CN114637914A

CN114637914A - List processing method, computing device and storage medium

Info

Publication number: CN114637914A
Application number: CN202210283796.0A
Authority: CN
Inventors: 沈宗沂
Original assignee: Zhangyue Technology Co Ltd
Current assignee: Zhangyue Technology Co Ltd
Priority date: 2022-03-22
Filing date: 2022-03-22
Publication date: 2022-06-17

Abstract

The invention discloses a list processing method, a computing device and a storage medium, wherein the list processing method comprises the following steps: collecting historical behavior data of a user aiming at books in a list to be processed; analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book; and adjusting the arrangement sequence of the books in the list to be processed according to the negative feedback grade data to obtain the processed list. According to the technical scheme provided by the invention, the negative feedback level data of the user for the books is determined by analyzing the behavior path depth of the historical behavior data, and the arrangement sequence of the books in the list is adjusted according to the negative feedback level data, so that the arrangement sequence of the books which are not interested by the user can be effectively adjusted, and the arrangement sequence of the books in the list can be determined by fusing the preference of the user.

Description

List processing method, computing device and storage medium

Technical Field

The invention relates to the technical field of data processing, in particular to a list processing method, computing equipment and a storage medium.

Background

Books in the form of electronic books are popular with a large number of users because of their advantages such as easy access. The e-book platform usually includes a book list page through which books are recommended to the user. The user's actions such as clicking and reading the book can reflect the preference of the user on the book to a certain extent. However, in the conventional list processing method, books are generally arranged according to policies such as book popularity and book collection number to obtain a list, and the preference result of the books is not fed back to the list based on the user behavior, so that the books seen by the user are approximately the same each time the user browses the book list page, for example, an uninteresting book determined by the user in the previous list browsing process still exists in the next list browsing process. The list processing mode cannot well integrate the preference of the user to recommend books, so that the book recommendation effect is poor.

Disclosure of Invention

In view of the above, the present invention has been made to provide a list processing method, a computing device, and a storage medium that overcome or at least partially solve the above problems.

According to an aspect of the invention, a list processing method is provided, which includes:

collecting historical behavior data of a user aiming at books in a list to be processed;

analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book;

and adjusting the arrangement sequence of the books in the list to be processed according to the negative feedback grade data to obtain the processed list.

According to another aspect of the present invention, there is provided a computing device comprising: the processor, the memory and the communication interface complete mutual communication through the communication bus;

the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the following operations:

According to another aspect of the embodiment of the invention, a computer storage medium is provided, and at least one executable instruction is stored in the storage medium and causes a processor to execute operations corresponding to the list processing method.

According to the technical scheme provided by the invention, the historical behavior data of the user for the books is introduced into the list sorting mechanism, the negative feedback level data of the user for the books is determined by analyzing the behavior path depth of the historical behavior data, the negative feedback level data can be used for reflecting the uninterested degree of the user for the books, and the arrangement sequence of the books in the list is adjusted according to the negative feedback level data, so that the preference result of the user for the books is fed back to the list based on the behavior of the user, the effective adjustment on the arrangement sequence of the books uninterested by the user is realized, the arrangement sequence of the books in the list can be determined by fusing the preference of the user, the book list processing mode is optimized, and the better book recommendation effect is facilitated.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

fig. 1 is a flowchart illustrating a list processing method according to an embodiment of the present invention;

fig. 2a is a flowchart illustrating a list processing method according to a second embodiment of the present invention;

FIG. 2b shows a schematic diagram of a behavior path of a user for a book;

FIG. 2c is a schematic diagram showing the front-to-back arrangement of a plurality of books having the same book popularity value;

FIG. 2d shows a first display of a book listing page;

FIG. 2e shows a second display diagram of a book listing page;

fig. 3 is a schematic structural diagram of a computing device according to a fourth embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Example one

Fig. 1 is a flowchart illustrating a list processing method according to an embodiment of the present invention, and as shown in fig. 1, the method includes the following steps:

step S101, collecting historical behavior data of a user aiming at books in a list to be processed.

