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

Advertisement Classification Method and Device Based on Webpage Features

A technology of web page features and classification methods, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of small number of related keywords, insufficient feature description, insufficient training data, etc., to improve efficiency and accuracy High efficiency, avoiding repetitive labor, and accurate classification results

Inactive Publication Date: 2014-10-29
亿赞普(北京)科技有限公司
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In the traditional advertisement classification technology, the advertisement-related description is usually relatively short, and the number of relevant keywords is relatively small, resulting in insufficient description of its characteristics, which is not conducive to the automatic classification of advertisements.
At the same time, there is very little labeled data for the category of advertisements, and the training data is seriously insufficient
[0006] There is currently no technology that can overcome the shortcomings of traditional technology in ad classification

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
  • Advertisement Classification Method and Device Based on Webpage Features
  • Advertisement Classification Method and Device Based on Webpage Features
  • Advertisement Classification Method and Device Based on Webpage Features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] figure 1 It is a flow chart of an advertisement classification method based on web page features according to Embodiment 1 of the present invention, combined below figure 1 Each step of the method will be described in detail.

[0039]Step S110, extracting web page feature information from web page sample information, and extracting advertisement feature information from advertisement sample information.

[0040] In this embodiment, the sample is a web page or an advertisement, and the feature is a description of the sample. A sample can be expressed as (x, y), where x is a feature vector, also called feature information. In addition, y is the category label of the sample. Usually, the advertisement sample information does not carry annotation information, and the webpage sample information carries annotation information. Annotation information is usually made based on webpage content or related query words, and refers to a judgment made manually or automatically on ...

Embodiment 2

[0072] Figure 4 is a structural diagram of an advertisement classification device based on web page category features according to the second embodiment of the present invention, combined below figure 2 Explain in detail the components of the system.

[0073] The advertisement classification device in this embodiment can be any electronic device with computing and storage functions connected to the network of each website server, and can also be a computer device integrating website servers.

[0074] The device includes the following units:

[0075] The extracting unit is configured to extract web page feature information from web page sample information, and extract advertisement feature information from advertisement sample information.

[0076] The mapping unit is connected to the extraction unit, and is used to map the web page feature information and advertisement feature information extracted by the extraction unit to a common feature space by using a transfer learni...

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 discloses an advertisement classification method and system based on a webpage characteristic. The method comprises the following steps of: extracting the webpage characteristic information from the webpage sample information and extracting the advertisement characteristic information from the advertisement sample information; mapping the webpage characteristic information and the advertisement characteristic information to a common characteristic space by use of a transfer learning method to obtain the webpage sample information and advertisement sample information mapped to the common characteristic space; training a classifier based on the webpage sample information mapped to the common characteristic space and a current training set, and classifying the advertisement sample information according to the trained classifier to obtain a classification result; establishing a link network between the webpage and the advertisement according to the historical release and click data of the advertisement sample information so that the classification result is transmitted along the link network and the corrected classification result is obtained; and updating the training set according to the corrected classification result. Through the invention, existing mark data can be sufficiently utilized, and a large amount of repeated work is avoided.

Description

technical field [0001] The invention relates to the fields of webpage classification, advertisement classification, transfer learning and the like, and in particular relates to automatic classification of advertisements by using webpage classification data. Background technique [0002] Network classified advertisement is a form of advertisement that makes full use of the advantages of computer networks to scientifically classify large-scale practical information in daily life by subject and provide quick retrieval. Recently, online classified advertisements have become a new form of online advertisements, which meet the needs of enterprises, institutions and individual merchants to publish various product and service advertisements on the Internet by using advertisement classification technology, and provide practical, Rich, authentic consumer and business information resources. Compared with traditional media classified advertisements, online classified advertisements hav...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 罗峰黄苏支李娜
Owner 亿赞普(北京)科技有限公司
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