Not a Good News For Me

How was you weekend guys? It is almost over in Europe now. I guess I am having a great one at the same time a bad one...but not really bad at all..I'm still kicking right now! so what's really the bad news? I just found it out now. This is not really a good news for me. My PR in this blog went down to 2 again from 3. I don't exactly know how many time Big G is updating PR or the so-called pagerank. I remember one year ago, this blog of mine had a PR of 4. Sometimes I am confuse of what are really the basis for PR...any idea out there? I am not an expert..I am just an ordinary blogger who loves to share anything in my blogsites. I hope I can have a better PR next time..but I am still thankful of what I have right now...

Blog-stats Update for My WWW Site

It seems that this blog of mine is getting better. I just check it's Google pagerank at prchecker.info and found out that from PR2, it is getting a PR3 now..Wow I am very happy. One year ago this blog have PR4. I guess that PR4 ran until September. I am just happy that it is one level higher now. Blogging is getting more exciting for me!

here are some blog-stats for this blog.

Google PR: 3 out of 10
Alexa: 316,733
Technorati : 72 and 93..old and new URL
Blogcatalog: 64.8 out of 100

some more blog stats according to pagerank.net
yahoo backlinks: 11,759
Google backlinks: 178
Google Index page: 369
Yahoo Index Page: 819
Alexa backlinks: 242

I guess these are so far the important statistics for this blog as of now. It seems that the stats in my side bar are still not updated until now. Hopefully tomorrow. happy weekend in advance!

Blog-Stats and Pagerank

I guess the most powerful site on the net has updated again Page ranking. You might probably know whom I am talking about here. It is no other than Google which I simply called Big G. I was surprised that my other site entitled Blog Connections got a PR2....hmmmm just confused how PR is really computed by Google. I already read about it before but it seems a little complicated for me. without further adieu here is some statistics of this site...

PR: 2 out of 10 (this was pr4 back in April 2008)
Alexa: 264,647
Technorati: 109
YBL: 11,417 (according to pagerank)
GBL: 146
Blogcatalog: 57.7 out of 100

I guess these are the most important statistics that I can share to you. I just do it once in a while to know how the standing or performance of this site.

Blog stats update!!

This is really sad but my PR went down from 4 to 3!! hello what's up!!! anybody there who can tell me why such thing happen??? I don't know too...hope to find out next time!! I'm just so busy the past days..not only doing household chores but also doing my escapades especially from yesterday!!! will tell you about it later!! and of course, I am really always busy updating my blogs..trying my best!! just don't have more time for blog hopping..hope to do it next time when time permits..sorry dear blogger friends!!

let me proceed first with my blog stats update...here we go;...

PR 3; YBL; 9869; GIP 565; GBL 147; MIP 58; Alexa 533,221; techorati authority 321;
blog cat. 61..

I will try to always monitor my blog stats (if I have time of course) simply because I want to know the standing of my blogs...but I am just really sad that my PR went down.. To all expert bloggers out there esp. blogger friends, any infos or ideas are great appreciated...hope you end your weekend with a very memorable one!!! Happy weekdays in advance!!

You can never find out the true PageRank

How can you discover a page’s PageRank? You can use the Google toolbar. (I explain in a moment why you can never find out the true PageRank.) You should install the Google toolbar, which is available for download at toolbar.google.com. Each time you open a page in Internet Explorer 5.0 or later, you see the page’s PageRank in a bar. If the bar is all white, the PageRank is 0. If it’s all green, the PageRank is 10.

You can estimate PageRank simply by looking at the position of the green bar, or you can mouse over the bar, and a pop-up appears with the PageRank number. If the PageRank component isn’t on your toolbar, click the Options button to open the Toolbar Options dialog box, select the PageRank checkbox, and click OK.

If you don’t have the Google toolbar, you can still check PageRank. Search for the term pagerank tool to find various sites that allow you to enter a URL and get the PageRank. Mozilla’s FireFox browser also has extensions that display the page rank in the status bar of every page.

Here are a few things to understand about this toolbar:

Sometimes the bar is gray. Sometimes when you look at the bar, it’s grayed out. Some people believe that this means Google is somehow penalizing the site by withholding PageRank. I’ve never seen this happen, though. I believe the bar is simply buggy, and that PageRank is just not being passed to the bar for some reason.

Every time I’ve seen the bar grayed out, I’ve been able to open the Web page in another browser window (you may have to try two or three) and view the PageRank.

Sometimes the toolbar guesses. Sometimes the toolbar guesses a PageRank. You may occasionally find it being reported for a page that isn’t even in the Google index. It seems that Google may be coming up with a PageRank for a page on the fly, based on the PageRank of other pages in the site that have already been indexed.

