Time Travel: 2014

As for why Google is interested in the algorithm proposed by Lin Hui?

This has a lot to do with Google's history.

The reason why Google is what it is today is largely because of the PageRank algorithm.

In the early days of the Internet, as the number of web pages on the Internet gradually increased, how to retrieve the pages we wanted from the massive web pages became very important.

At that time, the famous Ya/hoo and other Internet companies tried to solve this problem, but they failed to find a good solution.

It was not until around 1998 that two PhD students at Stanford University, Larry Page and Sergey Brin, jointly invented the famous PageRank algorithm, which perfectly solved the problem of web page ranking.

It is precisely because of this algorithm that Google/Google was born.

PageRank is a technique that calculates the importance of web pages through the hyperlinks between them.

Named after the surname of Google founder Larry Page, Google’s naming it also reflects the importance of the algorithm.

This algorithm can calculate the numerical value that reflects the relevance and importance of a web page.

PageRank determines the rank of a page through the vast hyperlink relationship on the Internet. It interprets the link from page A to page B as page A voting for page B. Google/Google based on the rank and voting target of page A or even pages linked to A. to determine the grade of B.

Simply put, a high-level page can improve the level of other low-level pages.

This algorithm regards the entire Internet as a directed graph, web pages are nodes in the graph, and links between web pages are edges in the graph.

With the help of this algorithm, the relevance of the root search keywords of different web pages can be measured to rank the web pages.

Over a long period of time, you get search information when you type keywords into Google.

The sequence of web pages corresponding to the series of web pages in the search information is sorted based on the PageRank algorithm.

The importance of this algorithm is evident.

The Page Rank algorithm is not only used in the search engine field.

It has also crossed over into the field of natural language processing (NLP).

The famous TextRank algorithm in NLP is based on the PageRank algorithm.

The TextRank algorithm has always been the core algorithm of the extractive summary algorithm.

Although the TextRank algorithm is currently mainly used in natural language processing.

But it does not mean that this algorithm cannot be applied to search.

After all, the TextRank algorithm and the PageRank algorithm used for search originate from the same root.

Lin Hui’s Generative Text Summarization Algorithm (GTSA) appears to be a text processing algorithm.

But in fact, it also has the potential to be used in the future search field.

Compared with the PageRank algorithm, it ranks web page hyperlinks.

With the GTSA algorithm, Google can go further and directly crawl the top-ranked web page content under the PageRank algorithm to obtain corresponding information.

Perform a second precise sorting according to the criticality of the information and search keywords.

This can undoubtedly greatly improve the accuracy of Google/Google searches.

Although it is difficult to ensure high search efficiency by embedding the generative text summarization algorithm under the PageRank algorithm with current technology.

But who can guarantee that future servers and computing power levels will not advance by leaps and bounds?

What if technology can skyrocket in the future?

And even if Google cannot use this technology in the search field in a short period of time.

The powerful word processing capabilities demonstrated by the generative text summarization algorithm are also technologies worthy of Google's attention.

Anyway, judging from the wording of the task issued by Google.

Google not only pays attention to generative text summarization algorithms.

And eager to acquire the technology.