Display method, apparatus, computer device and storage medium

Patent metadata

Field	Value
Publication number	US-12443639-B2
Application number	US-202318531244-A
Country	US
Kind code	B2
Filing date	Dec 6, 2023
Priority date	Dec 23, 2022
Publication date	Oct 14, 2025
Grant date	Oct 14, 2025

Abstract

The present disclosure provides a display method, apparatus, computer device and storage medium, wherein the method comprises: in response to a trigger operation for any of book recommendation topics, acquiring a plurality of topic posts under the book recommendation topic, and target filtering items matching the topic posts; wherein the target filtering items are determined based on book recommendation information of the topic posts and book information recommended in the topic posts; displaying the target filtering items; and in response to one of the target filtering items being selected, displaying topic posts associated with the one of the target filtering items.

First claim

What is claimed is:

1. A display method, comprising:
in response to a trigger operation for any of book recommendation topics, acquiring a plurality of topic posts under the book recommendation topic, and target filtering items matching the topic posts; wherein the target filtering items are determined based on book recommendation information of the topic posts and book information recommended in the topic posts;
displaying the target filtering items; and
in response to one of the target filtering items being selected, displaying topic posts associated with the one of the target filtering items,
wherein the target filtering items matching the topic posts are determined by:
determining target attribute characteristics according to common information of various books corresponding to the book information recommended in the topic posts;
segmenting the book recommendation information of each of the topic posts respectively according to preset segmentation dimensions, to obtain at least one initial keyword of each of the topic posts under the preset segmentation dimensions;
filtering out recommendation keywords that match the target attribute characteristics from the initial keywords; and
generating the target filtering items based on the recommendation keywords and the target attribute characteristics.

2. The method according to claim 1 , wherein the preset segmentation dimension includes at least one of a first segmentation dimension determined according to the relationship between characters in a book, a second segmentation dimension determined according to the personalities of characters in a book, and a third segmentation dimension determined according to part-of-speech attributes.

3. The method according to claim 1 , wherein generating the target filtering items based on the recommendation keywords and the target attribute characteristics comprises:
generating at least one first filtering item based on the recommendation keywords, and generating at least one second filtering item based on the target attribute characteristics;
determining the target filtering items based on the at least one first filtering item and the at least one second filtering item.

4. The method of claim 3 , wherein determining the target filtering items based on the at least one first filtering item and the at least one second filtering item comprises:
determining the number of filtering items corresponding to a target type according to the type of each of the second filtering items;
in a case that the number of filtering items is greater than a first preset number, determining sorting orders of individual second filtering items of the target type according to a first number of books corresponding to each second filtering item of the target type in order from high to low in quantity;
taking the second filtering items whose sorting order is greater than a preset order, the at least one first filtering item, and other second filtering items than the second filtering items of the target type as the target filtering items.

5. The method according to claim 3 , wherein the second filtering item includes a first sub-filtering item for characterizing a book type of a book;
the generating at least one second filtering item based on the target attribute characteristics comprising:
recognizing the book recommendation topics semantically to determine book search intention; the book search intention being used to indicate attribute characteristics of the book to be found corresponding to the book recommendation topics;
in a case that the type of the book search intention complies with a first preset type, acquiring reading type indication information corresponding to the user who triggers the book recommendation topic; the first preset type including at least one of a non-directional type and a score being higher than a set threshold type; the reading type indication information being used to indicate each of book types of interest;
determining a second number of a first book under each of the book types of interest according to the book type of each of the books indicated by the target attribute characteristics;
generating at least one of the first sub-filtering items according to the corresponding second number of book types of interest being greater than a second preset number.

6. The method according to claim 3 , wherein the second filtering item includes a second sub-filtering item for characterizing a book genre of a book;
the generating at least one second filtering item based on the target attribute characteristics comprising:
in a case that the type of book search intention meets a second preset type, determining a third number of topic posts in the book recommendation topics; the second preset type including at least one preset book genre type;
in a case that the third number is greater than a third preset number, determining a fourth number of a second book that matches the type of the book search intention according to the book genre of each of the book indicated by the target attribute characteristics;
in a case that the ratio between the fourth number and the total number of books corresponding to the book information is greater than a preset ratio, generating at least one of the second sub-filtering items according to the type of the book search intention.

7. The method according to claim 3 , wherein the second filtering item includes at least one of a third sub-filtering item for characterizing a completed status of a book or a fourth sub-filtering item for characterizing a book score for a book;
the generating at least one second filtering item based on the target attribute characteristics comprises at least one of:
in a case that it is determined that there is a book whose update status is a completed status based on the book update status of each of the books indicated by the target attribute characteristics, generating the third sub-filtering item; and
in a case that it is determined that there is a book with a book score greater than a set threshold based on the book score of each of the books indicated by the target attribute characteristics, generating the fourth sub-filtering item.

8. A computer device, comprising: a processor and a memory having machine-readable instructions executable by the processor stored thereon, the processor being configured to execute the machine-readable instructions stored in the memory, when the machine-readable instructions are executed by the processor, executes a display method, the display method comprises:
in response to a trigger operation for any of book recommendation topics, acquiring a plurality of topic posts under the book recommendation topic, and target filtering items matching the topic posts; wherein the target filtering items are determined based on book recommendation information of the topic posts and book information recommended in the topic posts;
displaying the target filtering items; and
in response to one of the target filtering items being selected, displaying topic posts associated with the one of the target filtering items,
wherein the target filtering items matching the topic posts are determined by:
determining target attribute characteristics according to common information of various books corresponding to the book information recommended in the topic posts;
segmenting the book recommendation information of each of the topic posts respectively according to preset segmentation dimensions, to obtain at least one initial keyword of each of the topic posts under the preset segmentation dimensions;
filtering out recommendation keywords that match the target attribute characteristics from the initial keywords; and
generating the target filtering items based on the recommendation keywo

Assignees

• Beijing Zitiao Network Technology Co Ltd

Inventors

• Li Xiaojie
• Li Yiyong
• Cao Zhiying
• Deng Qi

Classifications

• G06F40/284

  Lexical analysis, e.g. tokenisation or collocates · CPC title

• G06F16/3323 Primary

  using document space presentation or visualization, e.g. category, hierarchy or range presentation and selection · CPC title

• G06F16/9535

  Search customisation based on user profiles and personalisation · CPC title

• G06F16/00

  Information retrieval; Database structures therefor; File system structures therefor · CPC title

• G06F16/335 Primary

  Filtering based on additional data, e.g. user or group profiles (filtering in web context G06F16/9535, G06F16/9536) · CPC title