CN111221784B - Method and device for adjusting collection object, terminal equipment and computer storage medium - Google Patents
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Abstract
The embodiment of the invention provides a method and a device for adjusting a collection object, terminal equipment and a computer storage medium, wherein the method for adjusting the collection object comprises the following steps: acquiring collection data of a target object, wherein the collection data comprises behavior data of a user aiming at the target object; determining the recording parameter data of the target object according to the collection data; and calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface. According to the adjustment scheme of the collection object, the identification of the target object can be automatically moved into the collection or the identification of the target object in the collection can be moved out according to the collection data of the target object, so that the operation of moving in or moving out the identification of the target object in the collection is more convenient, efficient and intelligent.
Description
Technical Field
The embodiment of the invention relates to the technical field of data processing, in particular to a method and a device for adjusting collection objects, terminal equipment and a computer storage medium.
Background
Favorites are folders for recording target objects that are liked or commonly used by a user, such as a browser for recording websites, etc. that are liked or commonly used by a user.
Currently, the use of favorites remains in the stage of manually adding or deleting favorites by a user. For example, when a user manually deletes a favorite object, the user needs to open the favorite, determine a target object to be deleted from a plurality of target objects collected, and then click a delete button to delete the target object; alternatively, if the user needs to add a certain web page to the favorites while browsing, the user needs to manually find and open the web page again and then click on the favorites to add it to the favorites.
Therefore, the operation of the using mode of the favorites is complex, and the using experience of users is further poor.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a method, an apparatus, a terminal device, and a computer storage medium for adjusting a collection object, so as to solve the above problems.
According to a first aspect of an embodiment of the present invention, there is provided a method for adjusting a collection object, including: acquiring collection data of a target object, wherein the collection data comprises behavior data of a user aiming at the target object; determining the recording parameter data of the target object according to the collection data; and calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface.
According to a second aspect of an embodiment of the present invention, there is provided an adjustment device for a collection object, including: the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring collection data of a target object, and the collection data comprises behavior data of a user aiming at the target object; the recording parameter data determining module is used for determining recording parameter data of the target object according to the collection data; and the adjustment module is used for calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface.
According to a third aspect of an embodiment of the present invention, there is provided a terminal device including: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus; the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the adjustment method of the collection object.
According to a fourth aspect of embodiments of the present invention, there is provided a computer storage medium having stored thereon a computer program which, when executed by a processor, implements the method of adjusting a collection object as described above.
According to the adjustment scheme of the collection object provided by the embodiment of the invention, the collection data of the target object are obtained, wherein the collection data comprise behavior data of a user aiming at the target object; determining the recording parameter data of the target object according to the collection data; and calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface. According to the adjustment scheme of the collection object provided by the embodiment of the invention, the identification of the target object can be automatically moved into the collection or the identification of the target object in the collection can be moved out according to the collection data of the target object, so that the operation of moving in or moving out the identification of the target object in the collection is more convenient, efficient and intelligent.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the embodiments of the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a flowchart illustrating a method for adjusting a collection object according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for adjusting collection objects according to a second embodiment of the present invention;
FIG. 3 is a block diagram illustrating a device for adjusting a collection object according to a third embodiment of the present invention;
FIG. 4 is a block diagram illustrating a device for adjusting a collection object according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of a terminal device according to a fifth embodiment of the present invention.
Detailed Description
In order to better understand the technical solutions in the embodiments of the present invention, the following description will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which are derived by a person skilled in the art based on the embodiments of the present invention, shall fall within the scope of protection of the embodiments of the present invention.
The implementation of the embodiments of the present invention will be further described below with reference to the accompanying drawings.
Example 1
Referring to fig. 1, a flowchart illustrating steps of a method for adjusting a collection object according to a first embodiment of the present invention is shown.
The method for adjusting the collection object of the embodiment comprises the following steps:
s102, collecting data of the target object is obtained.
Wherein the collection data includes behavior data of a user for the target object.
In this embodiment, the target object may be any suitable object capable of moving into or out of the favorites, for example, if the favorites are the favorites of the browser, the target object may be a web page; if the favorites are the favorites of the reading software, the target object can be a book; if the favorites are favorites of shopping software, the target object may be an online store or a sales product, which is not limited in this embodiment.