Also, note that Google has various data centers around the world, and because they’re not all in sync, with data varying among them, it’s possible for one person looking at a page’s PageRank to see one number, while someone else sees another number.

A white bar is not a penalty. Another common PageRank myth is that Google penalizes pages by giving them PageRanks of 0.

That is, if you see a page with a PageRank of 0, something is wrong with the page, and if you link to the page, your Web page may be penalized, too. This is simply not true. Most of the world’s Web pages show a PageRank of 0. That’s not to say that Google won’t take away PageRank if it wants to penalize a page or site for some reason. I’m just saying you can’t know if it’s a penalty or if it’s simply a page with few valuable links pointing in.

Zero is not zero, and ten is not ten. Although commonly referred to as PageRank, and even labeled as such, the number you see in the Google toolbar is not the page’s actual PageRank. It’s simply a number indicating the approximate position of the page on the PageRank range. Therefore, pages never have a PageRank of 0, even though most pages show 0 on the toolbar, and a page with a rank of, say, 2 might actually have a PageRank of 25 or 100.

The true PageRank scale is probably a logarithmic scale. Thus, the distance between PageRank 5 and 6 is much greater than the difference between 2 and 3. The consensus of opinion among people who like to discuss these things is that the PageRank shown on the toolbar is probably on a logarithmic scale with a base of around 5 or 6, or perhaps even lower.

Suppose, for a moment, that the base is actually 5. That means that a page with a PageRank of 0 shown on the toolbar may have an actual PageRank somewhere between a fraction of 1 and just under 5. If the PageRank shown is 1, the page may have a rank between 5 and just under 25; if 2 is shown, the number may be between 25 and just under 125, and so on. A page with a rank of 9 or 10 shown on the toolbar most likely has a true PageRank in the millions.

The maximum possible PageRank, and thus this scale, continually changes as Google recalculates PageRank. As pages are added to the index, the PageRank has to go up. How can you be sure that the numbers on the toolbar are not the true PageRank? The PageRank algorithm simply doesn’t work on a scale of 1 to 10 on a Web that contains billions of Web pages. And, perhaps more practically, it’s not logical to assume that sites such as Yahoo! and Google have PageRanks just slightly above small, privately owned sites.

I have pages with ranks of 6 or 7, for instance, whereas the BBC Web site, the world’s 25th most popular Web site according to Alexa, has a PageRank of 9. It’s not reasonable to assume that its true PageRank is just 50 percent greater than pages on one of my little sites. Here are two important points to remember about the PageRank shown on the Google toolbar:

• Two pages with the same PageRank shown on the toolbar may actually have very different true PageRanks. One may have a PageRank of a fifth or sixth, or maybe a quarter, of the other.
• It gets progressively harder to push a page to the next PageRank level on the toolbar. Getting a page to 1 or 2 is pretty easy, but to push it to 3 or 4 is much harder (though certainly possible), and to push it to the higher levels is very difficult indeed. To get to 8 or above is rare.

source: http://www.stylishdesign.com/you-can-never-find-out-the-true-pagerank

PageRank

History

PageRank was developed at Stanford University by Larry Page (hence the name Page-Rank^[3]) and later Sergey Brin as part of a research project about a new kind of search engine. The project started in 1995 and led to a functional prototype, named Google, in 1998. Shortly after, Page and Brin founded Google Inc., the company behind the Google search engine. While just one of many factors which determine the ranking of Google search results, PageRank continues to provide the basis for all of Google's web search tools.^[1]

PageRank is based on citation analysis that was developed in the 1950s by Eugene Garfield at the University of Pennsylvania. Google's founders cite Garfield's work in their original paper. In this way virtual communities of webpages are found. Teoma's search technology uses a communities approach in its ranking algorithm. NEC Research Institute has worked on similar technology. Web link analysis was first developed by Jon Kleinberg and his team while working on the CLEVER project at IBM's Almaden Research Center.

Algorithm

PageRank is a probability distribution used to represent the likelihood that a person randomly clicking on links will arrive at any particular page. PageRank can be calculated for any-size collection of documents. It is assumed in several research papers that the distribution is evenly divided between all documents in the collection at the beginning of the computational process. The PageRank computations require several passes, called "iterations", through the collection to adjust approximate PageRank values to more closely reflect the theoretical true value.

A probability is expressed as a numeric value between 0 and 1. A 0.5 probability is commonly expressed as a "50% chance" of something happening. Hence, a PageRank of 0.5 means there is a 50% chance that a person clicking on a random link will be directed to the document with the 0.5 PageRank.

Simplified algorithm

How PageRank Works

Assume a small universe of four web pages: A, B, C and D. The initial approximation of PageRank would be evenly divided between these four documents. Hence, each document would begin with an estimated PageRank of 0.25.

