Electronic book recommendation method, electronic equipment and computer storage medium

A recommendation method and e-book technology, applied in the computer field, can solve the problems of single type of e-book, poor user experience, poor recommendation effect, etc., and achieve better recommendation effect and rich types

Inactive Publication Date: 2018-03-06
ZHANGYUE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the process of using the reader, one type of scenario is that the system will actively recommend some e-books to the user while the user is browsing e-books, but the existing recommendation schemes are based on the reading history data of the recommended users. Recommendations, or recommendations by analyzing user preferences, these recommendation methods only consider the preferences of the recommended users, result

Method used

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  • Electronic book recommendation method, electronic equipment and computer storage medium
  • Electronic book recommendation method, electronic equipment and computer storage medium
  • Electronic book recommendation method, electronic equipment and computer storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0017] figure 1 A flow chart of an e-book recommending method provided in Embodiment 1 of the present invention is shown, which is used for recommending an e-book to a first user. Such as figure 1 As shown, the method includes the following steps:

[0018] Step S101, searching for at least one second user whose attribute is similar to that of the first user.

[0019] In the present invention, the user who needs to recommend e-books is called the first user, and according to the attribute similarity of each user, the user whose attribute is similar to the first user is called the second user. Among them, the e-book recommendation requirement can be the active recommendation requirement of the system in some scenarios, or the recommendation requirement obtained according to the search request of the first user; "Like" and other columns to make active recommendations and other scenarios.

[0020] In this step, the attribute feature of at least one attribute of each user and t...

Embodiment 2

[0028] figure 2 A flow chart of the e-book recommendation method provided by Embodiment 2 of the present invention is shown. This embodiment is applied to the scenario where the system actively recommends e-books to the first user, such as figure 2 As shown, the method includes:

[0029] Step S201, calculating the attribute similarity between users according to the attribute information of at least one preset dimension.

[0030] Since the solution of the present invention is mainly applicable to e-book recommendation, in order to make the candidate e-book set recommended to the first user based on the reading history data of similar users more suitable for the interests and concerns of the first user, it is necessary to start from The attribute similarity between users is calculated on at least one preset dimension; and the at least one preset dimension is selected based on the principle of reflecting the user's reading habits or reading preferences. In other words, the de...

Embodiment 3

[0061] image 3 A flow chart of an e-book recommendation method provided by Embodiment 3 of the present invention is shown, and this embodiment is applied to a scenario where a first user inputs a search condition to initiate an e-book search request. Such as image 3 As shown, the method includes the following steps:

[0062] Step S301, receiving an e-book search request carrying search conditions sent by a first user.

[0063] In the process of using the reader, the user will purposely search for some e-books that meet the search conditions. "Update" and other tags for the user to choose, and the user enters the search criteria by selecting the search tag to initiate an e-book search request.

[0064] Step S302, calculating the attribute similarity between users according to the attribute information of at least one preset dimension.

[0065] Step S303, find out at least one second user whose attribute similarity with the first user is higher than a preset threshold.

...

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Abstract

The invention discloses an electronic book recommendation method, electronic equipment and a computer storage medium. The electronic book recommendation method is used for recommending electronic books to a first user. The method comprises the steps of searching for at least one second user similar to attributes of the first user; determining an electronic book set used for complementary recommendation according to reading history data of at least one second user; selecting the electronic books from the electronic book set to be recommended to the first user. As can be seen, considering similarities among attributes of the similar users, provided is the novel electronic book complementary recommendation method in which the electronic books are screened from the reading history data of thesimilar users to be recommended to the first user, and the types of the recommended electronic books are richer.

Description

technical field [0001] The invention relates to the technical field of computers, in particular to an e-book recommendation method, electronic equipment and a computer storage medium. Background technique [0002] At present, with the popularity of mobile terminals such as mobile phones and the development of e-book readers, e-books are becoming more and more popular among readers. [0003] In the process of using the reader, one type of scenario is that the system will actively recommend some e-books to the user while the user is browsing e-books, but the existing recommendation schemes are based on the reading history data of the recommended users. Recommendations, or recommendations by analyzing user preferences, these recommendation methods only consider the preferences of the recommended users, resulting in a relatively single type of recommended e-books and poor recommendation results; another type of scenario is that users retrieve e-books by inputting search conditio...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/06
CPCG06F16/9535G06Q30/0631
Inventor 田敬焘
Owner ZHANGYUE TECH CO LTD
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