The collection data of the target object is basic data for determining whether to move the identification of the target object into or out of the favorites. In this embodiment, the favorites data includes behavior data of the user for the target object, so that it can be determined whether to move the identifier of the target object into or out of the favorites according to the behavior of the user, so that the target object in the favorites better conforms to the behavior habit of the user, for example, the web sites of the web pages frequently visited by the user (i.e., the identifier of the target web page) can be automatically moved into the favorites, and the web sites of the web pages not visited by the user for a long time are moved out of the favorites. The identification of the target object may be any suitable data that may identify the target object, for example, a link or title of a web page, an identification of a book, a link address of an online store, or a link address of a sales product, which is not limited in this embodiment.
S104, determining the recording parameter data of the target object according to the collection data.
In this embodiment, the recording parameter data is data that is determined according to the collection data and is used to measure whether the identification of the target object is to be moved into or out of the collection. For example, the listing parameter data may be 0 or 1, where 0 may represent moving the identity of the target object out of the favorites and 1 may represent moving the identity of the target object into the favorites; or the recording parameter data can be a numerical value, if the numerical value of the recording parameter data is smaller than a preset threshold value, the identification of the target object can be determined to be moved out of the favorites, and if the numerical value of the recording parameter data is larger than the preset threshold value, the identification of the target object can be determined to be moved into the favorites; alternatively, the "TRUE" indicates that the identity of the target object is moved into the favorites, and the "FALSE" indicates that the identity of the target object is moved out of the favorites. However, in practical applications, those skilled in the art may characterize the recording parameter data in any suitable form according to actual needs, which is not limited in this embodiment.
In the above step, the collection data may include behavior data of the user with respect to the target object, and in this step, when determining the recording parameter data, the behavior data may be analyzed, and according to the analysis result, the behavior feature of the user with respect to the target object may be determined, and then the recording parameter data may be determined according to the analysis result. For example, according to the browsing record in the set period of the browser, the behavior data of the user for the target webpage can be determined, the analysis result obtained after analyzing the behavior data is that the total duration of the user browsing the target webpage in the set period is 30 minutes, and then the recording parameter data can be determined according to the analysis result.
S106, calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface.
In this embodiment, the favorites interface may include multiple interfaces, and different interfaces may be used to implement different functions, e.g., the favorites interface may include, but is not limited to, a move-in interface, a move-out interface, a export favorites interface, and so forth. The functions corresponding to the called interfaces can be realized by calling the corresponding favorites interfaces and providing the required parameters. For example, calling the move-in interface and providing the identification corresponding to the target object, the identification of the target object can be moved into the favorites; and calling the removal interface and providing the identification corresponding to the target object, and removing the identification of the target object from the favorites.
In this embodiment, if the identifier of the target object is not in the favorites, it may be determined whether the recording parameter data of the target object meets the preset collection conditions, if so, the identifier of the target object is moved into the user's favorites through the invoked favorites interface, and if not, the target object is not moved in; if the identification of the target object is in the favorites, whether the recording parameter data of the target object accords with the preset removal condition can be determined, if so, the identification of the target object existing in the favorites of the user is removed from the favorites of the user through the called favorites interface, and if not, the identification of the target object is still reserved in the favorites. The favorites included in the favorites of the user may be predetermined, or may be determined while performing the above-described step S102 or S104, which is not limited in this embodiment. Based on the favorites included in the favorites, a determination can be made as to whether the identification of the target object is in the favorites. Specifically, when the collection objects included in the favorites are determined, the export collection content interface in the favorites interface can be called to export the collection content in the favorites.
Or in this embodiment, if it is determined that the recording parameter data of the target object meets the preset collection condition, the favorites interface may be directly called to move the identifier of the target object into the user's favorites, and if the identifier of the target object already exists in the favorites, the identifier of the target object already existing in the favorites may be covered; if the identification of the target object does not exist in the favorites, the target object can be directly moved into the favorites.
The preset storage conditions and removal conditions can be set appropriately by those skilled in the art according to actual requirements, and the embodiment is not limited thereto.