The list to be processed is a ranking list formed by arranging books in the electronic book platform according to the initial ranking index of the list in advance, and the ranking order of a plurality of books is recorded in the list to be processed. Considering that the behaviors of the user such as clicking and reading the book can reflect the preference of the user for the book to a certain extent, in this embodiment, historical behavior data of the user for the book is introduced into the list sorting mechanism, and the arrangement order of the book in the list to be processed is influenced by the historical behavior data of the user, so in step S101, the historical behavior data of the user for the book in the list to be processed needs to be collected. The historical behavior data of the user for the book in the list to be processed is data used for describing interaction between the user and the book, and specifically includes: exposure book behavior data, click book behavior data, reading book behavior data, adding bookshelf behavior data, and the like. The preference degree of the user for the book can be reflected through the historical behavior data.

And S102, analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book.

The books can be displayed in the book list page according to the arrangement sequence of the books, and particularly, book information such as book covers, book titles and book description texts of a plurality of books can be displayed. The behavior path of the user on the book displayed in the book list page mainly comprises the following steps: exposing books, clicking the books, entering a book detail page, reading the books, adding a bookshelf and the like. Specifically, a user can browse book information such as book covers, book names and book description texts of books in a book list page, book details are browsed by clicking the book covers, the book names and the book description texts in the book list page and entering a book detail page, the user can enter the book reading page to read the books in the book detail page by triggering a reading button and the like, and the user can add the books into the bookshelf by triggering an adding bookshelf button and the like. In order to determine negative feedback level data of the user for the book, multiple levels of feedback nodes may be set according to a behavior path depth on a behavior path of the user. After the historical behavior data are collected, the behavior path depth of the historical behavior data can be obtained by analyzing the historical behavior data, and then the node data of the feedback nodes corresponding to the behavior path depth are used as negative feedback level data of the book.

And step S103, adjusting the arrangement sequence of the books in the list to be processed according to the negative feedback level data to obtain the processed list.

The negative feedback level data is data indicating a degree of user disinterest in the book. If a certain book has negative feedback level data, which indicates that the user is not interested in the book, the recommendation weight of the book can be correspondingly reduced according to the negative feedback level data, so that the arrangement sequence of the book in the list to be processed is ranked backwards, and the processed list is obtained. Specifically, the higher the level of the negative feedback level data is, the higher the uninterested degree of the user in the book is, the more the recommendation weight is reduced, the later the ranking order of the book in the list to be processed is, so that the book uninterested by the user is ranked backwards.

By using the list processing method provided by the embodiment, the historical behavior data of the user for the book is introduced into the list sorting mechanism, the negative feedback level data of the user for the book is determined by analyzing the behavior path depth of the historical behavior data, the negative feedback level data can be used for reflecting the uninterested degree of the user for the book, and the arrangement sequence of the book in the list is adjusted according to the negative feedback level data, so that the preference result of the user for the book is fed back to the list based on the behavior of the user, the effective adjustment of the arrangement sequence of the book uninterested by the user is realized, the arrangement sequence of the book in the list can be determined by fusing the preference of the user, the book list processing mode is optimized, and a better book recommendation effect is obtained.

Example two

Fig. 2a is a schematic flowchart illustrating a list processing method according to a second embodiment of the present invention, and as shown in fig. 2a, the method includes the following steps:

step S201, collecting historical behavior data of the user aiming at the books in the list to be processed.

In this embodiment, considering that the historical behavior data of the user for the books in the list to be processed can reflect the preference degree of the user for the books, the historical behavior data of the user for the books is introduced into the list sorting mechanism, the arrangement order of the books in the list to be processed is influenced by the historical behavior data of the user, and the historical behavior data of the user for the books in the list to be processed may be collected from an electronic book platform or the like in step S201. Wherein, the historical behavior data may include: exposing book behavior data, clicking book behavior data, reading book behavior data, and adding bookshelf behavior data. The historical behavior data may also include other data of the interaction between the user and the book, and is not limited herein.

Step S202, setting a multi-level feedback node on a behavior path of the user for the book according to the behavior path depth.

By analyzing the behavior path of the user for the book, the behavior path mainly includes: exposing books, clicking the books, entering a book detail page, reading the books, adding a bookshelf and the like. Fig. 2b is a schematic diagram illustrating a behavior path of a user for a book, and as shown in fig. 2b, the behavior path mainly includes: exposing book information of the book to a user on a book list page; judging whether the user clicks the book information of the book, if so, entering a book detail page, and if not, returning the book list page by the user, and exposing the book information of other books to the user on the book list page; after entering a book detail page, judging whether a user triggers a reading button, if so, entering the book reading page, and if not, returning the book list page by the user, and exposing book information of other books to the user on the book list page; after entering a book reading page, if the user finds that the book is liked by reading and continues to read later, the book can be added into the bookshelf, if the user finds that the book is disliked by reading, the book list page can be returned, and book information of other books is exposed to the user on the book list page.