In the original form of PageRank initial values were simply 1. This meant that the sum of all pages was the total number of pages on the web. Later versions of PageRank (see the below formulas) would assume a probability distribution between 0 and 1. Here we're going to simply use a probability distribution hence the initial value of 0.25.

If pages B, C, and D each only link to A, they would each confer 0.25 PageRank to A. All PageRank PR( ) in this simplistic system would thus gather to A because all links would be pointing to A.

But then suppose page B also has a link to page C, and page D has links to all three pages. The value of the link-votes is divided among all the outbound links on a page. Thus, page B gives a vote worth 0.125 to page A and a vote worth 0.125 to page C. Only one third of D's PageRank is counted for A's PageRank (approximately 0.083).

In other words, the PageRank conferred by an outbound link L( ) is equal to the document's own PageRank score divided by the normalized number of outbound links (it is assumed that links to specific URLs only count once per document).

In the general case, the PageRank value for any page u can be expressed as:

,

i.e. the PageRank value for a page u is dependent on the PageRank values for each page v out of the set B_u (this set contains all pages linking to page u), divided by the number L(v) of links from page v.

Damping factor

The PageRank theory holds that even an imaginary surfer who is randomly clicking on links will eventually stop clicking. The probability, at any step, that the person will continue is a damping factor d. Various studies have tested different damping factors, but it is generally assumed that the damping factor will be set around 0.85.^[4]

The damping factor is subtracted from 1 (and in some variations of the algorithm, the result is divided by the number of documents in the collection) and this term is then added to the product of the damping factor and the sum of the incoming PageRank scores.

That is,

or (N = the number of documents in collection)

So any page's PageRank is derived in large part from the PageRanks of other pages. The damping factor adjusts the derived value downward. The second formula above supports the original statement in Page and Brin's paper that "the sum of all PageRanks is one".^[2] Unfortunately, however, Page and Brin gave the first formula, which has led to some confusion.

Google recalculates PageRank scores each time it crawls the Web and rebuilds its index. As Google increases the number of documents in its collection, the initial approximation of PageRank decreases for all documents.

The formula uses a model of a random surfer who gets bored after several clicks and switches to a random page. The PageRank value of a page reflects the chance that the random surfer will land on that page by clicking on a link. It can be understood as a Markov chain in which the states are pages, and the transitions are all equally probable and are the links between pages.

If a page has no links to other pages, it becomes a sink and therefore terminates the random surfing process. However, the solution is quite simple. If the random surfer arrives at a sink page, it picks another URL at random and continues surfing again.

When calculating PageRank, pages with no outbound links are assumed to link out to all other pages in the collection. Their PageRank scores are therefore divided evenly among all other pages. In other words, to be fair with pages that are not sinks, these random transitions are added to all nodes in the Web, with a residual probability of usually d = 0.85, estimated from the frequency that an average surfer uses his or her browser's bookmark feature.

So, the equation is as follows:

where p₁,p₂,...,p_N are the pages under consideration, M(p_i) is the set of pages that link to p_i, L(p_j) is the number of outbound links on page p_j, and N is the total number of pages.

The PageRank values are the entries of the dominant eigenvector of the modified adjacency matrix. This makes PageRank a particularly elegant metric: the eigenvector is

where R is the solution of the equation

where the adjacency function is 0 if page p_j does not link to p_i, and normalised such that, for each j

i.e. the elements of each column sum up to 1.

This is a variant of the eigenvector centrality measure used commonly in network analysis.

The values of the PageRank eigenvector are fast to approximate (only a few iterations are needed) and in practice it gives good results.

As a result of Markov theory, it can be shown that the PageRank of a page is the probability of being at that page after lots of clicks. This happens to equal t ^{− 1} where t is the expectation of the number of clicks (or random jumps) required to get from the page back to itself.

The main disadvantage is that it favors older pages, because a new page, even a very good one, will not have many links unless it is part of an existing site (a site being a densely connected set of pages, such as Wikipedia). The Google Directory (itself a derivative of the Open Directory Project) allows users to see results sorted by PageRank within categories. The Google Directory is the only service offered by Google where PageRank directly determines display order. In Google's other search services (such as its primary Web search) PageRank is used to weight the relevance scores of pages shown in search results.

Several strategies have been proposed to accelerate the computation of PageRank.^[5]

Various strategies to manipulate PageRank have been employed in concerted efforts to improve search results rankings and monetize advertising links. These strategies have severely impacted the reliability of the PageRank concept, which seeks to determine which documents are actually highly valued by the Web community.

Google is known to actively penalize link farms and other schemes designed to artificially inflate PageRank. In December 2007 Google started actively penalizing sites selling paid text links. How Google identifies link farms and other PageRank manipulation tools are among Google's trade secrets.

source: Wikipedia.http://en.wikipedia.org/wiki/PageRank