According to the adjustment scheme of the collection object, through acquiring the collection data of the target object and determining the recording parameter data of the target object according to the collection data, a collection interface can be called according to the recording parameter data, the identification of the target object is moved into the user's collection or the identification of the target object existing in the user's collection is moved out of the user's collection through the called collection interface, and the identification of the target object can be automatically moved into the collection or the identification of the target object in the collection is moved out of the user's collection according to the collection data of the target object. Compared with the existing favorites adjustment method, the existing favorites adjustment method monitors the moving-in or moving-out operation of the user, invokes the favorites interface according to the moving-in or moving-out operation of the user, moves the object identification corresponding to the operation into or out of the favorites, and the favorites adjustment scheme provided by the embodiment can automatically move the identification of the target object into the favorites or move the identification of the target object in the favorites directly according to the favorites data, so that the moving-in or moving-out operation of the target object identification in the favorites is more convenient, efficient and intelligent. Of course, the favorites adjustment scheme provided in the present embodiment may also be used simultaneously with the existing favorites adjustment scheme, which is not limited in this embodiment.
The method for adjusting the collection object of the present embodiment may be performed by any suitable terminal device having data processing capability, including but not limited to: mobile terminals (e.g., tablet computers, cell phones, etc.) and PCs.
Example two
Referring to fig. 2, a flowchart illustrating steps of a method for adjusting a collection object according to a second embodiment of the present invention is shown.
The method for adjusting the collection object of the embodiment comprises the following steps:
s202, collecting data of the target object is obtained.
Wherein the collection data includes behavior data of a user for the target object.
Optionally, in this embodiment, if the target object is a target web page, the behavior data includes at least one of the following: the method comprises the steps of browsing frequency data of a target webpage by a user, browsing duration data of the target webpage by the user and interaction data of interaction between the user and the target webpage.
The behavior data of the user for the target web page may be determined by historical usage data of the browser used by the user. Specifically, when the user browses the web pages using the browser, the number of target web pages may be one or more of the browsed web pages in this embodiment. If the number of the target webpages is one, directly extracting behavior data corresponding to the target webpages from the historical use data; if the number of the target web pages is multiple, the behavior data corresponding to the multiple target web pages is determined from the historical usage data for the multiple target web pages.
The browsing frequency data of the target web page, that is, the number of times the user browses the target web page within a preset time period, where the preset time period can be adjusted by a person skilled in the art according to the need, or can be dynamically adjusted according to the number of times, time period, etc. of the user using the browser, etc., and this embodiment is not limited.
The browsing duration data of the target webpage, that is, the total duration of the target webpage browsed by the user within the preset duration, where the preset duration of the browsing duration data is determined in the same manner as the preset duration of the browsing frequency data, which is not described herein in detail.
The interaction data of the user interacting with the target webpage may include: the data generated by interaction of the interactive buttons such as clicking, sharing and submitting performed by the user when browsing the target webpage can also be the interactive data in the preset duration.
In this embodiment, through any one of the above three behavior data, it may be determined whether the user is interested in the target web page or whether the user opens the target web page again according to the user behavior. For example, whether the target webpage is a webpage frequently browsed by the user can be determined through the browsing frequency data, if so, the probability that the user opens the target webpage again is high; whether the target webpage is the webpage with more browsing time of the user can be determined through the browsing time length data, if so, the probability that the user opens the target webpage again is larger; through the interactive data, it can be determined whether the user performs interactive operation on the target webpage, for example, whether registration information is submitted, etc., and then the probability that the user opens the target webpage again can be determined according to the interactive operation of the user.
In this embodiment, the three behavior data may be considered simultaneously when the recording parameter data is determined, so that the operation of moving the identifier of the target object into or out of the user's favorites may be more consistent with the behavior habits of the user.
Optionally, in this embodiment, the collection data further includes at least one of: and the user actively triggers operation data corresponding to the operation of moving the identification of the target object into or out of the favorites, user portrait data of the user and evaluation data of the target object.
In this embodiment, when the favorites are used, the method provided in the first embodiment may not only automatically move the identifier of the target object into or out of the favorites, but also actively operate the favorites by the user, so that the favorites data of the target object include operation data corresponding to the operation of moving the identifier of the target object into or out of the favorites, which is actively triggered by the user. The user actively moves the identification of the target object into or out of the favorites, and the operation data corresponding to the move-in or move-out favorites is used as one of the favorites, so that the target object identification manually added into the favorites by the user can be prevented from being moved out, or the target object identification manually moved out of the favorites by the user can be prevented from being moved into the favorites again, and the user experience is improved.
In this embodiment, the user portrait data of the user is used to characterize the personalized features of the user, and the user portrait data may be determined according to the attribute of the user, the historical usage data of the user, the design label of the user, and the like, which is not described herein. By using the user representation as one of the favorites, certain operations of moving the identification of the target object into or out of the favorites can be made to better conform to the user's preference.
