Catching Up: NYT on Google Algorithm

This is a catch-up post that I’m writing and publishing mainly for my own future reference. It’s about the New York Times article that ran last Sunday, Google Keeps Tweaking Its Search Engine, which was the hot topic at SMX. Due to my crazy schedule all week, I only got around to reading it today. If you’ve read it and digested all of the other blog/forum discussion about the article, feel free to move along; there’s nothing for you here. 🙂

Takeaways from the article:

• “…the search-quality team makes about a half-dozen major and minor changes a week to the vast nest of mathematical formulas that power the search engine”
• Google employees can use the “Buganizer” to report a search-related problem; “about 100 times a day they do”
• “Recently, a search for ‘French Revolution’ returned too many sites about the recent French presidential election campaign — in which candidates opined on various policy revolutions — rather than the ouster of King Louis XVI. A search-engine tweak gave more weight to pages with phrases like ‘French Revolution’ rather than pages that simply had both words.”
• Google has a problem called “Debug” that “shows how its computers evaluate each query and each Web page”
• fixing a poor-quality local search: “…Google’s formulas were not giving enough importance to links from other sites about Palo Alto.”
• QDF = “query deserves freshness” — a solution to not seeing enough new content for certain queries; “THE QDF solution revolves around determining whether a topic is ‘hot.’ If news sites or blog posts are actively writing about a topic, the model figures that it is one for which users are more likely to want current information. The model also examines Google’s own stream of billions of search queries, which Mr. Singhal believes is an even better monitor of global enthusiasm about a particular subject.
• Google “makes a copy of the entire Internet — every word on every page — that it stores in each of its huge customized data centers so it can comb through the information faster.”
• Google’s ranking system “involves more than 200 types of information, or what Google calls ‘signals.’ PageRank is but one signal. Some signals are on Web pages — like words, links, images and so on. Some are drawn from the history of how pages have changed over time. Some signals are data patterns uncovered in the trillions of searches that Google has handled over the years.”
• Queries are processed through “classifiers” which determine the type of search. “Classifiers can tell, for example, whether someone is searching for a product to buy, or for information about a place, a company or a person.”
• Just as spellcheck can fix query typos, Google’s system can recognize abbreviations and synonyms to produce results.

This article generated a lot of discussion, but none of it was more off-target than what Robert Gorell wrote on GrokDotCom: “…aren’t most SEO firms just selling Search Engine Optimism?” Bill Slawski, Stoney deGeyter, and others do a fine job responding to that poorly-worded question (hint: the word “most” is the problem) so I’m leaving it as is. Some of the other useful discussion of the article includes:

• Search Engine Roundtable (with links to several forum discussions)
• Google Blogoscoped
• SEOmoz
• Google’s own Matt Cutts