According to the behavior path, the preference of the user for the book can be predicted according to the operation behavior of the user for the book in the list to be processed, and if the operation behavior of the user is 'exposing the book, clicking the book, reading the book and adding the bookshelf', the user can be determined to like the book; on the contrary, if the user performs a series of operations of "exposing the book", "clicking the book", and "reading the book", but does not add the book to the bookshelf at last, it may be determined that the user is not interested in the book; since the more the user knows about a book, the higher the possibility that the user makes a decision, the more the series of operations are performed without adding a bookshelf, the higher the possibility that the user is determined to be uninterested in the book.

In step S202, the behavior path of the user for the book is analyzed, a node that can reflect negative feedback of the user is searched, and a multi-stage feedback node is set on the behavior path according to the depth of the behavior path. Specifically, considering that negative feedback of the user can be represented by exposing the book but not clicking the book by the user, clicking the book but not reading by the user, and reading the book but not adding the bookshelf by the user, and can be used for reflecting the degree of disinterest of the user in the book, the set multi-stage feedback nodes may include: the method comprises the steps of exposing the book without clicking a feedback node corresponding to the book, clicking the book without reading the feedback node corresponding to the book, and reading the book without adding a feedback node corresponding to the bookshelf. Since the more the user knows about a book, the higher the possibility of making a decision, the deeper the action path depth without adding a bookshelf, the higher the possibility of determining that the user is not interested in the book, and the higher the level of the corresponding feedback node. As shown in fig. 2b, the feedback node corresponding to the exposed book without clicking the book is a first-level feedback node, the feedback node corresponding to the clicked book without reading the book is a second-level feedback node, and the feedback node corresponding to the read book without adding the bookshelf is a third-level feedback node, wherein the level data of the 3 feedback nodes with different levels can be used for reflecting the degree of the user not interested in the book, the level of the third-level feedback node is higher than that of the second-level feedback node, and the level of the second-level feedback node is higher than that of the first-level feedback node.

Step S203, analyzing the behavior path depth of the historical behavior data to obtain a feedback node corresponding to the behavior path depth, and using the node data of the feedback node as negative feedback level data of the user for the book.

Specifically, the behavior path depth of the historical behavior data collected in step S201 is analyzed, and if the analyzed behavior path depth has a corresponding feedback node, the node data of the feedback node is used as negative feedback level data of the book. The node data of the feedback node may specifically include data such as a level of the feedback node, and a behavior path depth corresponding to the feedback node. Those skilled in the art can also set the node data to include other data, which is not limited herein.

For example, as shown in fig. 2b, if the collected behavior path depth of the historical behavior data of the book 1 in the list to be processed by the user is to expose the book without clicking the book, the collected behavior path depth corresponds to a first-level feedback node, and the node data of the first-level feedback node is used as the negative feedback level data of the book 1, for example, the negative feedback level data of the book 1 may include a first level, and the corresponding behavior path depth is to expose the book without clicking the book.

After the negative feedback level data is obtained, the arrangement sequence of the books in the list to be processed can be adjusted according to the negative feedback level data, and the processed list is obtained. If a certain book has negative feedback level data, which indicates that the user is not interested in the book, the recommendation weight of the book can be correspondingly reduced according to the negative feedback level data, so as to rank the book backwards in the ranking order of the book to be processed. In a practical application scenario, the list to be processed refers to a ranking list formed by arranging books in an electronic book platform in advance according to an initial ranking index of the list, where the list to be processed includes many books, for example, one list to be processed includes 30 thousands of books, and many books may exist under the same initial ranking index of the list, so that the order of the books in the list to be processed may be adjusted according to negative feedback level data of the books under the same initial ranking index of the list. And for books with different initial ranking indexes of the lists, the books are still ranked according to the preset sequence of the initial ranking indexes of the lists. Specifically, the implementation is performed by step S204 to step S208.

Step S204, collecting initial ranking indexes of the lists of the books in the list to be processed.

The list initial ranking index comprises the following indexes: book popularity, number of readers, number of books praise, number of books collected, book scoring, update time, author focus parameters, and/or cumulative length of reading. The author concern parameter can be specifically the number of author fans and the like.