In this embodiment, the evaluation data of the target object is determined according to the related data of the target object, and is used for evaluating the collected value of the target object, where the evaluation data of the target object may be determined according to the content of the target object, the click heat of the target object, the collection operation of other users on the target object, and so on; alternatively, the evaluation data of the target object may directly include quality data, click heat data, and the like of the target object, which is not limited in this embodiment. By taking the evaluation data of the target object as one of the collection data, the identification of the target object with higher collection value can be moved into the user's collection, or the identification of the target object with lower collection value can be moved out of the user's collection, so that the overall collection value of the target object in the collection is improved, and better experience is provided for the user.
S204, determining the weight and score value corresponding to each collection data, and determining the recording parameter data according to the weight and score value corresponding to each collection data.
In this embodiment, different collection data may have different weights and different score value determination criteria. The weight of each collection data may be fixed or may be dynamically changed, which is not limited in this embodiment.
For example, according to the above steps, the collection data may include: the method comprises the steps of browsing frequency data of a target webpage browsed by a user, browsing duration data of the target webpage browsed by the user, interaction data of interaction between the user and the target webpage, operation data which are actively triggered by the user and correspond to operation of moving an identification of a target object into or out of a favorites, user portrait data of the user, quality data of the target object and heat data of the target object. The seven weight and score values are determined as follows:
a. the weight A of the user portrait data of the user can be predefined or can be used for determining the matching degree of the user portrait data and the target object; and then determining the weight of the user image data according to the matching degree, wherein the higher the matching degree is, the higher the weight is. The score value a of the user portrait data can be 0-100, and then the score value corresponding to the user portrait data can be determined according to the time length of a target object matched with the user portrait browsed by the user within a preset period, and the longer the time length is, the higher the score value is. For example, if the user portrait of the current user is "cartoon control", the average time period for the current user to browse the cartoon-like web page every day is 10 minutes, the score value a of the user portrait data is 60 minutes, and if the average time period for the current user to browse the cartoon-like web page every day is 30 minutes, the score value a of the user portrait data is 80 minutes.
b. For the browsing frequency data of the target web page browsed by the user, the weight is defined as a coefficient B, the value of B can be fixed, the score value is defined as B, the value of B is 0-100, the determining logic of B is similar to that of a, namely, the higher the frequency is, the higher the score value is, and the embodiment is not repeated here.
c. For the browsing duration data of the target web page browsed by the user, the weight is defined as a coefficient C, the value of C can be fixed, the score value is defined as C, the value of C is 0-100, the determining logic of C is similar to a, namely the higher the browsing duration, the higher the score value, and the embodiment is not described in detail herein.
d. For the interaction data of the user interacting with the target webpage, the weight is defined as a coefficient D, the score value is defined as D, the D value is 0-100, the D value can be determined according to different interactions performed by the user, for example, the common button is triggered to interact (for example, the link of the webpage and the like) for 60 minutes, the sharing button is clicked for 80 minutes, the submitting button (for example, the button for submitting registration information) is clicked for 100 minutes and the like.
e. For the operation data corresponding to the operation of moving the identifier of the target object into or out of the favorites, which is actively triggered by the user, the weight value of the operation data may be set to be a coefficient E, E may be fixed, and the score value of the operation data may be set to be E.
f. For the quality data of the target object, the weight of the quality data can be directly set to be 1, the score value of the quality data is f, and in particular, if the target object is a webpage, f can be directly determined and returned by a browser for the target webpage and used for representing the webpage quality of the target webpage.
g. The weight of the heat data of the target object can be directly set to 1, and the score value of the heat data is g, specifically, if the target object is a webpage, the g can be directly determined and returned by a browser for the target webpage, and the browser is used for representing the page heat of the target webpage.
In addition, it should be noted that, if the favorites data includes the operation data corresponding to the move-in favorites operation, the weight of the operation data corresponding to the move-in favorites operation is set to be higher than the weight corresponding to other favorites data, and/or the score value of the operation data corresponding to the move-in favorites operation is set to be higher than the score value corresponding to other favorites data, so as to ensure that the identification of the target object manually moved into the favorites by the user is not moved out, i.e., the coefficient E is set to be a higher value, or the score value of the operation data corresponding to the move-in favorites operation is set to be 100.
