Method and device for generating object combination, electronic equipment and readable medium

Abstract

The invention discloses a method and device for generating an object combination, electronic equipment and a readable medium, and the method comprises the steps: determining a category to which each object belongs according to the category information of each object; at least one object combination is generated according to a category association relationship library and the category to which each object belongs, and each category association relationship in the category association relationship library comprises at least two categories which are determined based on historical interaction result information and meet a combination condition, the interaction result information is used for reflecting the historical interaction condition between the at least two categories, and the category to which the at least two objects included in each object combination in the at least one object combination belong is matched with one category association relationship in the category association relationship library. Thus, manual object matching by workers is not needed, the purpose of automatically generating the object combination can be achieved through the automatic matching function integrated in the background of the management platform, convenience is brought to the workers, and the quality of the automatically generated object combination can also be guaranteed.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device, electronic device and readable medium for generating an object combination. Background Art

[0002] With the development of Internet technology, people can operate online objects through online behaviors, and staff can also better display objects to people through editing, management, etc. For example, online store staff can display the goods and / or services in the online store through editing, management, etc., and users can browse, collect or purchase the goods and / or services in the online store.

[0003] Currently, staff can manually combine multiple objects on the line into an object combination on an online management platform (hereinafter referred to as the management platform), and display the object combination to people, who can browse, view and even purchase the object combination online.

[0004] However, the manual matching of object combinations by the staff is not convenient enough for the staff, and the matched object combinations are also of varying quality. The purpose of optimizing the online marketing situation cannot be achieved by matching object combinations. Summary of the invention

[0005] In order to solve the above technical problems, the present application provides a method, device, electronic device and readable medium for generating object combinations, which can automatically and intelligently generate object combinations, which not only facilitates the staff, but also ensures the quality of the automatically generated object combinations, thereby making it possible to optimize online marketing situations.

[0006] In order to achieve the above objectives, the technical solutions provided by this application are as follows:

[0007] In a first aspect, the present application provides a method for generating an object combination, comprising:

[0008] According to the category information of each object, determine the category to which each object belongs;

[0009] At least one object combination is generated based on a category association relationship library and the categories to which each object belongs, wherein each category association relationship in the category association relationship library includes at least two categories that meet a combination condition determined based on historical interaction result information, and the interaction result information is used to reflect the historical interaction between the at least two categories, and the categories to which the at least two objects included in each object combination in the at least one object combination belong match a category association relationship in the category association relationship library.

[0010] In a possible implementation, the category association relationship library includes a first category association relationship, the first category association relationship includes a first category and a second category, and generating at least one object combination according to the category association relationship library and the category to which each object belongs includes:

[0011] Determine a first object set consisting of objects belonging to the first category among the objects;

[0012] Determine a second object set consisting of objects belonging to the second category among the objects;

[0013] The at least one object combination is generated according to the first object set and the second object set, and each object combination in the at least one object combination includes any one object in the first object set and any one object in the second object set.

[0014] In a possible implementation, the process of constructing the category association relationship library includes:

[0015] According to the interaction behavior between the object of the third category and the category of other objects, the interaction result information corresponding to the third category is obtained, and the interaction result information corresponding to the third category includes the number of positive interactions and the reverse interaction ratio between the third category and the other categories, the positive interaction refers to the time when the same user interacts with the object belonging to the third category at a preset time before the time when the user interacts with the object belonging to the other category, and the interaction corresponding to the object belonging to the third category and the interaction corresponding to the object belonging to the other category are two adjacent interaction behaviors, the reverse interaction ratio refers to the number of times that the previous interaction behavior before the interaction corresponding to the object belonging to the other category is the interaction behavior corresponding to the object belonging to the third category, and the ratio of the number of times that the interaction behavior corresponding to the object belonging to the third category occurs, and the interval time between the time when the interaction corresponding to the object belonging to the other category occurs and the time when the interaction corresponding to the object belonging to the third category occurs is less than or equal to the preset time;

[0016] determining, according to the number of positive interactions and the reverse interaction ratio, a fourth category that meets the combination condition with the third category, wherein the fourth category belongs to at least one of the other categories;

[0017] The third category and each of the fourth categories are recorded as a category association relationship in the category association relationship library.

[0018] As an example, determining, according to the number of positive interactions and the reverse interaction ratio, a fourth category that meets the combination condition with the third category includes:

[0019] Determining, according to the number of positive interactions and the reverse interaction ratio, an association weight between the third category and each of the other categories;

[0020] According to the association weights of the other categories, the fourth category that meets the combination condition is determined, and the combination condition includes: a preset number of the other categories with the largest association weights, or, the other categories with association weights greater than a preset weight threshold are determined as the fourth category.