Step S205, judging whether the initial ranking indexes of any two books in the list to be processed are the same; if yes, go to step S206; if not, go to step S207.

And step S206, according to the negative feedback grade data, reducing the recommendation weight of the books corresponding to the negative feedback grade data, and according to the recommendation weight, adjusting the arrangement sequence of any two books in the list to be processed.

Under the condition that the initial ranking indexes of the lists of any two books are judged to be the same, the recommendation weight of the book corresponding to the negative feedback level data is adjusted to be low according to the negative feedback level data, the arrangement sequence of any two books in the list to be processed is adjusted according to the preset sequence of the recommendation weight, wherein the recommendation weight corresponds to the negative feedback level data, and the higher the level of the negative feedback level data is, the lower the recommendation weight is.

The initial ranking index of the list is used as the popularity value of the book to be introduced. In the list to be processed, books are sorted in the order of their popularity value from high to low as a whole, wherein the book popularity value is usually in ten thousand units. For a plurality of books with the same book popularity value, the recommendation weight of the book corresponding to the negative feedback level data is reduced, so that the higher the level of the negative feedback level data is, the lower the recommendation weight of the book corresponding to the negative feedback level data is. That is, for a plurality of books having the same book popularity value, in which the recommendation weight of an unexposed book > the recommendation weight of an exposed and unchecked book > the recommendation weight of a clicked and unread book > the recommendation weight of a read and unread book, the higher the recommendation weight is, the more forward the arrangement order of the corresponding book in the plurality of books having the same book popularity value is. Fig. 2c is a schematic view showing an arrangement order of a plurality of books having the same book popularity value from front to back, and as shown in fig. 2c, among the plurality of books having the same book popularity value, an unexposed book is arranged most forward, an exposed and unchecked book is arranged behind the unexposed book, a clicked and unread book is arranged behind the exposed and unchecked book, and a book that is read without being added to a bookshelf is arranged behind the clicked and unread book.

Step S207, determining the ranking order of any two books in the list to be processed according to the preset order of the initial ranking indexes of the list.

Wherein, the preset sequence can be from high to low or from low to high. Taking the initial ranking index of the list as the popularity value of the books, and taking the preset sequence as the sequence from high to low as an example, assuming that two books are book 1 and book 2, the user has negative feedback level data for book 1 and no negative feedback level data for book 2, but since the popularity value of book 1 is higher than that of book 2, the arrangement sequence of book 1 in the list to be processed is before the arrangement sequence of book 2, that is, book 1 is arranged in front of book 2.

And step S208, obtaining the processed list.

And after the sequencing is completed for all the books in the list to be processed, the list after processing can be obtained.

And step S209, adding behavior marks to the books according to the historical behavior data.

In order to facilitate the user to quickly identify which books in the book list page are the books which are read but not added to the bookshelf and which books are the books which are added to the bookshelf, behavior marks can be added to the books corresponding to the historical behavior data according to the historical behavior data, wherein the behavior marks include read marks and/or on-bookshelf marks. The specific mark form of the behavior mark can be set by those skilled in the art according to actual needs, and is not limited herein.

Specifically, the read flag is used to identify a book that has been read by the user without being added to the bookshelf, and the on-shelf flag is used to identify a book that has been added to the bookshelf by the user. If the user knows that the user has read the book but does not add the book to the bookshelf according to the historical behavior data of the book, adding a read mark to the book; if the user knows that the book is added to the bookshelf according to the historical behavior data of the book, a bookshelf mark is added to the book.

In step S210, the book information of each book and the behavior flag of each book in the processed list are displayed on the book list page.

When the user enters the book list page, the book information of each book and the behavior marks of each book in the processed list can be displayed in the book list page. Fig. 2d shows a first display diagram of a book list page, as shown in fig. 2d, a list obtained by arranging books of publication types in order of popularity of the books from high to low is shown in the book list page, wherein a book card area 21 of a plurality of books is shown in the book list page, book information of the books is shown in the book card area 21 of each book, the book information includes book covers, book names, and book description texts, and "X" represents a character. For a book that has been read by the user but not added to the bookshelf, a read mark 22, i.e. a mark in the form of a "read" text shown in fig. 2d, is displayed at the upper right corner of the book card area 21; for a book that the user has added to the bookshelf, the upper right corner of the book card area 21 is shown with a label 23 on the bookshelf, i.e. a label in the form of "on the shelf" text shown in fig. 2 d.

