is obtained by combining the ways of formula (1) and formula (2), so that the above beneficial effects are simultaneously achieved, i.e., the active intention of the user is met, and the recommended value has high timeliness, thereby further improving the accuracy of the road book recommendation.

[0097] In addition, for a certain target label, when the historical operation data does not include at least one of the operation time or the operation number corresponding to the attribute of the certain target label, the recommended value corresponding to any target label can be directly obtained based on the value and weight corresponding to the certain target label. For example, the product of the value and weight corresponding to the certain target label is taken as the recommended value corresponding to any target label.

[0098] Optionally, the way of obtaining the recommended value corresponding to any reference road book according to the recommended values corresponding to the plurality of target labels can be that the sum of the recommended values corresponding to the plurality of target labels is taken as the recommended value corresponding to any reference road book; or the weighted sum of the recommended values corresponding to the plurality of target labels is taken as the recommended value corresponding to any reference road book.

[0099] Exemplarily, taking the historical profiling data shown in Table 2 above as an example, if the target tags of a certain reference travel book matching the historical profiling data shown in Table 2 include days, mileage, region, season, festival, number of scenic spots, price, and play duration, and the historical operation data includes 3 times of operation number for days of 3-5 days and 3 days ago of operation time, and 3 times of operation number for mileage of > 500 kilometers (km) and 3 days ago of operation time, then the recommended value corresponding to the certain reference travel book can be: (1*0.2+7*0.5)(1-0.3)+(1*0.2+7*0.5)(1-0.3)+1*0.1+2*0.1+1*0.1+1*0.1+1*0.1+1*0.1=6.88.

[0100] In step 203, at least one reference travel book in the plurality of reference travel books whose recommended value satisfies the recommendation condition is recommended.

[0101] In the embodiments of the present application, the recommendation condition is that the recommended value is greater than the recommendation threshold, and the recommendation threshold can be flexibly adjusted according to the application scenario or set according to experience; or, when the recommended values are sorted in descending order, the recommendation condition is that the recommended value is ranked in the top N positions in the order of recommended values; or, when the recommended values are sorted in ascending order, the recommendation condition is that the recommended value is ranked in the last N positions in the order of recommended values, and N is a positive integer.

[0102] In a possible implementation, the at least one reference travel book in the plurality of reference travel books whose recommended value satisfies the recommendation condition is recommended, including: the at least one reference travel book in the plurality of reference travel books whose recommended value satisfies the recommendation condition is displayed in order of recommended values. Thus, the user can intuitively obtain the recommended travel book through the display by order, improving the user experience.

[0103] After the at least one reference travel book in the plurality of reference travel books whose recommended value satisfies the recommendation condition is recommended, if the user is not satisfied with the recommended at least one reference travel book, for example, when the at least one reference travel book is not selected, a corresponding custom travel book can also be automatically generated for the user for recommendation, i.e., the reference travel book in the travel book database is no longer used.

[0104] Optionally, a plurality of custom travel books are generated based on the historical profiling data, any custom travel book in the plurality of custom travel books matches the attributes of each of the at least one tag included in the historical profiling data, and the distance between the location of the first scenic spot included in any custom travel book in the plurality of custom travel books and the location of the user satisfies a distance condition; the plurality of custom travel books are recommended. The distance condition can be that the distance between the location of the first scenic spot included in each of the plurality of custom travel books and the location of the user is the smallest.

[0105] Therefore, the travel book can be generated in a self-defined manner to meet the needs of the user, so as to make up for the case that the user cannot find a desired travel book in the reference travel book, make the travel book recommendation method more flexible, make the recommended travel book more accurate, increase the probability of the user selecting a desired travel book, and effectively improve the user experience.

[0106] In addition, the embodiments of the present application also provide a bottom-up strategy, that is, when the user is a first-time login user, since the historical portrait data is not included, a plurality of first reference travel books matching the current city of the user login can be recalled in the travel book database, secondly, a plurality of second reference travel books matching the current season are recalled in the plurality of first reference travel books, and finally, a recommendation value of the plurality of second reference travel books is calculated, the second reference travel books in the first N positions are recommended according to the size of the recommendation value.