[0021] As another example, determining the fourth category that satisfies the combination condition according to the association weights of the other categories includes:

[0022] If there is a fifth category in the other categories whose proportion is greater than or equal to the preset proportion threshold, the fourth category satisfying the combination condition is determined from the fifth category.

[0023] In a possible implementation manner, objects in the at least one object combination all belong to the same entity.

[0024] In a possible implementation, the method further includes:

[0025] According to the association degree of each object combination in the at least one object combination, a collocation score of each object combination in the at least one object is determined, the association degree of the object combination represents the proportion or number of times that the objects belonging to the object combination in the target entity are marketed in combination, and the collocation score is used to guide the display and / or publication of the corresponding object combination.

[0026] In a second aspect, the present application also provides a device for generating an object combination, including:

[0027] A determination unit, used to determine the category to which each object belongs according to the category information of each object;

[0028] A generating unit is used to generate at least one object combination according to a category association relationship library and the categories to which each object belongs, wherein each category association relationship in the category association relationship library includes at least two categories that meet a combination condition determined based on historical interaction result information, and the interaction result information is used to reflect the historical interaction between the at least two categories, and the categories to which the at least two objects included in each object combination in the at least one object combination belong match a category association relationship in the category association relationship library.

[0029] In a possible implementation, the category association relationship library includes a first category association relationship, the first category association relationship includes a first category and a second category, and the generating unit includes:

[0030] A first determining subunit, configured to determine a first object set consisting of objects belonging to the first category among the objects;

[0031] A second determining subunit is used to determine a second object set consisting of objects belonging to the second category among the objects;

[0032] A generating subunit is used to generate the at least one object combination according to the first object set and the second object set, each object combination in the at least one object combination includes any one object in the first object set and any one object in the second object set.

[0033] In a possible implementation, the device further includes: a construction unit;

[0034] The construction unit is used to construct a category association relationship library.

[0035] As an example, the construction unit includes:

[0036] A first obtaining subunit is configured to obtain interaction result information corresponding to the third category according to interaction behaviors between the objects of the third category and categories of other objects, wherein the interaction result information corresponding to the third category includes the number of positive interactions and the reverse interaction ratio between the third category and the other categories, wherein the positive interaction refers to the time at which the same user interacts with the objects belonging to the third category at a preset time before the time at which the user interacts with the objects belonging to the other categories, and the interaction corresponding to the objects belonging to the third category and the interaction corresponding to the objects belonging to the other categories are two adjacent interaction behaviors, and the reverse interaction ratio refers to the number of times that the previous interaction behavior before the interaction corresponding to the objects belonging to the other categories is the interaction behavior corresponding to the objects belonging to the third category, and the ratio of the number of times that the interaction behaviors corresponding to the objects belonging to the third category occur, and the interval between the time at which the interaction occurs with the objects belonging to the other categories and the time at which the interaction occurs with the objects belonging to the third category is less than or equal to the preset time;

[0037] a third determining subunit, configured to determine, according to the number of positive interactions and the reverse interaction ratio, a fourth category that meets the combination condition with the third category, wherein the fourth category belongs to at least one of the other categories;

[0038] The saving subunit is used to record the third category and each of the fourth categories as a category association relationship in the category association relationship library.

[0039] As an example, the third determining subunit includes:

[0040] A first determination module, configured to determine an association weight between the third category and each of the other categories according to the number of positive interactions and the reverse interaction ratio;

[0041] The second determination module is used to determine the fourth category that meets the combination condition according to the association weights of the other categories, and the combination condition includes: a preset number of the other categories with the largest association weights, or determining the other categories whose association weights are greater than a preset weight threshold as the fourth category.

[0042] As another example, the second determining module is specifically configured to:

[0043] If there is a fifth category in the other categories whose proportion is greater than or equal to the preset proportion threshold, the fourth category satisfying the combination condition is determined from the fifth category.

[0044] In a possible implementation manner, objects in the at least one object combination all belong to the same entity.

[0045] In a possible implementation manner, the device further includes:

[0046] A scoring unit is used to determine a collocation score for each object combination in the at least one object according to the correlation degree of each object combination in the at least one object combination, wherein the correlation degree of the object combination represents the proportion or number of times that the objects belonging to the object combination in the target entity are marketed in combination, and the collocation score is used to guide the display and / or publication of the corresponding object combination.

[0047] It should be noted that the specific implementation method of the device and the technical effects achieved can refer to the relevant description of the method provided in the first aspect or any implementation method of the first aspect.

[0048] In a third aspect, the present application further provides an electronic device, the electronic device comprising: a processor and a memory;

[0049] The memory is used to store instructions or programs;

[0050] The processor is used to execute the instructions or programs in the memory so that the electronic device executes the method provided by the first aspect or any one of the implementations of the first aspect.