Optionally, a function of shielding books that have been read by the user in the list but not added to the bookshelf may also be provided in the book list page. The read shielding switch assembly can be arranged at a preset position of the book list page, and a person skilled in the art can set the preset position according to actual needs. The user can turn on or off the shielding function by triggering the read shielding switch assembly.

Specifically, in response to a user's request for turning on the read shielding switch component in the book list page, the read books of the user are removed from the books of the processed list displayed on the book list page, where the read books may specifically include books that have been read by the user but not added to the bookshelf. The person skilled in the art may also set the read book to include a book that has been read by the user and has been added to the bookshelf, and the like, which is not limited herein.

That is, only the unread books of the user may be displayed in the book list page without displaying the read books of the user, so that the user can quickly screen the unread books from the list for browsing. In addition, in the case that the user has turned on the shielding function, the shielding function may be turned off by triggering the read shielding switch component again, and specifically, in response to a turn-off request of the user for the read shielding switch component in the book list page, display of the read book of the user in the book list page is resumed, that is, book information of each of the books in the processed list is displayed in the book list page, where the displayed books include an unread book and a read book of the user.

As shown in fig. 2d, a read shielding switch assembly 24 is disposed at the upper right corner of the book list page, and a user can turn on or off the shielding function by triggering the read shielding switch assembly 24. If the user activates the shielding function by triggering the read shielding switch assembly 24, the updated book list page may remove the book with the read mark, i.e., remove the book 1, from the list displayed on the book list page as shown in fig. 2e, and display the book information of more books according to the arrangement order of the books in the list. If the user continues to trigger the read shielding switch component 24 in the page state shown in fig. 2e, the shielding function is turned off, and the book list page is restored to the page state shown in fig. 2 d.

By using the list processing method provided by this embodiment, historical behavior data of a user for books is introduced into a list sorting mechanism, a multistage feedback node is set on a behavior path of the user for the books according to a behavior path depth, negative feedback level data of the user for the books is determined by analyzing the behavior path depth of the historical behavior data, and for a plurality of books having the same list initial sorting index, recommendation weights of the books corresponding to the negative feedback level data are adjusted to be lower, so that the higher the level of the negative feedback level data is, the lower the recommendation weight of the corresponding book is, and books which are not interested by the user are sorted backwards according to the recommendation weights, so that the arrangement order of the books in the list can well fuse preferences of the user, and a better book recommendation effect is obtained; in addition, behavior marks can be added to the books according to historical behavior data, so that a user can quickly and conveniently identify which books in the book list page are the books read by the user without being added to the bookshelf and which books are the books added to the bookshelf; in addition, a read shielding function is provided, the read books in the list are screened out for the user, and the user can find the unread books conveniently.

EXAMPLE III

A third embodiment of the present invention provides a nonvolatile storage medium, where the storage medium stores at least one executable instruction, and the executable instruction may execute the list processing method in any method embodiment described above.

The executable instructions may be specifically configured to cause the processor to: collecting historical behavior data of a user for books in a list to be processed; analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book; and adjusting the arrangement sequence of the books in the list to be processed according to the negative feedback grade data to obtain the processed list.

In an alternative embodiment, the historical behavior data includes: exposing book behavior data, clicking book behavior data, reading book behavior data, and adding bookshelf behavior data.

In an alternative embodiment, the executable instructions further cause the processor to: setting a multi-stage feedback node on a behavior path of a user for the book according to the behavior path depth; and analyzing the behavior path depth of the historical behavior data to obtain a feedback node corresponding to the behavior path depth, and taking the node data of the feedback node as negative feedback level data of the user for the book.

In an alternative embodiment, the multi-level feedback node comprises: the method comprises the steps of exposing the book without clicking a feedback node corresponding to the book, clicking the book without reading the feedback node corresponding to the book, and reading the book without adding a feedback node corresponding to the bookshelf.

In an alternative embodiment, the executable instructions further cause the processor to: acquiring list initial sequencing indexes of each book in a list to be processed; judging whether the initial ranking indexes of any two books in the list to be processed are the same; if yes, according to the negative feedback grade data, reducing the recommendation weight of the books corresponding to the negative feedback grade data, and according to the recommendation weight, adjusting the arrangement sequence of any two books in the list to be processed; and if not, determining the arrangement sequence of any two books in the list to be processed according to the preset sequence of the initial list arrangement indexes.