[0107] Among them, for any reference travel book, the calculation method of the recommendation value of the travel book in the bottom-up strategy can be: (the completed number of any reference travel book x 1000 + the number of click-initiated navigation of any reference travel book x 400 + the number of click-collection of any reference travel book x 200 + the number of click-viewing of any reference travel book x 20 + 20) / (the number of exposure of any reference travel book + 10) x 0.5 ^ [(current date - the listing date of any reference travel book) / 90].

[0108] Exemplarily, referring to Figure 3 , Figure 3 A schematic diagram of a travel book recommendation model provided by the embodiments of the present application. A large amount of historical travel book data and historical operation data of users are collected in the database, and the T+1 form of offline calculation mode is used to calculate the labels of different users in real time through ETL (Extract-Transform-Load, extract-transform-load), and the data synchronization mode is used to provide services. Among them, ETL is a data warehouse technology. T+1 form refers to the data of today is calculated tomorrow. For example, the label features of the user are obtained by taking the ID of the user as the unique identifier, and are synchronized to the ES (Elasticsearch, elastic research) service. The ES service is a distributed, highly scalable, and highly real-time search and data analysis engine, which can easily make a large amount of data have the ability of search, analysis and exploration.

[0109] Optionally, when the user inputs the search data, a plurality of reference route books matching the search data can be acquired, and then the relevant data of the user can be pulled from the ES service. When the historical portrait data and the historical operation data of the user are pulled, the recommendation value of each reference route book is calculated based on the historical portrait data and the historical operation data of the user. When the historical portrait data and the historical operation data of the user are not pulled, the recommendation value of each reference route book is calculated based on a bottom-up strategy. Finally, the route books can be displayed in order of the size of the recommendation value, for example, the top N reference route books with the largest recommendation value are displayed on the display interface in order of the recommendation value from large to small.

[0110] The route book recommendation method provided by the embodiments of the present application generates the historical portrait data of the user based on the historical route book data of the user, and matches the filtered reference route books for the user based on the historical portrait data of the user, so that the recommended route books are based on the historical data of the user and are more in line with the travel habits of the user. Secondly, the historical operation data of the user is used to calculate the recommendation value, so that the recommended route books take into account the active intention of the user. Moreover, the decay strategy is used to ensure the timeliness of the historical portrait data of the user, so that the user can quickly find the route books that meet the preferences of the user.

[0111] Referring to Figure 4 The embodiments of the present application provide a route book recommendation device, which comprises:

[0112] The first acquisition module 401 is configured to acquire the historical portrait data and the historical operation data of the user. The historical portrait data of the user is acquired based on the historical route book data of the user, and the historical operation data is acquired based on at least one of the historical click data or the historical search data of the user.

[0113] The second acquisition module 402 is configured to acquire a plurality of reference route books.

[0114] The determination module 403 is configured to determine the recommendation value corresponding to each of the plurality of reference route books based on the historical portrait data and the historical operation data.

[0115] The recommendation module 404 is configured to recommend at least one reference route book in the plurality of reference route books that meets a recommendation condition.

[0116] In a possible implementation, the second acquisition module 402 is configured to acquire the search data of the user, and acquire a plurality of reference route books matching the search data in the route book database; or acquire a plurality of reference route books matching the historical portrait data in the route book database.

[0117] In a possible implementation, the historical portrait data includes at least one of a value or a weight corresponding to each of the at least one label and the attribute, and the at least one label includes a day number, a mileage, a region, a season, a festival, a number of scenic spots, a price, or a play duration.

[0118] The determining module 403 is configured to, for any reference travel book in the plurality of reference travel books, match the any reference travel book with the attribute of the at least one label to obtain a target label that is matched successfully, and obtain a recommended value corresponding to the any reference travel book based on at least one of a value or a weight corresponding to the target label and the historical operation data.

[0119] In a possible implementation, when the number of target labels is a plurality, for any target label, the historical operation data includes at least one of an operation number or an operation time for the attribute corresponding to the any target label.