[0051] In a fourth aspect, the present application further provides a readable medium, in which instructions or programs are stored. When the instructions or programs are executed on a processor, the processor executes the method provided in the first aspect or any one of the implementations of the first aspect.

[0052] Compared with the prior art, the embodiments of the present application have at least the following advantages:

[0053] In the technical solution provided by the present application, an automatic matching function is provided online. After the staff executes the function, the category to which each object belongs can be determined based on the category information of each object; at least one object combination is generated based on the category association relationship library and the category to which each object belongs. Each category association relationship in the category association relationship library includes at least two categories that meet the combination conditions determined based on historical interaction result information. The interaction result information is used to reflect the historical interaction between the at least two categories. The categories to which at least two objects included in each object combination in at least one object combination belong match a category association relationship in the category association relationship library. In this way, there is no need for staff to manually match objects. Thanks to the automatic matching function integrated in the background of the management platform, the staff only needs to use the automatic matching function, and the management platform can build and maintain a category association library based on the historical interactions between at least two categories reflected by the historical interaction result information, and automatically determine the object combination based on the matching results between the category to which each object belongs and the category association library. On the one hand, this achieves the purpose of automatically generating object combinations. On the other hand, since the category association library is determined by the historical interaction result information, using the category association library as a matching benchmark is a reliable data basis, which makes the quality of the generated object combination better, thereby making it possible to optimize online marketing. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0055] Figure 1 A flowchart of a method for generating an object combination provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of a process for constructing a category association relationship library provided in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of the structure of a device 300 for generating an object combination provided in an embodiment of the present application;

[0058] Figure 4 A schematic diagram of the structure of an electronic device 400 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0059] In some cases, users want to view and purchase multiple objects with specific relationships through online entities. For the convenience of users, online entities usually display multiple objects next to each other or as a combination of objects. The scenario where an online entity displays multiple objects as a combination of objects to users can be understood as the online entity performing a matching operation on multiple objects. For example, an online store can combine nursing pads, confinement caps, confinement shoes and other products in a maternity bag. For another example, an online store can combine shirts and trousers in a commuting suit combination.

[0060] At present, the staff of online entities usually manually enter the matched object combinations on the operation platform of the online entity according to their own experience or the sales data of each object. For example, the operation platform of an online store has a "product matching" function. The staff enters the editing page through "new matching" and creates a matching combination on the editing page by uploading the matching main picture, adding products, etc. After the matching combination passes the review, it can be released and put on the shelf for users to view and / or purchase. Although this process can facilitate users to view and / or purchase on the online entity, it is not very friendly to the staff of the online entity. On the one hand, the staff needs to perform complex editing and other operations on the objects they want to match. On the other hand, the quality of the object combination generated by the manual object matching of the staff cannot be guaranteed. In many cases, the object combination provided cannot meet the needs of users. Therefore, the current method of matching objects is time-consuming and labor-intensive and has little effect.

[0061] Based on this, an embodiment of the present application provides a method for generating an object combination. Taking the management platform of an online entity as an example, an automatic matching function is integrated in the background of the management platform, so that the management platform can provide the automatic matching function for the staff of the online entity. Taking the automatic matching demand of the staff of the online entity as an example, the device for generating an object combination can first determine the category to which each object belongs based on the category information of each object; then, based on the category association relationship library and the category to which each object belongs, at least one object combination is generated, each category association relationship in the category association relationship library includes at least two categories that meet the combination conditions based on historical interaction result information, and the interaction result information is used to reflect the historical interaction between the at least two categories. The categories to which at least two objects included in each object combination in at least one object combination belong match a category association relationship in the category association relationship library.

[0062] In this way, there is no need for staff to manually match objects. Thanks to the automatic matching function integrated in the background of the management platform, the staff only needs to use the automatic matching function, and the management platform can build and maintain a category association library based on the historical interactions between at least two categories reflected by the historical interaction result information, and automatically determine the object combination based on the matching results between the category to which each object belongs and the category association library. On the one hand, this achieves the purpose of automatically generating object combinations. On the other hand, since the category association library is determined by the historical interaction result information, using the category association library as a matching benchmark is a reliable data basis, which makes the quality of the generated object combination better, thereby making it possible to optimize online marketing.

[0063] It should be noted that the management platform of the online entity can be: a management platform page that the online entity can operate after logging in to the management platform provided by the e-commerce enterprise that hosts the online entity. The management platform can be in the form of a client or a web page.