In addition, if the favorites data includes the operation data corresponding to the operation of moving out the favorites, the score value corresponding to the operation of moving out the favorites is set to be negative, namely the score value e is set to be-100, so that the identification of the target object of the user manually moving out the favorites is ensured not to be moved in.
The ordering of the plurality of weights by size may be as follows: e > (B|C|D) > A >1, wherein E is the weight of operation data corresponding to the operation of moving in or out the favorites, B is the weight of browsing frequency data, C is the weight of browsing duration data, D is the weight of interaction data, and A is the weight of user portrait data, and (B|C|D) represents that the content in brackets is B or C or D.
The magnitude of the weight corresponds to the importance of the corresponding collection data, and the larger the weight is, the higher the importance of the collection data is when the recording parameter data is determined.
In this embodiment, after determining the weight and score value of each collection data, the recording parameter data may be determined according to the weight and score value corresponding to each collection data.
For example, the value h of the recording parameter data may be specifically determined by the following formula:
h＝A*a+B*b+C*c+D*d+E*e+f+g
note that, if some of the collection data is not considered, it may be directly calculated without taking into consideration a formula for calculating the value h of the recording parameter data, which is not limited in this embodiment.
In the present embodiment, the manner of determining the recording parameter data is described by taking step S204 as an example, but in other implementations of the present embodiment, the recording parameter data may be determined by other manners, and the present embodiment is not limited thereto.
S206, calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface.
In this embodiment, a collection threshold z may be predefined, and the value of the collection threshold z may be set by those skilled in the art according to experience, or may be determined according to historical usage data of the user, attributes of the user, and the like; the value of the collection threshold z may also be dynamically adjusted as needed, which is not limited in this embodiment.
When the identification of the target object is determined to be moved into or out of the user's favorites according to the recording parameter data, if the value h > z of the recording parameter data, the target object is determined to be recorded into the user's favorites, specifically, if the target object is not in the favorites, the identification thereof is moved into the user's favorites, and if the target object already exists in the user's favorites, no operation is performed; or if the value h < z of the recording parameter data, determining that the target object can not be recorded in the user's favorite, specifically, if the target object is not in the user's favorite, not performing any operation, and if the target object is already in the user's favorite, moving the identification of the target object out of the user's favorite.
In this embodiment, the invoked favorites interface may specifically be an AP I interface corresponding to a favorites.
By the method, the identification of the target object can be intelligently moved into or out of the favorites of the user.
Optionally, in this embodiment, step S206 may further include an optional step S208, that is:
s208, classifying the plurality of target objects in the favorites.
In one implementation, tag data for a plurality of target objects within the favorites may be determined first, and then the plurality of target objects may be categorized according to the tag data. For example, tag data corresponding to a plurality of target objects in a favorites can be determined, and then the target objects with the same tag data are classified, wherein the tag data can be determined by analyzing the content of the target object or the like, and can also be determined by other tags set by other users, and the embodiment is not limited to the determination; alternatively, the similarity between the tag data of the plurality of target objects and the existing classification data may be determined, and then the target objects may be classified into the existing classification according to the result of the determination of the similarity, where, when the similarity is determined by the tag data and the classification data through text identification, any suitable manner, such as a determination manner of calculating semantic similarity, may be adopted to determine the similarity between the tag data and the classification data through text identification.
Alternatively, in another implementation manner of this embodiment, the plurality of target objects in the favorites may be classified according to user portrait data of the user. For example, the matching degree of a plurality of target objects with the user portrait data may be determined separately, and then the plurality of target objects may be classified according to the value of the matching degree. For example, when determining the matching degree, the tag data of the target object and the tag data corresponding to the user image may be determined first, and then the matching degree between the two may be determined by determining the similarity of the tag data of the target object and the tag data.
Through the above step S208, automatic classification of the target objects in the favorites can be achieved.
In this embodiment, only the step S208 is executed after the step S206, for example, but steps S202-S206 are used to modify the target objects included in the favorites, and step S208 is used to classify the plurality of target objects in the favorites, and the two parts have no clear timing relationship in actual use.
According to the scheme provided by the embodiment, the identification of the target object can be automatically moved into the favorites or moved out of the favorites according to the collection data of the target object, and meanwhile, the automatic classification of a plurality of target objects in the favorites can be realized, so that the operation of the favorites is simplified, and the favorites are more convenient, efficient and intelligent to use.
The method for adjusting the collection object of the present embodiment may be performed by any suitable terminal device having data processing capability, including but not limited to: mobile terminals (e.g., tablet computers, cell phones, etc.) and PCs.