[0120] The determining module 403 is configured to obtain a recommended value corresponding to any target label based on at least one of a value and a weight corresponding to the any target label, at least one of an operation number or an operation time, at least one of a number decay factor or a time decay factor, and obtain a recommended value corresponding to any reference travel book according to recommended values corresponding to a plurality of target labels respectively.

[0121] In a possible implementation, the determining module 403 is configured to obtain a recommended value corresponding to any target label based on at least one of a value and a weight corresponding to the any target label, at least one of an operation number or an operation time, at least one of a number decay factor or a time decay factor, according to the following formula:

[0122] Score(i)=(C*weigh+α*num)β;

[0123] wherein Score(i) represents a recommended value corresponding to any target label, C represents a value corresponding to any target label, weigh represents a weight corresponding to any target label, α represents a number decay factor, num represents an operation number, β represents a time decay factor, and the time decay factor is obtained based on an operation time.

[0124] In a possible implementation, the recommending module 404 is configured to display, in an order of recommended values, at least one reference travel book in the plurality of reference travel books, which has a recommended value greater than a recommended threshold value or a recommended value in a front N position in the order of recommended values, where N is a positive integer.

[0125] In a possible implementation, the apparatus further includes:

[0126] The self-defined module is configured to generate a plurality of self-defined route books based on the historical portrait data, any self-defined route book in the plurality of self-defined route books matches attributes corresponding to each of at least one label included in the historical portrait data, and a distance between a location of a first scenic spot included in any self-defined route book in the plurality of self-defined route books and a location of the user satisfies a distance condition;

[0127] The recommendation module 404 is further configured to recommend the plurality of self-defined route books.

[0128] The route book recommendation apparatus provided by the embodiments of the present application generates historical portrait data of a user based on historical route book data of the user, and matches the filtered reference route books to the user based on the historical portrait data of the user, so that the recommended route books are based on the historical data of the user and are more in line with the travel habits of the user. Secondly, the historical operation data of the user is used to calculate the recommendation value, so that the recommended route books take into account the active intention of the user. Moreover, a decay strategy is used to ensure the timeliness of the historical portrait data of the user, so that the user can quickly find route books that meet the preferences of the user.

[0129] It should be understood that the apparatus provided by the above embodiments is only exemplified by the division of the above functional modules when realizing its functions, and in actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions. In addition, the apparatus and method embodiments provided by the above embodiments belong to the same concept, and the specific implementation process is described in detail in the method embodiments, which will not be described here.

[0130] Please refer to Figure 5 which shows a structural schematic diagram of a computer device provided by an embodiment of the present application. The computer device can be a terminal, for example, can be: a smart phone, a tablet computer, a vehicle-mounted terminal, a notebook computer or a desktop computer. The terminal can also be referred to as a user equipment, a portable terminal, a laptop terminal, a desktop terminal, and other names.

[0131] Generally, the terminal includes a processor 701 and a memory 702.

[0132] The processor 701 can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 701 can be implemented in at least one of a hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), a PLA (Programmable Logic Array). The processor 701 can also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state, also known as a CPU (Central Processing Unit), and the coprocessor being a low-power processor for processing data in a standby state. In some embodiments, the processor 701 can be integrated with a GPU (Graphics Processing Unit) for rendering and drawing content required to be displayed by the display screen. In some embodiments, the processor 701 can further include an AI (Artificial Intelligence) processor for processing machine learning related computing operations.

[0133] The memory 702 can include one or more computer-readable storage media that can be non-transitory. The memory 702 can also include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 702 is used to store at least one instruction for being executed by the processor 701 to implement the route book recommendation method provided by the method embodiments in the present application.

[0134] In some embodiments, the terminal can also optionally include a peripheral device interface 703 and at least one peripheral device. The processor 701, the memory 702, and the peripheral device interface 703 can be connected through a bus or a signal line. Each peripheral device can be connected to the peripheral device interface 703 through a bus, a signal line, or a circuit board. Specifically, the peripheral device includes at least one of a radio frequency circuit 704, a display screen 705, a camera assembly 706, an audio circuit 707, and a power supply 709.