[0064] It should be noted that the subject implementing the method of generating an object combination may be the device for generating an object combination provided in the embodiment of the present application. The device for generating an object combination may be carried in an electronic device or a functional module of an electronic device. Taking the scenario of the management platform of an online entity as an example, the device for generating an object combination may include the management platform of an online entity, or the device for generating an object combination may be connected to the management platform of an online entity; the electronic device may be installed with a client corresponding to the management platform of the online entity, or may access a webpage corresponding to the management platform of the online entity.

[0065] Figure 1 The present invention provides a method for generating an object combination according to an embodiment of the present invention. The method can be applied to a device for generating an object combination. The device for generating an object combination can be, for example, Figure 3 The device 300 for generating an object combination shown in the figure corresponds to the scenario of the management platform of the online entity. The device for generating an object combination may include the management platform of the online entity or be connected to the management platform of the online entity. Therefore, it can also be considered that the method is applied to the management platform of the online entity.

[0066] like Figure 1 As shown, the method may include, for example, the following S101 to S102:

[0067] S101, determining the category to which each object belongs according to the category information of each object.

[0068] It is understandable that the method can automatically match objects in a certain entity, so each object in S101 can refer to all or part of the objects in the target entity. If each object in S101 is a part of the objects in the target entity, then the method can also include: selecting objects to participate in automatic matching from all objects in the target entity, and the basis for the selection can be one or some information in the historical information of the object, such as sales quantity, browsing quantity, favorite quantity, etc.

[0069] In the embodiment of the present application, the management platform of the online entity has an operation item corresponding to the automatic matching function. By the staff's action on the operation item, it can be considered that the target operation has been performed on the management platform. The execution of the target operation triggers the background of the management platform to automatically match objects for the target entity corresponding to the staff. For example, the interface corresponding to the management platform of the online entity may include a "smart matching recommendation" button, and the "smart matching recommendation" button can correspond to the operation item corresponding to the automatic matching function on the management platform of the online entity. When the user clicks the "smart matching recommendation" button, it is equivalent to performing the target operation on the management platform, thereby triggering the management platform to execute the method.

[0070] In the process of automatically matching objects for the target entity in the background of the management platform, it is necessary to first obtain the category information of each object in the target entity as the data basis for matching. Category information can refer to information that can indicate the category to which the object belongs. For example, the category information can be the name of the category or the number of the category. For example, for the object lipstick, the category information can be "makeup", so that it can be determined that lipstick belongs to the category of "makeup"; for another example, for the object lipstick, the category information can also be "001", and "001" is the category number of "makeup", so that it can be determined that lipstick belongs to the category of "makeup".

[0071] S102, generating at least one object combination according to a category association relationship library and the categories to which each object belongs, wherein each category association relationship in the category association relationship library includes at least two categories that meet a combination condition determined based on historical interaction result information, and the interaction result information is used to reflect the historical interaction between the at least two categories, and the categories to which the at least two objects included in each object combination in the at least one object combination belong match a category association relationship in the category association relationship library.

[0072] In a possible implementation, S102 may include, for example: inputting the categories of each object included in the target entity into a collocation algorithm, and the collocation algorithm outputs at least one object combination of the target entity. The collocation algorithm may include a category association relationship library.

[0073] Taking online entities as an example, the objects involved in at least one object combination belong to the same online entity (i.e., the target entity). Among them, the online entity can refer to a store in an e-commerce enterprise, the object can correspond to the goods and / or services in the store, and the object combination is a combination of at least two goods and / or services in the store. For example, the target entity corresponds to the B flagship store on the A e-commerce enterprise, the object refers to the goods a1, a2, ..., a100 in the B flagship store, and the object combination can be a combination of at least two objects in a1, a2, ..., a100, such as a1+a3+a100, a2+a30, and a5+a33+a100, which can all be regarded as an object combination of the target entity B.

[0074] Among them, the category association library can be a database including multiple category associations that is pre-built and maintained based on historical interaction result information and combination conditions before executing S102. Each category association includes at least two categories, and the category association library is used to indicate at least two categories with collocation associations to determine the categories that can be combined in the target entity, thereby determining the possible object combinations in the target entity. According to the analysis of historical interaction result information, multiple categories in the same category association have a strong correlation, and the possibility of interaction is relatively high. For example, shirts, trousers and leather shoes can be included in a category association, and the correlation is reflected in professional suits; for another example, T-shirts and skirts can be included in another category association, and the correlation is reflected in common wear; however, vests and cotton shoes may not be maintained in a category association.

[0075] The historical interaction result information is determined by statistical analysis based on the historical interaction behavior data of each user, and reflects the historical interaction between at least two categories. The historical interaction situation may include the frequency and accuracy of the historical interaction. For example, the process of determining the interaction result information may include: for each user, statistically analyzing the historical interaction behaviors of objects belonging to different categories to obtain the interaction behavior sub-results of the user; and determining the interaction result information in combination with the interaction behavior sub-results of each user.