Example III
Referring to fig. 3, a block diagram of a device for adjusting a collection object according to a third embodiment of the present invention is shown.
The device for adjusting the collection object provided in this embodiment includes: an acquisition module 302, a recording parameter data determination module 304, and an adjustment module 306.
The obtaining module 302 is configured to obtain collection data of a target object, where the collection data includes behavior data of a user for the target object.
The recording parameter data determining module 304 is configured to determine recording parameter data of the target object according to the collection data.
The adjustment module 306 is configured to call a favorites interface according to the recording parameter data, and move the identifier of the target object into the favorites of the user or move the identifier of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface.
According to the adjustment scheme of the collection object provided by the embodiment of the invention, the identification of the target object can be automatically moved into the collection or the identification of the target object in the collection can be moved out according to the collection data of the target object, so that the operation of moving in or moving out the identification of the target object in the collection is more convenient, efficient and intelligent.
Example IV
Referring to fig. 4, a block diagram of a device for adjusting a collection object according to a fourth embodiment of the present application is shown.
As shown in fig. 4, the adjustment device for the collection object includes an acquisition module 402, a recording parameter data determination module 404, and an adjustment module 406. The adjusting device for collecting the objects on the basis of the above further comprises: a classification module 408, configured to determine tag data of a plurality of target objects in the favorites, and classify the plurality of target objects according to the tag data; alternatively, the classification module 408 is configured to classify the plurality of target objects in the favorites according to user portrait data of the user.
Optionally, in any embodiment of the present application, if the target object is a target web page, the behavior data includes at least one of the following: the method comprises the steps of browsing frequency data of a target webpage by a user, browsing duration data of the target webpage by the user and interaction data of interaction between the user and the target webpage.
Optionally, in any embodiment of the present application, the collection data further includes at least one of: and the user actively triggers operation data corresponding to the operation of moving the identification of the target object into or out of the favorites, user portrait data of the user and evaluation data of the target object.
Optionally, in any embodiment of the present application, the recording parameter data determining module 404 is specifically configured to: and determining the weight and the score value corresponding to each collection data, and determining the recording parameter data according to the weight and the score value corresponding to each collection data.
Optionally, in any embodiment of the present application, if the collection data includes operation data corresponding to the move-in favorites operation, the weight of the operation data corresponding to the move-in favorites operation is set to be higher than the weight corresponding to other collection data, and/or the score value of the operation data corresponding to the move-in favorites operation is set to be higher than the score value corresponding to other collection data; or if the collection data comprises the operation data corresponding to the operation of moving out the favorites, setting the score value corresponding to the operation of moving out the favorites to be a negative value.
Optionally, in any embodiment of the present application, if the collection data includes user portrait data of the user, determining the weight corresponding to each collection data includes: determining the matching degree of the user portrait data and the target object; and determining the weight of the user portrait data according to the matching degree.
According to the adjustment scheme of the collection objects, the identification of the target objects can be automatically moved into the favorites or the identification of the target objects in the favorites according to the collection data of the target objects, meanwhile, the automatic classification of a plurality of target objects in the favorites can be realized, the operation of the favorites is simplified, and the favorites are more convenient, efficient and intelligent to use.
Example five
A terminal device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus; the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the adjustment method of the collection object.
Specifically, referring to fig. 5, a schematic structural diagram of a terminal device according to a fifth embodiment of the present invention is shown, and the specific embodiment of the present invention does not limit the specific implementation of the terminal device.
As shown in fig. 5, the terminal device may include: a processor 502, a communication interface (Communications Interface) 504, a memory 506, and a communication bus 508.
Wherein:
processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508.
A communication interface 504 for communicating with other terminal devices or servers.
The processor 502 is configured to execute the program 510, and may specifically perform relevant steps in the above-described embodiment of the method for adjusting a collection object.
In particular, program 510 may include program code including computer-operating instructions.
The processor 502 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors comprised by the terminal device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
A memory 506 for storing a program 510. Memory 506 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 510 may be specifically operable to cause the processor 502 to: acquiring collection data of a target object, wherein the collection data comprises behavior data of a user aiming at the target object;
Determining the recording parameter data of the target object according to the collection data; and calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface.
In an alternative embodiment, if the target object is a target web page, the behavior data includes at least one of: the method comprises the steps of browsing frequency data of a target webpage by a user, browsing duration data of the target webpage by the user and interaction data of interaction between the user and the target webpage.
