Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Commodity recommendation method and system based on video content

A technology of product recommendation and video content, applied in the field of product recommendation based on video content, can solve the problem of low accuracy of recommendation results, and achieve the effect of reducing the amount of calculation, speeding up the processing speed, and improving the accuracy

Active Publication Date: 2015-06-17
BEIJING QIYI CENTURY SCI & TECH CO LTD
View PDF5 Cites 59 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a product recommendation method and system based

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Commodity recommendation method and system based on video content
  • Commodity recommendation method and system based on video content
  • Commodity recommendation method and system based on video content

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] refer to figure 1 , which shows a flow chart of a video content-based product recommendation method according to an embodiment of the present invention. This embodiment may specifically include the following steps:

[0031] Step 101, extract key frames from the target video.

[0032] In this embodiment, the key frame extraction of the target video can be realized by using a frame difference method based on color (or histogram), a method based on motion analysis, or a method based on video frame clustering. Among them, the key frames of the video are extracted through the video frame clustering method, that is, the frames of the video shots are divided into several categories through cluster analysis, and the points closest to the cluster center are selected to represent the cluster points, and finally the key frame set of the video sequence is formed. . It should be noted that this embodiment does not limit the specific method used for extracting the key frames of the...

Embodiment 2

[0047] On the basis of the above embodiments, this embodiment continues to discuss the video content-based commodity recommendation method.

[0048] refer to figure 2 , which shows a flow chart of a video content-based product recommendation method according to an embodiment of the present invention. This embodiment may specifically include the following steps:

[0049] Step 201, extract key frames from the target video.

[0050] In this embodiment, extracting key frames from the target video may specifically include the following sub-steps:

[0051] Sub-step 1: Shot detection is performed on the target video, and several shots are extracted. First, extract the color histogram features of each frame of the target video; secondly, calculate the similarity of the color histograms of adjacent two frames according to the color histogram features of each frame; again, when the adjacent two frames When the similarity of the color histogram is smaller than the similarity threshol...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a commodity recommendation method and system based on video content to solve the problem that the accuracy of commodity recommendation results is low. The method comprises the steps that keyframes are extracted from target video; object detection is conducted to each keyframe according to objectivity of objects, and the detected objects serve as candidate objects of each keyframe; commodity identification is conducted to the candidate objects of each keyframe through a convolutional neural network model, and commodities of each keyframe are obtained; keyword mapping is conducted to the commodities of each keyframe, and corresponding commodity tags are obtained to serve as the commodity tags of each keyframe; the commodity tags of each keyframe are determined as commodity recommendation information of the target video, and the commodity recommendation information is output. According to the commodity recommendation method and system based on the video content, the video content is taken into consideration when commodity recommendation is conducted, the video content is analyzed, and the obtained commodity recommendation information is closely bound up with the content of the target video, so that the accuracy of the the commodity recommendation results is improved.

Description

technical field [0001] The invention relates to the technical field of computer data processing, in particular to a video content-based product recommendation method and system. Background technique [0002] With the continuous development of e-commerce, more and more users choose to shop online. Users access the e-commerce website through a browser and can conveniently select the commodities they need. In many cases, e-commerce websites will recommend products to users. For example, after a user purchases a certain product, it will recommend products similar to or related to the product. products, discounted products, best-selling products and more. [0003] Generally speaking, current e-commerce websites on the Internet recommend products based on product sales rankings, user ratings on products, or analysis of other behavioral data of users on e-commerce websites. When users watch movies and TV shows, they often insert advertisements. These advertisements involve a var...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/30G06Q30/02
Inventor 兰细鹏王涛杨琛张彦刚朱成
Owner BEIJING QIYI CENTURY SCI & TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products