Topic Grabbing Method Based on Anchor Text Context and Link Analysis

Abstract

The invention relates to an internet search technology and aims to provide a theme capturing method based on anchor text context and link analysis. The theme capturing method based on anchor text context and link analysis includes: computing a global priority of a link, computing a partial priority of the link and computing a final priority of the link. The theme capturing method based on anchor text context and link analysis has the advantages that webpage quality can be quickly estimated, preceding part of a text of the link can be acquired, and accuracy of theme relevancy prediction of the link can be increased according to the preceding part of the text.

Description

technical field [0001] The invention relates to Internet search technology, in particular to a topic grabbing method based on anchor text context and link analysis. Background technique [0002] With the rapid development of the Internet, various Internet products emerge in an endless stream, such as social networking, instant messaging, online shopping, personal blogs, vertical communities, etc. These products have changed the way people obtain information in the past. Especially with the advent of the web2.0 era, everyone is a producer of information. According to the "31st Statistical Report on Internet Development in China" released by CNNIC, China's Internet penetration rate exceeds 40%, and Internet users have reached 564 million. [0003] The information on the Internet is also growing explosively. According to research, at the beginning of the 21st century, Google indexed 2 billion web pages, while the size of the Internet at that time was about 4 billion to 10 bill...

AI Technical Summary

Problems solved by technology

[0004] Search engines such as Google or Baidu are the main entrances for everyone to obtain network resources, but research shows that general search engines have certain limitations:

[0018] Guan et al. pointed out the limitations of this algorithm: this algorithm needs to store the web graph of the downloaded pages, and needs to iteratively access and modify this web graph. As the crawler runs, the web graph becomes larger and larger, and the cost of each iteration increases. Become very large, seriously affecting the scalability of the crawler

[0020] But this method does not explain why only the highest quality pages need to be recrawled to solve the problem of insufficient link quality transfer in the network dynamic discovery process. In addition, this method uses a window around the link to predict the relevance of the link to the topic , the definition of window is unreasonable

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