In an alternative embodiment, the collection data further includes at least one of: and the user actively triggers operation data corresponding to the operation of moving the identification of the target object into or out of the favorites, user portrait data of the user and evaluation data of the target object.
In an alternative embodiment, the determining the recording parameter data of the target object according to the collection data includes: and determining the weight and the score value corresponding to each collection data, and determining the recording parameter data according to the weight and the score value corresponding to each collection data.
In an optional implementation manner, if the collection data includes the operation data corresponding to the move-in favorites operation, the weight of the operation data corresponding to the move-in favorites operation is set to be higher than the weight corresponding to other collection data, and/or the score value of the operation data corresponding to the move-in favorites operation is set to be higher than the score value corresponding to other collection data; or if the collection data comprises the operation data corresponding to the operation of moving out the favorites, setting the score value corresponding to the operation of moving out the favorites to be a negative value.
In an alternative embodiment, if the collection data includes user portrait data of the user, determining the weight corresponding to each collection data includes: determining the matching degree of the user portrait data and the target object; and determining the weight of the user portrait data according to the matching degree.
In an alternative embodiment, the program 510 may be further operable to cause the processor 502 to: determining tag data of a plurality of target objects in the favorites, and classifying the plurality of target objects according to the tag data; or classifying the target objects in the favorites according to the user portrait data of the user.
The specific implementation of each step in the program 510 may refer to corresponding steps and corresponding descriptions in the units in the embodiment of the method for adjusting a collection object, which are not described herein. It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and modules described above may refer to corresponding procedure descriptions in the foregoing method embodiments, which are not repeated herein.
According to the terminal equipment, the collection data of the target object are obtained, the recording parameter data of the target object is determined according to the collection data, so that the collection interface can be called according to the recording parameter data, the identification of the target object is moved into the user's collection or the identification of the target object existing in the user's collection is moved out of the user's collection through the called collection interface, the identification of the target object can be automatically moved into the collection or the identification of the target object in the collection according to the collection data of the target object, and the moving-in or moving-out operation of the identification of the target object in the collection is more convenient, efficient and intelligent.
Example six
An embodiment of the present application provides a computer storage medium having stored thereon a computer program which, when executed by a processor, implements the method for adjusting a collection object as described above.
According to the computer storage medium, the collection data of the target object are obtained, the recording parameter data of the target object is determined according to the collection data, so that the collection interface can be called according to the recording parameter data, the identification of the target object is moved into the user's collection or the identification of the target object existing in the user's collection is moved out of the user's collection through the called collection interface, the identification of the target object can be automatically moved into the collection or the identification of the target object in the collection according to the collection data of the target object, and the moving-in or moving-out operation of the identification of the target object in the collection is more convenient, efficient and intelligent.
It should be noted that, according to implementation requirements, each component/step described in the embodiments of the present application may be split into more components/steps, or two or more components/steps or part of operations of the components/steps may be combined into new components/steps, so as to achieve the objects of the embodiments of the present application.
The above-described methods according to embodiments of the present invention may be implemented in hardware, firmware, or as software or computer code storable in a recording medium such as a CD ROM, RAM, floppy disk, hard disk, or magneto-optical disk, or as computer code originally stored in a remote recording medium or a non-transitory machine-readable medium and to be stored in a local recording medium downloaded through a network, so that the methods described herein may be stored on such software processes on a recording medium using a general purpose computer, special purpose processor, or programmable or special purpose hardware such as an ASIC or FPGA. It is understood that a computer, processor, microprocessor controller, or programmable hardware includes a memory component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code that, when accessed and executed by the computer, processor, or hardware, implements the methods of adjusting the collection object described herein. Further, when the general-purpose computer accesses code for implementing the adjustment method of the collection object shown herein, execution of the code converts the general-purpose computer into a special-purpose computer for executing the adjustment method of the collection object shown herein.
Those of ordinary skill in the art will appreciate that the elements and method steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the embodiments of the present invention.
The above embodiments are only for illustrating the embodiments of the present invention, but not for limiting the embodiments of the present invention, and various changes and modifications may be made by one skilled in the relevant art without departing from the spirit and scope of the embodiments of the present invention, so that all equivalent technical solutions also fall within the scope of the embodiments of the present invention, and the scope of the embodiments of the present invention should be defined by the claims.
