A Monday morning rant

I love Google as much as the next guy or maybe more than most… Not only the search engine and many apps and services I play with, but I also enjoy how the engineers think (Patent hound here ya know)… but the whole link FUD has finally started to irk me.

I have yet to write about the ‘nofollow’ fiasco… today it changes.

Are we simply a gutless bunch of weenies under the spell of the mighty G? Methinks it’s true.

Matt McGee is a guy I enjoy reading and have respected for some time … and still do. BUT this morning I noticed a post of his that was thanking some advertisers and highlighting some of there posts. He not only nofollowed the links to some of their recent posts, but felt he had to state that they were nofollowed. Good lord, is this what we’ve come to?

Eat my shorts

Because it's about time 

When in comes to doing SEO for Google, one thing is certain; you’d better know about backlinks. Given the fact that the core algorithm is based largely on ranking and detecting spam via links, it is certainly an area to be familiar with.

A while ago there was a re-release of a Google patent on temporal ranking factors which really was a watershed back in 2005 when it first came out, as were subsequent related patents. Analyzing the recent (re-released) publication for new anomalies gave life to the thought that it would be interesting to highlight a few areas as a bit of a refresher course.

For this post I am merely going to address the implications of temporal factors on link building programs.

The basics of historical factors

Just because a web page is 10 years old, doesn’t mean it is still relevant. It also doesn’t ensure that it is. In some situations fresh content can be more relevant than older content. The discovery data can be used to re-rank a document in a positive or negative manner…

Search engines, (such as Google) can use temporal data to analyze link profiles for anomalies based on discovery, (inception) dates;

“…it may be assumed that a document with a fairly recent inception date will not have a significant number of links from other documents”

And can be used for Spam detection;

“While a spiky rate of growth in the number of back links may be a factor used by search engine to score documents, it may also signal an attempt to spam search engine. Accordingly, in this situation, search engine may actually lower the score of a document(s) to reduce the effect of spamming.”

Thus inception dates and historical data can be used for link velocity analysis.

Microsoft’s take on user behavioural data

A search related patent released by Microsoft the other day touches on a popular theme of late, (with me at least); user behaviour analysis. In simplest terms, they look at various interactions with the search results (SERPs) and listing pages, to try and determine the relevance of a set of results. This has been a common theme among the Big 3 as noted by these recent posts;

Google confirms using query analysis – use of past queries in the regular index
Google on User Performance Metrics – trio of patents on the subject
Yahoo Personalized PageRank – user behaviour and PageRank
Yahoo on Personalized Networks – user annotations used to populate networks

..you get the idea...

While concepts utilizing user behaviour relating to AdServing have been around for while, there is increasing interest in ways to harness it within the main SERPs. That is beyond mere personal search implications – though they work best there.

The Microsoft approach

The patent; Search system using user behaviour data - Filed; December 2003 – Published; April 22 2008 

Another chat with Bill Slawski

Where is the future of Search headed? Will algorithmic, link based, search engines continue to rule the roost? Or will the Web 2.0 world produce a social search engine that takes the world by storm? What about a mix of both?

These are some of the questions that have been bantered about with a few of my friends in the SEO and SMM worlds over the last few months. As you might imagine, the views are as varied as the individuals I talk to. Many of my mates in the social media marketing world tend to believe that people are the answer to search relevance and the death of spam. I personally can’t see a straight social search approach ultimately providing the most relevant results. Granted it is hard to say as there have been no widely-accepted/used social search engines and the premise requires a larger data set than we can see so far. So for me the jury is still out.

For me, search engines are always taking in implied or passive data, which in many ways is a form of social search engineering (behavioural targeting at very least).

Talking to the experts

I don’t really do a lot of interviews here, but I do enjoy bringing conversations public and over the next few weeks shall be asking a few friends to talk about this with me here on the Trail. First up; technical search geek and fellow algo-holic – Bill Slawski (we last chatted here)