[0076] As an example, taking the case where the category association relationship library includes a first category association relationship, and the first category association relationship includes a first category and a second category, S102 may include: determining a first object set consisting of objects belonging to the first category among each object; determining a second object set consisting of objects belonging to the second category among each object; generating at least one object combination based on the first object set and the second object set, each object combination in the at least one object combination includes any one object in the first object set and any one object in the second object set. For example, the objects belonging to the first category in the target entity include object A, object B and object C, and the objects belonging to the second category in the target entity include object D, object E, object F and object G. Then, the generated object combinations may include: object combination 1 {object A, object D}, object combination 2 {object A, object E}, object combination 3 {object A, object F}, object combination 4 {object A, object G}, object combination 5 {object B, object D}, object combination 6 {object B, object E}, object combination 7 {object B, object F}, object combination 8 {object B, object G}, object combination 9 {object C, object D}, object combination 10 {object C, object E}, object combination 11 {object C, object F} and object combination 12 {object C, object G}.

[0077] As another example, taking the case where the category association relationship library includes a second category association relationship, and the second category association relationship includes a first category, a second category, and a third category, S102 may, for example, include: determining a first object set consisting of objects belonging to the first category among each object; determining a second object set consisting of objects belonging to the second category among each object; determining a third object set consisting of objects belonging to the third category among each object; generating the at least one object combination based on at least two object sets among the first object set, the second object set, and the third object set, wherein each object combination in the at least one object combination includes any one object corresponding to each of the at least two object sets participating in the combination. For example, the objects belonging to the first category in the target entity include object A and object B, the objects belonging to the second category in the target entity include object C, and the objects belonging to the third category in the target entity include object D and object E. Then, the generated object combinations may include: object combination 1 {object A, object C}, object combination 2 {object B, object C}, object combination 3 {object A, object D}, object combination 4 {object A, object E}, object combination 5 {object B, object D}, object combination 6 {object B, object E}, object combination 7 {object C, object D}, object combination 8 {object C, object E}, object combination 9 {object A, object C, object D}, object combination 10 {object A, object C, object E}, object combination 11 {object B, object C, object D} and object combination 12 {object B, object C, object E}.

[0078] In some implementations, during the construction of the category association library, it is necessary to use the full order database of the online platform as the data source to count orders within a preset period of time in the past. The longer the preset period, the richer the data basis for building the category association library, the more meaningful the analyzed interaction result information is, and the more reliable the resulting category association library is. Therefore, as an example, statistics can be taken for orders of all time in the past. In addition, the orders involved in the statistics can be any orders. In order to make the statistical results more accurate, normal payment orders that have not been canceled and have not applied for after-sales can also be screened out from all orders.

[0079] The process of building the category association library can be found in Figure 2As shown, it includes: S11, according to the interaction behavior between the object of the third category and the category of other objects, obtaining the interaction result information corresponding to the third category, the interaction result information corresponding to the third category includes the number of positive interactions and the reverse interaction ratio between the third category and the other categories, the positive interaction refers to the time when the same user interacts with the object belonging to the third category at a preset time before the time when the user interacts with the object belonging to the other category, and the interaction corresponding to the object belonging to the third category and the interaction corresponding to the object belonging to the other category are two adjacent interaction behaviors, and the reverse interaction ratio refers to the number of positive interactions between the third category and the other category. The number of interaction behaviors corresponding to the object of the third category whose previous interaction behavior is the ratio of the number of interaction behaviors corresponding to the object of the third category, and the interval time between the interaction time corresponding to the object of the other categories and the interaction time corresponding to the object of the third category is less than or equal to the preset time; S12, according to the number of positive interactions and the reverse interaction ratio, determine the fourth category that meets the combination condition with the third category, and the fourth category belongs to at least one category of the other categories; S13, record the third category and each of the fourth categories as a category association relationship in the category association relationship library. Among them, S12 may include, for example: S121, determine the association weight between the third category and each of the other categories according to the number of positive interactions and the reverse interaction ratio; S122, determine the fourth category that meets the combination condition according to the association weights of the other categories. The combination condition may include, for example: a preset number of the other categories with the largest association weight, or determining the other categories with association weights greater than a preset weight threshold as the fourth category. As an example, S122 may include, for example: if there is a fifth category in the other categories whose proportion is greater than or equal to a preset proportion threshold, determining the fourth category that meets the combination condition from the fifth category.

[0080] The size of the association weight can reflect the rationality of the combination of the category.