[0135] The peripheral interface 703 can be used to connect at least one I / O (Input / Output) related peripheral device to the processor 701 and the memory 702. In some embodiments, the processor 701, the memory 702 and the peripheral interface 703 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 701, the memory 702 and the peripheral interface 703 can be implemented on a separate chip or circuit board, and the present embodiments are not limited in this regard.

[0136] The radio frequency circuit 704 is configured to receive and send RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 704 communicates with communication networks and other communication devices through electromagnetic signals. The radio frequency circuit 704 converts electric signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electric signals. Optionally, the radio frequency circuit 704 includes an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and the like. The radio frequency circuit 704 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: a metropolitan area network, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network, and / or a wireless fidelity (WiFi) network. In some embodiments, the radio frequency circuit 704 can also include NFC (Near Field Communication) related circuitry, and the present application is not limited in this regard.

[0137] The display screen 705 is configured to display a UI (User Interface). The UI can include graphics, text, icons, video, and any combination thereof. When the display screen 705 is a touch display screen, the display screen 705 is further configured to capture touch signals on or above the surface of the display screen 705. The touch signals can be input to the processor 701 as control signals for processing. In this case, the display screen 705 can also be configured to provide virtual buttons and / or virtual keyboard, also known as soft buttons and / or soft keyboard. In some embodiments, the display screen 705 can be one, disposed on the front panel of the terminal; in other embodiments, the display screen 705 can be at least two, respectively disposed on different surfaces of the terminal or in a folding design; in still other embodiments, the display screen 705 can be a flexible display screen, disposed on a curved surface or a folding surface of the terminal. Even, the display screen 705 can also be disposed in an irregular shape, i.e., a special-shaped screen. The display screen 705 can be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), etc.

[0138] The camera assembly 706 is configured to capture images or videos. Optionally, the camera assembly 706 includes a front camera and a rear camera. Typically, the front camera is disposed on the front panel of the terminal, and the rear camera is disposed on the back of the terminal. In some embodiments, the rear camera is at least two, respectively any one of a main camera, a depth-of-field camera, a wide-angle camera, and a telephoto camera, to realize the background blur function by fusing the main camera and the depth-of-field camera, the panoramic shooting and VR (Virtual Reality) shooting function by fusing the main camera and the wide-angle camera, or other fusion shooting functions. In some embodiments, the camera assembly 706 can further include a flash. The flash can be a single-color-temperature flash or a dual-color-temperature flash. The dual-color-temperature flash refers to the combination of a warm light flash and a cold light flash, which can be used for light compensation under different color temperatures.

[0139] The audio circuit 707 can include a microphone and a speaker. The microphone is used to collect sound waves of the user and the environment, and convert the sound waves into an electrical signal input to the processor 701 for processing, or input to the radio frequency circuit 704 to realize voice communication. For the purpose of stereo sound collection or noise reduction, the microphone can be multiple, respectively arranged at different parts of the terminal. The microphone can also be an array microphone or an omnidirectional collection type microphone. The speaker is used to convert the electrical signal from the processor 701 or the radio frequency circuit 704 into sound waves. The speaker can be a traditional diaphragm speaker, or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only can it convert electrical signals into sound waves that humans can hear, but it can also convert electrical signals into sound waves that humans cannot hear for ranging purposes. In some embodiments, the audio circuit 707 can also include a headphone jack.

[0140] The power supply 709 is used to supply power to various components in the terminal. The power supply 709 can be alternating current, direct current, disposable battery or rechargeable battery. When the power supply 709 includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0141] In some embodiments, the terminal also includes one or more sensors 710. The one or more sensors 710 include but are not limited to: an acceleration sensor 711, a gyroscope sensor 712, a pressure sensor 713, an optical sensor 715, and a proximity sensor 716.