Claims (12)
1. A method of adjusting a collection object, comprising:
acquiring collection data of a target object, wherein the collection data comprises behavior data of a user aiming at the target object;
Determining the recording parameter data of the target object according to the collection data;
calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface;
wherein the determining the recording parameter data of the target object according to the collection data comprises:
determining the weight and score value corresponding to each collection data, and determining the recording parameter data according to the weight and score value corresponding to each collection data;
and if the collection data includes user portrait data of the user, the determining weights corresponding to the collection data includes:
determining the matching degree of the user portrait data and the target object;
determining the weight of the user portrait data according to the matching degree;
and determining a score value corresponding to the user portrait data according to the duration of the target object matched with the user portrait browsed by the user in a preset period.
2. The method of claim 1, wherein if the target object is a target web page, the behavior data comprises at least one of: the method comprises the steps of browsing frequency data of a target webpage by a user, browsing duration data of the target webpage by the user and interaction data of interaction between the user and the target webpage.
3. The method of claim 1, wherein the collection data further comprises at least one of: and the user actively triggers operation data corresponding to the operation of moving the identification of the target object into or out of the favorites, user portrait data of the user and evaluation data of the target object.
4. The method of claim 3, wherein the step of,
if the collection data comprises the operation data corresponding to the moving-in collection operation, setting the weight of the operation data corresponding to the moving-in collection operation to be higher than the weight corresponding to other collection data, and/or setting the score value of the operation data corresponding to the moving-in collection operation to be higher than the score value corresponding to other collection data;
or alternatively, the process may be performed,
and if the collection data comprises operation data corresponding to the operation of moving out the favorites, setting the score value corresponding to the operation of moving out the favorites as a negative value.
5. The method of any one of claims 1-4, further comprising:
determining tag data of a plurality of target objects in the favorites, and classifying the plurality of target objects according to the tag data;
or classifying the target objects in the favorites according to the user portrait data of the user.
6. An adjustment device for a collection object, comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring collection data of a target object, and the collection data comprises behavior data of a user aiming at the target object;
the recording parameter data determining module is used for determining recording parameter data of the target object according to the collection data;
the adjustment module is used for calling a favorites interface according to the recording parameter data, and moving the identification of the target object into the favorites of the user or moving the identification of the target object existing in the favorites of the user out of the favorites of the user through the called favorites interface;
the recording parameter data determining module is specifically configured to:
determining the weight and score value corresponding to each collection data, and determining the recording parameter data according to the weight and score value corresponding to each collection data;
and if the collection data includes user portrait data of the user, the determining weights corresponding to the collection data includes:
determining the matching degree of the user portrait data and the target object;
determining the weight of the user portrait data according to the matching degree;
And determining a score value corresponding to the user portrait data according to the duration of the target object matched with the user portrait browsed by the user in a preset period.
7. The apparatus of claim 6, wherein if the target object is a target web page, the behavior data comprises at least one of: the method comprises the steps of browsing frequency data of a target webpage by a user, browsing duration data of the target webpage by the user and interaction data of interaction between the user and the target webpage.
8. The apparatus of claim 6, wherein the collection data further comprises at least one of: and the user actively triggers operation data corresponding to the operation of moving the identification of the target object into or out of the favorites, user portrait data of the user and evaluation data of the target object.
9. The apparatus of claim 8, wherein the device comprises a plurality of sensors,
if the collection data comprises the operation data corresponding to the moving-in collection operation, setting the weight of the operation data corresponding to the moving-in collection operation to be higher than the weight corresponding to other collection data, and/or setting the score value of the operation data corresponding to the moving-in collection operation to be higher than the score value corresponding to other collection data;
Or alternatively, the process may be performed,
and if the collection data comprises operation data corresponding to the operation of moving out the favorites, setting the score value corresponding to the operation of moving out the favorites as a negative value.
10. The apparatus according to any one of claims 6-9, further comprising:
the classification module is used for determining tag data of a plurality of target objects in the favorites and classifying the plurality of target objects according to the tag data;
or the classification module is used for classifying the plurality of target objects in the favorites according to the user portrait data of the user.
11. A terminal device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction, where the executable instruction causes the processor to perform operations corresponding to the method for adjusting a collection object according to any one of claims 1 to 5.
12. A computer storage medium having stored thereon a computer program which, when executed by a processor, implements a method of adjusting a collection object according to any of claims 1-5.
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