In an optional implementation manner, the list initial ranking index includes: book popularity, number of readers, number of books praise, number of books collected, book scoring, update time, author focus parameters, and/or cumulative length of reading.

In an alternative embodiment, the executable instructions further cause the processor to: adding behavior marks for the books according to historical behavior data; wherein the behavior mark comprises a read mark and/or a mark on a bookshelf; and displaying the book information of each book and the behavior mark of each book in the processed list in the book list page.

In an alternative embodiment, the executable instructions further cause the processor to: in response to a user's opening operation of the read shield switch component in the book list page, removing the user's read books from the respective books of the processed list presented on the book list page.

Example four

Fig. 3 is a schematic structural diagram of a computing device according to a fourth embodiment of the present invention, where the embodiment of the present invention does not limit a specific implementation of the computing device.

As shown in fig. 3, the computing device may include: a processor (processor)302, a communication Interface 304, a memory 306, and a communication bus 308.

Wherein:

the processor 302, communication interface 304, and memory 306 communicate with each other via a communication bus 308.

A communication interface 304 for communicating with network elements of other devices, such as clients or other servers.

The processor 302 is configured to execute the program 310, and may specifically execute relevant steps in the foregoing list processing method embodiment.

In particular, program 310 may include program code comprising computer operating instructions.

The processor 302 may be a central processing unit CPU, or an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement an embodiment of the present invention. The computing device includes one or more processors, which may be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.

A memory 306 for storing a program 310. Memory 306 may comprise high-speed RAM memory and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The program 310 may specifically be configured to cause the processor 302 to perform the following operations: collecting historical behavior data of a user aiming at books in a list to be processed; analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book; and adjusting the arrangement sequence of the books in the list to be processed according to the negative feedback grade data to obtain the processed list.

In an alternative embodiment, the historical behavior data includes: exposing book behavior data, clicking book behavior data, reading book behavior data and adding bookshelf behavior data.

In an alternative embodiment, program 310 further causes processor 302 to: setting a multi-level feedback node on a behavior path of a user for the book according to the behavior path depth; analyzing the behavior path depth of the historical behavior data to obtain a feedback node corresponding to the behavior path depth, and taking the node data of the feedback node as negative feedback level data of the user for the book.

In an alternative embodiment, program 310 further causes processor 302 to: acquiring list initial sequencing indexes of each book in a list to be processed; judging whether the initial ranking indexes of the lists of any two books in the list to be processed are the same or not; if yes, according to the negative feedback grade data, reducing the recommendation weight of the books corresponding to the negative feedback grade data, and according to the recommendation weight, adjusting the arrangement sequence of any two books in the list to be processed; and if not, determining the arrangement sequence of any two books in the list to be processed according to the preset sequence of the initial list arrangement indexes.

In an alternative embodiment, program 310 further causes processor 302 to: adding behavior marks for the books according to historical behavior data; wherein the behavior mark comprises a read mark and/or a mark on a bookshelf; and displaying the book information of each book and the behavior mark of each book in the processed list in the book list page.

In an alternative embodiment, program 310 further causes processor 302 to: in response to a user's opening operation for the read shield switch component in the book list page, removing the user's read books from the respective books of the processed list presented by the book list page.

For specific implementation of each step in the program 310, reference may be made to the description corresponding to the corresponding step in the foregoing list processing embodiment, which is not described herein again. It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the above-described device may refer to the corresponding process description in the foregoing method embodiment, and is not described herein again.

According to the scheme provided by the embodiment, the negative feedback level data of the user for the books is determined by analyzing the behavior path depth of the historical behavior data, the arrangement sequence of the books in the list is adjusted according to the negative feedback level data, the arrangement sequence of the books which are not interested by the user is effectively adjusted, and the arrangement sequence of the books in the list can be determined by fusing the preference of the user.

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system is apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

The invention discloses:

A1. a list processing method comprises the following steps:

and adjusting the arrangement sequence of the books in the list to be processed according to the negative feedback level data to obtain the processed list.

A2. The method of a1, the historical behavior data comprising: exposing book behavior data, clicking book behavior data, reading book behavior data, and adding bookshelf behavior data.