[0142] The acceleration sensor 711 can detect the acceleration in three coordinate axes of the coordinate system established by the terminal. For example, the acceleration sensor 711 can be used to detect the components of gravitational acceleration in three coordinate axes. The processor 701 can control the display screen 705 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 711. The acceleration sensor 711 can also be used for game or user motion data collection.

[0143] The gyroscope sensor 712 can detect the body orientation and rotation angle of the terminal. The gyroscope sensor 712 can cooperate with the acceleration sensor 711 to collect 3D actions of the user on the terminal. The processor 701 can realize the following functions according to the data collected by the gyroscope sensor 712: motion sensing (such as changing the UI according to the user's tilt operation), image stabilization when shooting, game control, and inertial navigation.

[0144] The pressure sensor 713 can be disposed at the side frame of the terminal and / or under the display screen 705. When the pressure sensor 713 is disposed at the side frame of the terminal, the holding signal of the user to the terminal can be detected, and the left-hand or right-hand recognition or the shortcut operation can be performed by the processor 701 according to the holding signal collected by the pressure sensor 713. When the pressure sensor 713 is disposed under the display screen 705, the operability control on the UI interface can be controlled by the processor 701 according to the pressure operation of the user to the display screen 705. The operability control includes at least one of the button control, the scroll bar control, the icon control, and the menu control.

[0145] The optical sensor 715 is used to collect the ambient light intensity. In an embodiment, the processor 701 can control the display brightness of the display screen 705 according to the ambient light intensity collected by the optical sensor 715. Specifically, when the ambient light intensity is high, the display brightness of the display screen 705 is increased; when the ambient light intensity is low, the display brightness of the display screen 705 is decreased. In another embodiment, the processor 701 can also dynamically adjust the shooting parameter of the camera assembly 706 according to the ambient light intensity collected by the optical sensor 715.

[0146] The proximity sensor 716, also called the distance sensor, is usually disposed at the front panel of the terminal. The proximity sensor 716 is used to collect the distance between the user and the front of the terminal. In an embodiment, when the proximity sensor 716 detects that the distance between the user and the front of the terminal gradually decreases, the display screen 705 is switched from the bright screen state to the off-screen state by the processor 701; when the proximity sensor 716 detects that the distance between the user and the front of the terminal gradually increases, the display screen 705 is switched from the off-screen state to the bright screen state by the processor 701.

[0147] Those skilled in the art can understand that the structure shown in the above embodiments is not a limitation on the computer device, and the computer device can include more or less components than the structure shown in the above embodiments, or combine certain components, or adopt a different component arrangement. Figure 5 The structure shown in the above embodiments is not a limitation on the computer device, and the computer device can include more or less components than the structure shown in the above embodiments, or combine certain components, or adopt a different component arrangement.

[0148] Please refer to Figure 6 , Figure 6is a structural schematic diagram of a server provided by an embodiment of the present application. The server 600 can have great differences due to different configurations or performances, and can include one or more processors 601 and one or more memories 602, wherein the one or more memories 602 store at least one program instruction, the at least one program instruction is loaded and executed by the one or more processors 601 to implement the route book recommendation method provided by each method embodiment described above. Of course, the server 600 can also have a wired or wireless network interface, a keyboard, and an input and output interface and other components for realizing the functions of the device, and the details are not described here.

[0149] In an exemplary embodiment, a computer device is also provided, which includes a processor and a memory having at least one program code stored therein. The at least one program code is loaded and executed by one or more processors to enable the computer device to implement any of the route book recommendation methods described above.

[0150] In an exemplary embodiment, a computer readable storage medium is also provided, which stores at least one program code. The at least one program code is loaded and executed by a processor of a computer device to enable the computer to implement any of the route book recommendation methods described above.

[0151] Optionally, the computer readable storage medium described above can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0152] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to perform any of the route book recommendation methods described above.

[0153] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0154] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application are authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the search data of target users involved in this application were obtained with full authorization.

