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E-book pushing method, electronic equipment and storage medium

A technology for e-books and books, applied in the computer field, can solve the problems of widening the reading range, the limitation of the user's reading range, and high similarity, and achieve the effect of widening the reading range

Pending Publication Date: 2021-03-05
ZHANGYUE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, the inventor found in the process of realizing the present invention that the above-mentioned recommendation method has at least the following defects: the relevance recommendation is only made based on the historical reading behavior of the current reading user, resulting in the similarity between the multiple reading books of the current reading user. High, which in turn limits the user's reading range, which is not conducive to expanding the user's reading range based on points of interest

Method used

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  • E-book pushing method, electronic equipment and storage medium
  • E-book pushing method, electronic equipment and storage medium
  • E-book pushing method, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0026] figure 1 A flow chart of a method for pushing e-books and book sorting and pushing provided by an embodiment of the present invention is shown. like figure 1 As shown, the method includes the following steps:

[0027] Step S110: Determine a book user cluster corresponding to the target user; wherein, the book user cluster corresponds to a central book, and is used to aggregate multiple reading users who interact with the central book.

[0028] Specifically, in this embodiment, multiple book user clusters aggregated through central books are set. Wherein, each book user cluster corresponds to a central book, and each reading user in the book user cluster has deep interaction with the central book. Among them, the method of determining the central book can be flexibly set. For example, for any e-book, when the number of reading users who generate in-depth interaction with the e-book is greater than the preset number threshold, the e-book is set as the central book and ...

Embodiment 2

[0038] figure 2 A flow chart of an e-book pushing method provided by another embodiment of the present invention is shown. like figure 2 As shown, the method includes the following steps:

[0039] Step S200: According to the reading behavior data of each reading user in advance, add each reading user to the book user cluster aggregated by the central book.

[0040] Wherein, a book user cluster refers to a user set composed of multiple reading users aggregated by a central book. Each book user cluster corresponds to a central book. Therefore, in order to distinguish each book user cluster, the cluster ID of each book user cluster can be set in a form related to the book ID of the central book.

[0041] During specific implementation, book user clusters are determined in the following ways:

[0042] First, according to the reading behavior data of each reading user, interactive books corresponding to each reading user are determined. Among them, the reading behavior data ...

Embodiment 3

[0072] An embodiment of the present application provides a non-volatile computer storage medium, the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the pushing of e-books and book sorting in any of the above-mentioned method embodiments push method.

[0073] Specifically, the executable instruction can be used to make the processor perform the following operations:

[0074] Determining a book user cluster corresponding to the target user; wherein, the book user cluster corresponds to a central book, and is used for aggregating multiple reading users who interact with the central book;

[0075] For the book user cluster corresponding to the target user, determine a candidate book pool corresponding to the book user cluster, according to each reading user in the book user cluster corresponding to each candidate book in the candidate book pool The interactive depth of each candidate book in the candidate bo...

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Abstract

The invention discloses an electronic book pushing method, electronic equipment and a storage medium. The method comprises the following steps: determining a book user cluster corresponding to a target user; for the book user cluster corresponding to the target user, determining a candidate book pool corresponding to the book user cluster, and according to the interaction depth of each reading user in the book user cluster corresponding to each candidate book in the candidate book pool, calculating a cluster interestingness score of each candidate book in the candidate book pool correspondingto the book user cluster; and according to the cluster interestingness score of each candidate book in the candidate book pool corresponding to the book user cluster, calculating the interestingness of the target user corresponding to each candidate book, screening a plurality of candidate books according to a calculation result, and pushing the screened candidate books to the target user. By means of the mode, the reading range of the current user can be widened, and the user can read more valuable books.

Description

technical field [0001] The invention relates to the field of computers, in particular to an e-book pushing method, electronic equipment and a storage medium. Background technique [0002] Books in the form of e-books are favored by a large number of users due to their advantages such as easy access. Most of the book reading platforms recommend books according to the similarity of the full text of the books. In the prior art, generally several books having a high degree of similarity in book content to books that the user has read are used as recommended books and presented to the user. [0003] However, the inventor found in the process of realizing the present invention that the above-mentioned recommendation method has at least the following defects: the relevance recommendation is only made based on the historical reading behavior of the current reading user, resulting in the similarity between the multiple reading books of the current reading user. High, which in turn ...

Claims

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Application Information

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IPC IPC(8): G06F16/9535
CPCG06F16/9535
Inventor 王海璐
Owner ZHANGYUE TECH CO LTD
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