[0081] For example, taking commodities as an example, the same user buys a Category B commodity within a preset time (such as 24 hours) after purchasing a Category A commodity, and the user does not purchase other commodities between the purchases of Category A commodities and Category B commodities (that is, the purchases of Category A commodities and Category B commodities are two adjacent purchases), then it is considered that there is an AB category combination. Then, on the one hand, in order to analyze the frequency of matching categories, the number of positive interactions of AB category matching can be counted based on all purchase records of all users during the entire statistical time (that is, the number of times the same user bought B category goods within a preset time after purchasing A category goods, and the user did not buy other goods between purchasing A category goods and B category goods); on the other hand, in order to make the obtained category association relationship more accurate, it is necessary to exclude the goods purchased by universal matching, so the reverse interaction ratio of AB category matching can also be counted based on all purchase records of all users during the entire statistical time, that is, the number of times B category goods were purchased is 100 times, and the number of times A category goods were purchased within a preset time before purchasing B category goods and no other goods were purchased between purchasing A category goods and B category goods is 50 times, then the reverse interaction ratio of AB category matching is determined to be 50%. In this way, the product of the number of positive interactions and the reverse interaction ratio can be recorded as the association weight of AB category matching. Based on the above method, the association weights of AB, AC, ..., AZ category matching can be determined. Next, we can first determine whether the reverse interaction ratio of each category combination is greater than a preset threshold (such as 1%). If so, select a preset number (such as 20) of category combinations with the largest association weights from the category combinations with a reverse interaction ratio greater than the preset threshold, and record the selected category combinations as a category association relationship, which are maintained in the category association relationship library; if the reverse interaction ratio of each category combination is not greater than the preset threshold, select a preset number of category combinations with the largest association weights from all category combinations, and record the selected category combinations as a category association relationship, which are maintained in the category association relationship library.

[0082] It should be noted that the category association relationships in the category association relationship library can be updated regularly or irregularly so as to provide accurate data basis for the process of automatically generating object combinations at any time.

[0083] At least one object combination generated based on the category association library can be maintained in a table, which may include at least: the identifier (ID) of category A, the ID of category B and the association weight of "AB category combination". For easy viewing, the table may also include the name of category A and / or the name of category B.

[0084] It is understandable that after generating at least one object combination of the target entity, the at least one object combination of the target entity can be saved in the form of a file for viewing, editing and other operations by the staff of the target entity.

[0085] In some possible implementations, in order to subsequently optimize the process of automatic matching and to provide a better experience for online entities, the method may also include: calculating the association of the object combination based on the page views, sales volume, buyer evaluation, staff evaluation, and sales association of each object in the object combination within the target entity, thereby determining the matching score of the object combination based on the association. Optionally, the matching score can be displayed on the management platform to guide the display and / or release of the object combination. For example, the staff can choose to put the object combination with a higher matching score on the shelf. For another example, the staff can choose to "adjust" the display order of each object combination in the display page of the online entity with one click according to the size of the matching score. The staff can even set the matching score threshold for the display. The object combination corresponding to the matching score below the matching score threshold will not be displayed on the display page. For another example, the staff can also affect the matching score of the object combination by filling in the evaluation.

[0086] It should be noted that, for at least one object combination generated by S102, it can be an object combination that has been deduplicated by the same combination and / or filtered by the same category in the match; or, at least one object combination generated by S102 can be an object combination that has not been deduplicated by the same combination and / or filtered by the same category in the match. Then, after S102, the method can also perform deduplication of the same combination and / or filtering of the same category in the match, so that the object combination finally provided to the staff of the target entity has better quality, so as to improve the user experience of using the automatic matching function.

[0087] It can be seen that in this method, there is no need for staff to manually match objects. Due to the automatic matching function integrated in the background of the management platform, the staff only needs to use the automatic matching function, and the management platform can build and maintain the category association library with the help of the historical interaction results information reflecting the historical interactions between at least two categories, and automatically determine the object combination according to the matching results between the category to which each object belongs and the category association library. On the one hand, the purpose of automatically generating object combinations is achieved. On the other hand, since the category association library is determined by the historical interaction results information, using the category association library as a matching benchmark is a reliable data basis, which makes the quality of the generated object combination better, thereby making it possible to optimize online marketing.

[0088] Accordingly, the embodiment of the present application also provides a device 300 for generating an object combination, see Figure 3 As shown, the device 300 may include:

[0089] A determination unit 301, configured to determine the category to which each object belongs according to the category information of each object;

[0090] A generation unit 302 is used to generate at least one object combination based on a category association relationship library and the categories to which each object belongs, wherein each category association relationship in the category association relationship library includes at least two categories that meet a combination condition determined based on historical interaction result information, and the interaction result information is used to reflect the historical interaction between the at least two categories, and the categories to which the at least two objects included in each object combination in the at least one object combination belong match a category association relationship in the category association relationship library.

