I think the author's perspective is skewed in order to stay in line with the title. Here's an example of why I say that:
The author states that "For some 90% of searches, a modern search engine analyzes and learns from past queries, rather than searching the Web itself, to deliver the most relevant results." This may be true in some types of searches but overall, I think the statement is misleading.
Rather, it's better to think of it like this:
One important part of the algorithmic process involves constantly crawling the web and updating the index with new information. (Important / frequently-updated web sites may get crawled all day every day, while ones that are less important may get crawled only weekly or monthly). Meanwhile, another part of the algorithmic process constantly analyzes new info discovered in the crawl and combines it with, as the author-mentioned, click-through data learned from past queries.
The answers to many queries don't change, while the answers to many other queries deserve freshness. For example, I'm quite certain Einstein's date of birth hasn't changed in quite a while, but his theory of relativity is in constant discussion and there is always new information and new queries pertaining to it. As a result, there is not much need for a search engine to go digging for the latest info on an "einstein's birthday" query, but it's to everyone's advantage that Google is able to identify which pages on the web deserve priority crawling and that Google has retrieved and incorporated the fresh info those pages contain into its index when it comes to a topical type of query like "diffraction of light with quantum physics".
In the end, the results to every query depend on info gathered from the web and user data helps refine the results. Info that is more static can be prioritized with more input from click-through data, while new information found on the web must rely more on Google's artificial intelligence to push it up in front of searchers.
Another reason that that "90%" statement sticks out to me is that there is a fairly often-used factoid tossed around industry experts that between "6% to 20% of queries that get asked every day have never been asked before." Google can't rely heavily on past query data for all of these type of searches.
The author states that "For some 90% of searches, a modern search engine analyzes and learns from past queries, rather than searching the Web itself, to deliver the most relevant results." This may be true in some types of searches but overall, I think the statement is misleading.
Rather, it's better to think of it like this: One important part of the algorithmic process involves constantly crawling the web and updating the index with new information. (Important / frequently-updated web sites may get crawled all day every day, while ones that are less important may get crawled only weekly or monthly). Meanwhile, another part of the algorithmic process constantly analyzes new info discovered in the crawl and combines it with, as the author-mentioned, click-through data learned from past queries.
The answers to many queries don't change, while the answers to many other queries deserve freshness. For example, I'm quite certain Einstein's date of birth hasn't changed in quite a while, but his theory of relativity is in constant discussion and there is always new information and new queries pertaining to it. As a result, there is not much need for a search engine to go digging for the latest info on an "einstein's birthday" query, but it's to everyone's advantage that Google is able to identify which pages on the web deserve priority crawling and that Google has retrieved and incorporated the fresh info those pages contain into its index when it comes to a topical type of query like "diffraction of light with quantum physics".
In the end, the results to every query depend on info gathered from the web and user data helps refine the results. Info that is more static can be prioritized with more input from click-through data, while new information found on the web must rely more on Google's artificial intelligence to push it up in front of searchers.
Another reason that that "90%" statement sticks out to me is that there is a fairly often-used factoid tossed around industry experts that between "6% to 20% of queries that get asked every day have never been asked before." Google can't rely heavily on past query data for all of these type of searches.