A journey into Google’s patent on generating suggestions

Search engines are always looking to make our lives easier, or at least accessing the world’s information in a timely manner. But in the old days they had to wait for the user to take action before they could begin to deliver potential results for a query – not these days – starting to gather search results and even implementing search assist can happen with each keystroke.

You know the one, the suggestions they make as you’re typing in a given query? It looks something like this;

I know more than a few SEO peeps have talked about this as a potential problem for some long tail targets and others have pondered if it would make a good keyword research tool. They can also use the same systems for query analysis as far as which documents to return and rank. But what if there is a potential for personalization of this data? Because there just might be; and that would certainly limit its overall effectiveness from a SEO perspective - At least as a research tool.

(Note; the following is a guest post from my good friend Miss CJ)

How search engineers look for nepotistic links

Paid links are a bit of problem for search engine engineers because they can be misleading.  Some links are bought in order to boost rank and others are purchased for legitimate reasons, such as actually offering something interesting to a website visitor.  Not all links should be discounted but different weights can be given to allow less important links to get a full "vote". 

It's not easy to differentiate between these, but there has been a fair bit of research around it we can look at.  If search engines could discount misleading nepotistic links, their performance would improve.  In the SEO community, this would be received with mixed emotions not doubt.  Google uses methods to detect keyword spamming for example, and uses other text based methods, but their algorithm is open to link spam.

But what are search engineers doing to combat nepotistic links in modern information retrieval?

Putting behavioural metrics in perspective

Wise men don't judge: they seek to understand. - (Wei Wu Wei)

So here’s the question; are behavioural metrics being used in modern search? You do remember them right? Those warm and fuzzy little signals such as bounce rates that there all the rage in late 2008 in the search engine optimization world? Sure you do… but let’s take one last look.

Although bounce rates received the biggest attention, we would be remiss not to start by quickly listing some signals commonly looked at by information retrieval folks. The two elements include implicit and explicit data (actions and interactions) – examples can include;

Implicit signals

1. Query history (search history)
2. SERP interaction (revisions, selections and bounce rates)
3. User document behaviour (time on page/site, scrolling behaviour);
4. Surfing habits (frequency and time of day)
5. Interactions with advertising
6. Demographic and geographic
7. Data from different application (application focus – IM, email, reader);
8. and closing a window.

Explicit signals

1. Adding to favourites
2. Voting (a la Search Wiki or toolbar)
3. Printing of page
4. Emailing a page to a friend (from site)

Now that we’re past that let’s get a little geeky so those information retrievers don’t shake their heads to hard at us – the terminology. I am as guilty as the next Gypsy of flinging the term ‘behavioural metrics’ about over the last year or so, even performance metrics. If you want to research this more, start by using the term; implicit/explicit user feedback signals – because that’s what we’re talking about.

and thanks to Steve Gerencser for sending the pic

In case you missed the memo

For the last while covering some web spam detection methods have been on my mind. Regardless if you walk on the dark side, or prance where daisies bloom, knowing how to stay in a search engine’s good graces is always a wise path to chart. To that end, Yahoo put out a patent that deals with link manipulations via reciprocal links. If you didn’t get the memo about recips being dead - at least excessive reciprocal linking - then do come along for the ride. (seems Bill and I have the same Friday night reading as he covered this link spam patent Saturday)

The patent is;

Identifying excessively reciprocal links among web entities – Yahoo – Filed in July 2007 and assigned Jan 8 2009 - Converse; Timothy M.; (Sunnyvale, CA) ; Garg; Priyank Shankar; (San Jose, CA) ; Tsioutsiouliklis; Konstantinos; (San Jose, CA)

Of interest right away is that they mention this being related to;

Link-based spam detection – Yahoo – Filed August 2005 and assigned May 2006 - Barkhin; Pavel; (Sunnyvale, CA) ; Gyongyi; Zoltan Istvan; (Stanford, CA) ; Pedersen; Jan; (Los Altos Hills, CA)

So what? Are reciprocal links now synonymous with spam? Well not entirely, but the folks at Yahoo aren’t thrilled about it. But as you may imagine few in the IR world are thrilled and spend a fair amount of time looking to combat it. Some good reading can be found on the Annual Workshop on Adversarial IR.