[0155] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A route recommendation method, characterized in that, The method includes: The system acquires the user's historical profile data and historical operation data. The user's historical profile data is obtained based on the user's historical route data, and the historical operation data is obtained based on at least one of the user's historical click data or historical search data. The historical profile data includes at least one value or weight corresponding to at least one tag, as well as attributes. The at least one tag includes number of days, mileage, region, season, holiday, number of attractions, price, or duration of play. Obtain multiple reference routes. For any one of the multiple reference routes, match the attribute of any one reference route with the attribute of at least one tag to obtain the target tag that is successfully matched. When there are multiple target tags, for any target tag, the historical operation data includes at least one of the number of operations or the operation time for the attribute corresponding to that target tag; based on the value and weight corresponding to that target tag, at least one of the number of operations or the operation time, and at least one of the number of operations decay factor or the time decay factor, the recommendation value corresponding to that target tag is obtained according to the following formula: Score(i)=(C*weigh+α*num)β; Wherein, Score(i) represents the recommended value corresponding to any target label, C represents the value corresponding to any target label, weight represents the weight corresponding to any target label, α represents the number of times decay factor, num represents the number of operations, β represents the time decay factor, and the time decay factor is obtained based on the operation time; The recommendation value corresponding to any one of the reference roadbooks is obtained based on the recommendation values ​​corresponding to multiple target tags; Recommend at least one reference route whose recommended value meets the recommendation criteria from the multiple reference route lists.

2. The method according to claim 1, characterized in that, The acquisition of multiple reference road books includes: Obtain the user's search data, and retrieve multiple reference routes matching the search data from the route database; or, Retrieve multiple reference routes from the route database that match the historical profile data.

3. The method according to claim 1 or 2, characterized in that, The step of recommending at least one reference route whose recommendation value meets the recommendation criteria from the plurality of reference route routes includes: At least one of the reference routes whose recommended value is greater than the recommended threshold or whose recommended value ranks in the top N in the order of recommended values ​​is displayed in the order of recommended values, where N is a positive integer.

4. The method according to claim 1 or 2, characterized in that, After recommending at least one reference route whose recommendation value meets the recommendation criteria from the plurality of reference route routes, the method further includes: Multiple custom route books are generated based on the historical profile data. Any custom route book in the multiple custom route books matches the attribute corresponding to each of the at least one tag included in the historical profile data, and the distance between the location of the first scenic spot included in any custom route book in the multiple custom route books and the location of the user satisfies the distance condition. The multiple custom route plans will be recommended.

5. A route recommendation device, characterized in that, The device includes: The first acquisition module is used to acquire the user's historical profile data and historical operation data. The user's historical profile data is obtained based on the user's historical route data, and the historical operation data is obtained based on at least one of the user's historical click data or historical search data. The historical profile data includes at least one value or weight corresponding to at least one tag and attributes. The at least one tag includes number of days, mileage, region, season, festival, number of attractions, price, or duration of play. The second acquisition module is used to acquire multiple reference road books; A determination module is used to match any reference roadbook among the plurality of reference roadbooks with the attributes of at least one tag to obtain a successfully matched target tag; when there are multiple target tags, for any target tag, the historical operation data includes at least one of the number of operations or the operation time for the attribute corresponding to the target tag; based on the value and weight corresponding to the target tag, at least one of the number of operations or the operation time, and at least one of the number of operations decay factor or the time decay factor, the recommendation value corresponding to the target tag is obtained according to the following formula: Score(i)=(C*weigh+α*num)β; where Score(i) represents the recommendation value corresponding to the target tag, C represents the value corresponding to the target tag, weight represents the weight corresponding to the target tag, α represents the number of operations decay factor, num represents the number of operations, and β represents the time decay factor, which is obtained based on the operation time; the recommendation value corresponding to any reference roadbook is obtained according to the recommendation values ​​corresponding to the plurality of target tags respectively. The recommendation module is used to recommend at least one reference route whose recommendation value meets the recommendation criteria from the plurality of reference route routes.

6. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one computer program or instruction, the at least one computer program or instruction being loaded and executed by the processor to enable the computer device to implement the route recommendation method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to enable the computer to implement the route recommendation method as described in any one of claims 1 to 4.

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