[0091] In a possible implementation, the category association relationship library includes a first category association relationship, the first category association relationship includes a first category and a second category, and the generating unit 302 includes:

[0092] A first determining subunit, configured to determine a first object set consisting of objects belonging to the first category among the objects;

[0093] A second determining subunit is used to determine a second object set consisting of objects belonging to the second category among the objects;

[0094] A generating subunit is used to generate the at least one object combination according to the first object set and the second object set, each object combination in the at least one object combination includes any one object in the first object set and any one object in the second object set.

[0095] In a possible implementation, the apparatus 300 further includes: a construction unit;

[0096] The construction unit is used to construct a category association relationship library.

[0097] As an example, the construction unit includes:

[0098] A first obtaining subunit is configured to obtain interaction result information corresponding to the third category according to interaction behaviors between the objects of the third category and categories of other objects, wherein the interaction result information corresponding to the third category includes the number of positive interactions and the reverse interaction ratio between the third category and the other categories, wherein the positive interaction refers to the time at which the same user interacts with the objects belonging to the third category at a preset time before the time at which the user interacts with the objects belonging to the other categories, and the interaction corresponding to the objects belonging to the third category and the interaction corresponding to the objects belonging to the other categories are two adjacent interaction behaviors, and the reverse interaction ratio refers to the number of times that the previous interaction behavior before the interaction corresponding to the objects belonging to the other categories is the interaction behavior corresponding to the objects belonging to the third category, and the ratio of the number of times that the interaction behaviors corresponding to the objects belonging to the third category occur, and the interval between the time at which the interaction occurs with the objects belonging to the other categories and the time at which the interaction occurs with the objects belonging to the third category is less than or equal to the preset time;

[0099] a third determining subunit, configured to determine, according to the number of positive interactions and the reverse interaction ratio, a fourth category that meets the combination condition with the third category, wherein the fourth category belongs to at least one of the other categories;

[0100] The saving subunit is used to record the third category and each of the fourth categories as a category association relationship in the category association relationship library.

[0101] As an example, the third determining subunit includes:

[0102] A first determination module, configured to determine an association weight between the third category and each of the other categories according to the number of positive interactions and the reverse interaction ratio;

[0103] The second determination module is used to determine the fourth category that meets the combination condition according to the association weights of the other categories, and the combination condition includes: a preset number of the other categories with the largest association weights, or determining the other categories whose association weights are greater than a preset weight threshold as the fourth category.

[0104] As another example, the second determining module is specifically configured to:

[0105] If there is a fifth category in the other categories whose proportion is greater than or equal to the preset proportion threshold, the fourth category satisfying the combination condition is determined from the fifth category.

[0106] In a possible implementation manner, objects in the at least one object combination all belong to the same entity.

[0107] In a possible implementation manner, the apparatus 300 further includes:

[0108] A scoring unit is used to determine a collocation score for each object combination in the at least one object according to the correlation degree of each object combination in the at least one object combination, wherein the correlation degree of the object combination represents the proportion or number of times that the objects belonging to the object combination in the target entity are marketed in combination, and the collocation score is used to guide the display and / or publication of the corresponding object combination.

[0109] It should be noted that the specific implementation method of the device 300 and the technical effects achieved can be found in Figure 1 Description of the method shown.

[0110] In addition, an embodiment of the present application also provides an electronic device, which includes a processor and a memory: the memory is used to store instructions or computer programs; the processor is used to execute the instructions or computer programs in the memory, so that the electronic device executes any implementation of the method provided in the embodiment of the present application.

[0111] See also Figure 4 , which shows a schematic diagram of the structure of an electronic device 400 suitable for implementing the embodiment of the present disclosure. The terminal device in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0112] like Figure 4 As shown, the electronic device 400 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 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 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0113] Typically, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 400 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The electronic device 400 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0114] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0115] The electronic device provided by the embodiment of the present disclosure and the method provided by the above embodiment belong to the same inventive concept, and the technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0116] The embodiment of the present application also provides a computer-readable medium, in which instructions or computer programs are stored. When the instructions or computer programs are executed on a device, the device executes any implementation of the method provided in the embodiment of the present application.

[0117] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0118] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0119] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0120] The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device can execute the method.

[0121] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including, but not limited to, object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0122] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0123] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit / module does not, in some cases, constitute a limitation on the unit itself.

