PageRank
Google’s gunning for web spammers, bans us from mentioning Bieber
Source: http://www.engadget.com/2012/04/26/google-targets-seo-spam/
Google’s changing its search algorithm to punish sites that emphasize search-engine optimization over quality. Mountain View’s data centers will exclude sites that offer no useful content, have articles written in keyword-sprinkled gibberish or only link to sites within a cluster. If the computers find it, the site’s pagerank will be demoted, with the company expecting to affect around three percent of all English language queries when it goes live later this week. The company isn’t providing more details (lest it help those trying to game the system), so just get all of those gratuitous Justin Bieber references out of your system before Friday, okay?
Google’s gunning for web spammers, bans us from mentioning Bieber originally appeared on Engadget on Thu, 26 Apr 2012 04:58:00 EDT. Please see our terms for use of feeds.
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Google Violated Its Own Evil-Free Policies While Promoting Chrome [Google]
Source: http://gizmodo.com/5872566/google-violated-its-own-evil+free-policies-while-promoting-chrome
The first rule of not being evil is: don’t do things you think are evil. So it’s a shame that Google has violated its own policy by giving bloggers cash in exchanges for writing about its browser, Chrome.
Google, or perhaps more likely its advertising firm Unruly, has managed to sponsor bloggers to chew the fat over Chrome, reports SEO Book. Some of them talk about how great Chrome is for small businesses, and most contain a Google promo video.
Meh, that’s kind of fine, right? Mmm, the thing is, paid-for links to the Chrome download page would be just fine according to Google’s rules — as long as they were tagged up as “nofollow” links. That’s supposed to let PageRank know that a link was paid for so as to exclude it from search rankings.
But, uh, some of the links didn’t follow that guideline.
OK, so this isn’t too bad: it isn’t like Google is culling small kittens, granted. And it could in fact be an innocent mistake on the part of the bloggers. But what it more likely indicates is that Google is getting so large that it can’t help but trip over its own policies. And at that point, it becomes difficult to hold an entire organisation up to its existing ethical codes.
So, don’t be evil. At least, if you can remember what you mean by evil. [SEO Book via TechCrunch; Image: brionv]
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Inside Google’s Secret Search Algorithm
Source: http://feeds.gawker.com/~r/gizmodo/full/~3/zzkIcilnJp4/inside-googles-secret-search-algorithm
Wired’s Steven Levy takes us inside the “algorithm that rules the web“—Google’s search algorithm, of course—and if you use Google, it’s kind of a must-read. PageRank? That’s so 1997.
It’s known that Google constantly updates the algorithm, with 550 improvements this year—to deliver smarter results and weed out the crap—but there are a few major updates in its history that have significantly altered Google’s search, distilled in a helpful chart in the Wired piece. For instance, in 2001, they completely rewrote the algorithm; in 2003, they added local connectivity analysis; in 2005, results got personal; and most recently, they’ve added in real-time search for Twitter and blog posts.
The sum of everything Google’s worked on—the quest to understand what you mean, not what you say—can be boiled down to this:
This is the hard-won realization from inside the Google search engine, culled from the data generated by billions of searches: a rock is a rock. It’s also a stone, and it could be a boulder. Spell it “rokc” and it’s still a rock. But put “little” in front of it and it’s the capital of Arkansas. Which is not an ark. Unless Noah is around. “The holy grail of search is to understand what the user wants,” Singhal says. “Then you are not matching words; you are actually trying to match meaning.”
Oh, and by the way, you’re a guinea pig every time you search for something, if you hadn’t guessed as much already. Google engineer Patrick Riley tells Levy, “On most Google queries, you’re actually in multiple control or experimental groups simultaneously.” It lets them constantly experiment on a smaller scale—even if they’re only conducting a particular experiment on .001 percent of queries, that’s a lot of data.