A3. Before the analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book according to the method of a1, the method further includes: setting a multi-level feedback node on a behavior path of a user for the book according to the behavior path depth;

the analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book further comprises:

analyzing the behavior path depth of the historical behavior data to obtain a feedback node corresponding to the behavior path depth, and taking the node data of the feedback node as negative feedback level data of the user for the book.

A4. The method of a3, the multi-stage feedback node comprising: the method comprises the steps of exposing the book without clicking a feedback node corresponding to the book, clicking the book without reading the feedback node corresponding to the book, and reading the book without adding a feedback node corresponding to the bookshelf.

A5. The method of any of a1-a4, wherein the adjusting the order of the books in the chart to be processed according to the negative feedback level data further comprises:

acquiring list initial sequencing indexes of each book in the list to be processed;

judging whether the initial ranking indexes of any two books in the list to be processed are the same;

if yes, according to the negative feedback level data, reducing recommendation weights of books corresponding to the negative feedback level data, and adjusting the arrangement sequence of any two books in the list to be processed according to the recommendation weights;

and if not, determining the arrangement sequence of any two books in the list to be processed according to the preset sequence of the initial ranking indexes of the list.

A6. The method of a5, the initial ranking indicator of the listing comprising: book popularity, number of readers, number of books praise, number of books collected, book scoring, update time, author focus parameters, and/or cumulative length of reading.

A7. The method of any one of a1-a6, the method further comprising:

adding behavior marks to the books according to the historical behavior data; wherein the behavior mark comprises a read mark and/or a mark on a bookshelf;

and displaying the book information of each book and the behavior mark of each book in the processed list in the book list page.

A8. The method of any one of a1-a7, the method further comprising:

in response to a user's opening operation of the read shield switch component in the book list page, removing the user's read books from the respective books of the processed list presented by the book list page.

B9. A computing device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus;

the memory is configured to store at least one executable instruction that causes the processor to:

B10. The computing device of B9, the historical behavior data comprising: exposing book behavior data, clicking book behavior data, reading book behavior data, and adding bookshelf behavior data.

B11. The computing device of B9, the executable instructions further cause the processor to:

setting a multi-level feedback node on a behavior path of a user for the book according to the behavior path depth;

B12. The computing device of B11, the multi-level feedback node comprising: the method comprises the steps of exposing the book without clicking a feedback node corresponding to the book, clicking the book without reading the feedback node corresponding to the book, and reading the book without adding a feedback node corresponding to the bookshelf.

B13. The computing device of any of B9-B12, the executable instructions further cause the processor to:

judging whether the initial ranking indexes of the list of any two books in the list to be processed are the same or not;

B14. The computing device of B13, the leaderboard initial ranking indicator comprising: book popularity value, number of readers, number of book praise, number of book collectors, book scoring, update time, author attention parameter, and/or reading accumulated time.

B15. The computing device of any of B9-B14, the executable instructions further cause the processor to:

B16. The computing device of any of B9-B15, the executable instructions further cause the processor to:

C17. A computer storage medium having stored therein at least one executable instruction that causes a processor to perform operations corresponding to the list processing method of any of a 1-A8.

Claims

1. A list processing method comprises the following steps:

2. The method of claim 1, the historical behavior data comprising: exposing book behavior data, clicking book behavior data, reading book behavior data and adding bookshelf behavior data.

3. The method of claim 1, before the analyzing the behavior path depth of the historical behavior data for negative feedback level data of a user for the book, the method further comprising: setting a multi-level feedback node on a behavior path of a user for the book according to the behavior path depth;

analyzing the behavior path depth of the historical behavior data to obtain negative feedback level data of the user for the book further comprises:

4. The method of claim 3, the multi-level feedback node comprising: the method comprises the steps of exposing the book without clicking a feedback node corresponding to the book, clicking the book without reading the feedback node corresponding to the book, and reading the book without adding a feedback node corresponding to the bookshelf.

5. The method of any of claims 1-4, wherein the adjusting the order of the books in the chart to be processed according to the negative feedback level data further comprises:

6. The method of claim 5, the leaderboard initial ranking indicator comprising: book popularity value, number of readers, number of book praise, number of book collectors, book scoring, update time, author attention parameter, and/or reading accumulated time.

7. The method of any of claims 1-6, further comprising:

8. The method of any of claims 1-7, further comprising:

9. A computing device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus;

10. A computer storage medium having stored therein at least one executable instruction that causes a processor to perform operations corresponding to the list processing method of any one of claims 1-8.