A method and system for in-text advertisement publishing based on deep semantic mining

Abstract

The invention discloses an in-text advertisement releasing method and an in-text advertisement releasing system based on deep semantic mining. The method comprises the following steps that an advertisement demand body is built; webpage contents are captured and received, webpage irrelevant to business information is removed according to the advertisement body and the text classification algorithm, the webpage types are judged, and keywords and key sentences are extracted; according to the linguistic rule, the deep semantic mining is carried out on the extracted key sentences, sentences, phases or words with commercial properties and with demands, emotion and attitude are discovered and extracted, and in addition, the advertisement marking is carried out; precise advertisement is embedded in an advertisement marking region through a generating type system, and when users browse the kind of webpage, the advertisement is shown in the specific region. The method and the system provided by the invention have the advantages that the advertisement relevant to the user reading content context demands can be issued in the webpage text contents, which page is suitable for in-text advertisement releasing in the website and the placing region and the advertisement words of the advertisement in the page can be analyzed, and the technical problems in the prior art can be solved.

Description

technical field [0001] The present invention relates to an advertisement release method and system, in particular to a content advertisement release method and system based on deep semantic mining. It belongs to the field of advertising technology. Background technique [0002] In-text advertisement is to identify the internal keywords and article characteristics of the article by computer, and display the corresponding accurate advertisement when the mouse rolls over a specific area or keyword according to these data, and the matching keywords will be marked (such as underlined Out), it accurately combines advertisement, content, and viewer closely together, and is a brand-new, gentle advertisement form completely triggered by consumers. [0003] Traditional search engine keyword advertisements store the product information that users have searched for into cookies. When users browse other websites, search engine companies analyze user cookies and assume that the informati...

AI Technical Summary

Problems solved by technology

[0006] Although internal text advertisements have many advantages, there are great shortcomings in domestic Chinese-oriented internal text advertisements

Especially at present, it is still impossible to accurately analyze the content of the page according to the semantics, so the current technology is to publish all the words related to the advertiser as advertisements. ads, greatly degrading the user experience

This is also the direct reason why internal text advertising has not been developed on a large scale; the biggest technical bottleneck faced by the internal text advertising system is that it is impossible to make advertisements relevant to the context of the article content, and it is difficult to search and analyze advertising pages and keywords , because the construction of commodity demand ontology at home and abroad is still immature, and the depth of semantic mining is insufficient. Most of the keyword extraction in the current academic research focuses on how to analyze the word frequency and structure of the article. The goal is to summarize the content of the article, which is different from the advertising itself. The fundamental goal of keyword extraction is very different. The current content advertisement publishing system is still unable to accurately identify keywords with commercial nature and contextual semantics as advertisement words

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