[0124] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0125] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A 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, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0126] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the system or device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0127] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0128] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0129] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0130] It should be noted that in the embodiments of the present application, user sensitive information is not involved, and user-related information is obtained, used and determined after user authorization. In one example, before obtaining user-related information, the corresponding interface displays prompt information related to obtaining data use authorization. The prompt information is based on relevant laws and regulations in an appropriate manner to inform the user of the type, scope of use, usage scenarios, etc. of the personal information involved in this disclosure, so that the user can determine whether to agree to the authorization based on the prompt information. It can be understood that the above notification and the process of obtaining user authorization are only illustrative and do not constitute a limitation on the implementation method of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation method of the present disclosure.

[0131] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for generating an object combination, characterized in that: include: According to the category information of each object, determine the category to which each object belongs; At least one object combination is generated based on a category association relationship library and the categories to which each object belongs, wherein each category association relationship in the category association relationship library includes at least two categories that meet a combination condition determined based on historical interaction result information, and the interaction result information is used to reflect the historical interaction between the at least two categories, and the categories to which the at least two objects included in each object combination in the at least one object combination belong match a category association relationship in the category association relationship library.

2. The method according to claim 1, characterized in that The category association relationship library includes a first category association relationship, the first category association relationship includes a first category and a second category, and generating at least one object combination according to the category association relationship library and the category to which each object belongs includes: Determine a first object set consisting of objects belonging to the first category among the objects; Determine a second object set consisting of objects belonging to the second category among the objects; The at least one object combination is generated according to the first object set and the second object set, and each object combination in the at least one object combination includes any one object in the first object set and any one object in the second object set.

3. The method according to claim 1 or 2, characterized in that: The process of constructing the category association relationship library includes: According to the interaction behavior between the object of the third category and the category of other objects, the interaction result information corresponding to the third category is obtained, and the interaction result information corresponding to the third category includes the number of positive interactions and the reverse interaction ratio between the third category and the other categories, the positive interaction refers to the time when the same user interacts with the object belonging to the third category at a preset time before the time when the user interacts with the object belonging to the other category, and the interaction corresponding to the object belonging to the third category and the interaction corresponding to the object belonging to the other category are two adjacent interaction behaviors, the reverse interaction ratio refers to the number of times that the previous interaction behavior before the interaction corresponding to the object belonging to the other category is the interaction behavior corresponding to the object belonging to the third category, and the ratio of the number of times that the interaction behavior corresponding to the object belonging to the third category occurs, and the interval time between the time when the interaction corresponding to the object belonging to the other category occurs and the time when the interaction corresponding to the object belonging to the third category occurs is less than or equal to the preset time; determining, according to the number of positive interactions and the reverse interaction ratio, a fourth category that meets the combination condition with the third category, wherein the fourth category belongs to at least one of the other categories; The third category and each of the fourth categories are recorded as a category association relationship in the category association relationship library.

4. The method according to claim 3, characterized in that The determining, according to the number of positive interactions and the reverse interaction ratio, a fourth category that meets the combination condition with the third category includes: Determining, according to the number of positive interactions and the reverse interaction ratio, an association weight between the third category and each of the other categories; According to the association weights of the other categories, the fourth category that meets the combination condition is determined, and the combination condition includes: a preset number of the other categories with the largest association weights, or, the other categories with association weights greater than a preset weight threshold are determined as the fourth category.

5. The method according to claim 4, characterized in that The determining, according to the association weights of the other categories, the fourth category that satisfies the combination condition includes: If there is a fifth category in the other categories whose proportion is greater than or equal to the preset proportion threshold, the fourth category satisfying the combination condition is determined from the fifth category.

6. The method according to any one of claims 1 to 5, characterized in that: The objects in the at least one object group all belong to the same entity.

7. The method according to claim 6, characterized in that The method further comprises: According to the association degree of each object combination in the at least one object combination, a collocation score of each object combination in the at least one object is determined, the association degree of the object combination represents the proportion or number of times that the objects belonging to the object combination in the target entity are marketed in combination, and the collocation score is used to guide the display and / or publication of the corresponding object combination.

8. A device for generating a combination of objects, characterized in that: include: A determination unit, used to determine the category to which each object belongs according to the category information of each object; A generating unit is used to generate at least one object combination according to a category association relationship library and the categories to which each object belongs, wherein each category association relationship in the category association relationship library includes at least two categories that meet a combination condition determined based on historical interaction result information, and the interaction result information is used to reflect the historical interaction between the at least two categories, and the categories to which the at least two objects included in each object combination in the at least one object combination belong match a category association relationship in the category association relationship library.

9. An electronic device, characterized in that: The electronic device comprises: a processor and a memory; The memory is used to store instructions or programs; The processor is used to execute the instructions or programs in the memory so that the electronic device executes the method according to any one of claims 1 to 7.

10. A readable medium, characterized in that: The readable medium stores instructions or programs, and when the instructions or programs are executed on a processor, the processor is enabled to execute the method according to any one of claims 1 to 7.

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