Be sure to check out the whole piece, it’s ridiculously fascinating, and borders on self-knowledge, given how much we all use Google (sorry, Bing). [Wired, Sweet graphic by Wired’s Mauricio Alejo]
Additional Information on Real Time Bidding
Aardvark Publishes A Research Paper Offering Unprecedented Insights Into Social Search
Source: http://feedproxy.google.com/~r/Techcrunch/~3/IMDRrISRf-8/
In 1998, Larry Page and Sergey Brin published a paper[PDF] titled Anatomy of a Large-Scale Hypertextual Search Engine, in which they outlined the core technology behind Google and the theory behind PageRank. Now, twelve years after that paper was published, the team behind social search engine Aardvark has drafted its own research paper that looks at the social side of search. Dubbed Anatomy of a Large-Scale Social Search Engine, the paper has just been accepted to WWW2010, the same conference where the classic Google paper was published.
Aardvark will be posting the paper in its entirety on its official blog at 9 AM PST, and they gave us the chance to take a sneak peek at it. It’s an interesting read to say the least, outlining some of the fundamental principles that could turn Aardvark and other social search engines into powerful complements to Google and its ilk. The paper likens Aardvark to a ‘Village’ search model, where answers come from the people in your social network; Google is part of ‘Library’ search, where the answers lie in already-written texts. The paper is well worth reading in its entirety (and most of it is pretty accessible), but here are some key points:
- On traditional search engines like Google, the ‘long-tail’ of information can be acquired with the use of very thorough crawlers. With Aardvark, a breadth of knowledge is totally reliant on how many knowledgeable users are on the service. This leads Aardvark to conclude that “the strategy for increasing the knowledge base of Aardvark crucially involves creating a good experience for users so that they remain active and are inclined to invite their friends”. This will likely be one of Aardvark’s greatest challenges.
- Beyond asking you about the topics you’re most familiar with, Aardvark will actually look at your past blog posts, existing online profiles, and tweets to identify what topics you know about.
- If you seem to know about a topic and your friends do too, the system assumes you’re more knowledgeable than if you were the only one in a group of friends to know about that topic.
- Aardvark concludes that while the amount of trust users place in information on engines like Google is related to a source website’s authority, the amount they trust a source on Aardvark is based on intimacy, and how they’re connected to the person giving them information
- Some parts of the search process are actually easier for Aardvark’s technology than they are for traditional search engines. On Google, when you type in a query, the engine has to pair you up with exact websites that hold the answer to your query. On Aardvark, it only has to pair you with a person who knows about the topic — it doesn’t have to worry about actually finding the answer, and can be more flexible with how the query is worded.
- As of October 2009, Aardvark had 90,361 users, of whom 55.9% had created content (asked or answered a question). The site’s average query volume was 3,167.2 questions per day, with the median active user asking 3.1 questions per month. Interestingly, mobile users are more active than desktop users. The Aardvark team attributes this to users wanting quick, short answers on their phones without having to dig for anything. They also think people are more used to using more natural language patterns on their phones.
- The average query length was 18.6 words (median of 13) versus 2.2-2.9 words on a standard search engine. Some of this difference comes from the more natural language people use (with words like “a”, “the”, and “if”). It’s also because people tend to add more context to their queries, with the knowledge that it will be read by a human and will likely lead to a better answer.
- 98.1% of questions asked on Aardvark were unique, compared with between 57 and 63% on traditional search engines.
- 87.7% of questions submitted were answered, and nearly 60% of them were answered within 10 minutes. The median answering time was 6 minutes and 37 seconds, with the average question receiving two answers. 70.4% of answers were deemed to be ‘good’, with 14.1% as ‘OK’ and 15.5% were rated as bad.
- 86.7% of Aardvark users had been asked by Aardvark to answer a question, of whom 70% actually looked at the question and 38% could answer. 50% of all members had answered a question (including 75% of all users who had ever actually interacted with the site), though 20% of users accounted for 85% of answers.
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