Internet SEO Consultant, SEM Strategy By Google Certified Professional

Wednesday, 18 April 2012

What is Microblogging ????? asked by Shubhi

Microblogging is a broadcast medium in the form of blogging. A microblog differs from a traditional blog in that its content is typically smaller in both actual and aggregate file size. Microblogs "allow users to exchange small elements of content such as short sentences, individual images, or video links"

During the past few months, I’ve been observing some changes in the blogging behaviors of many of my friends. I’ve been referring to their behavior as microblogging. I thought I was onto something new but a quick Live search reveals that the term has been floating around for awhile (just when I thought I had invented a new term!). I couldn’t find anything that actually defined it, though, so I figured I’d give my notion of what it means, what I’ve been observing, and why it’s important.

What is it?

Microblogging is just what it sounds – it’s regularly publishing small pieces of content on the web. The best example of microblogging is Twitter (from the same guys that brought you old school pre-Google-acquisition Blogger and Odeo). Twitter is a nifty new service that allows you to create a microblog of small pieces of text that you can update from your mobile, IM, or via the Twitter site (for an example, here’s my Twitter).

However, I don’t believe that Twitter is the first (or only) form of microblogging. I’ve been observing this trend of micro-microcontent (many people think regular blogging is microcontent) in various forms – del.icio.us (when posting a small note along with a bookmark), flickr (when posting a bit of text along with a photo), Facebook status, and even adding a review on Yelp could be considered microblogging.

About Goals and Funnels

Google Analytics uses the concept of goals and goal funnels to help you evaluate how well your site serves the ends you have in mind. For example, if you have an ecommerce site, you might set a goal to see what percentage of monthly visitors complete transactions, and then set up an accompanying goal funnel for the expected series of pages leading up to the transaction. If you have a publishing site, you might set a Visit Duration goal to see which percentage of visitors spend more than 3 minutes on the site. Or you might set up a Pages/Visit goal to see which percentage of visitors view a minimum number of pages in a single visit.

When a user completes a goal targeted toward a specific objective, that is called a conversion. You can specify a sequence of pages you expect the visitor to see en route to the goal and designate that sequence as a goal funnel.

The rest of this article describes:

Goals
Goal Funnels
Next Steps

Goals

Analytics offers four kinds of goals for different types of conversions:

URL Destination
The conversion occurs because a specific page (or virtual page) is viewed by the visitor. For example, if you have a lead-generation website that presents a page that thanks the user for sending contact requests, you could set the URL to/sales/thankyouforcontactingus.html.
Visit Duration
The conversion occurs after a specific period of time has elapsed for the visit. For example, you could use this type of goal to determine how many visitors stay longer than two minutes on your newly redesigned shopping page.
Pages/Visit
The conversion occurs after a defined number of pages have been viewed for the visit. You could use this type of goal when you anticipate visitors to view a set of 3 pages minimum, for example.
Event
The conversion occurs because an action has been triggered on an event. In order to set this kind of goal, you must first set up event tracking on your site with at least one named Event category. For information on event tracking, see Event Tracking on Google Code.

In addition to the Goals Reports, you can also view goal information in the following Analytics reports:

Visitor Reports
Traffiic Reports
Site Search Reports
Events Reports

Goal Sets—20 Goals Total

Goals are automatically grouped in sets, starting with Set 1. Use sets to categorize the different types of goals for your site. For example, you might track downloads, registrations, and receipt pages in separate goal sets. For each set of active goals, the Explorer tab above the score card shows the set number.

You can create up to four sets of goals per profile, each with a maximum of 5 goals for a total of 20 goals. To track more than 20 goals for a website, create an additional profile for that site.

Goal Values

The Goal Value metric is the total revenue realized from the goal conversions. The data for Goal Value is first obtained in the goal configuration itself: either by a manually assigned value that you enter, by ecommerce revenue, or by a combination of the two. The calculation of Goal Value in the reports is obtained by multiplying the number of conversions on the goal by the numeric data available for that goal. For example, if you have 3 visitors who each spent $20 on your site in the past month, and you configure a "Sales Goal" for transactions, the Goal Value metric is $60. Google Analytics also uses the Goal Value data to calculate other metrics like ROI and Average Score.

For non-ecommerce goals, a good way to manually configure goal value is to evaluate how often the visitors who reach the goal become customers. For example, if your sales team can close 10% of people who request to be contacted, and your average transaction is $500, you might assign $50 (i.e. 10% of $500) to your "Contact Me" goal. In contrast, if only 1% of mailing list signups result in a sale, you might only assign $5 to your "email sign-up" goal.

Goal Funnels

A goal funnel allows you to track a goal along with a series of pages you expect the visitor to see en route to the goal. A goal funnel is used only in conjunction with a URL Destination goal. Because Google Analytics tracks where visitors enter and leave the goal funnel (and at which rate), you can get valuable insight about visitor drop-off rates in expected activity paths. You can view funnel activity in the Funnel Visualization report.

To illustrate how goal funnels work, suppose you want to define a URL goal for an ecommerce purchase. You can also create a funnel to track activity across the whole purchase process. Here, the goal funnel -- or series of pages -- might look like this:

Page one of the checkout process
Shipping-address page
Credit-card information page
Order confirmation page

The last page in the sequence is your goal page (entered as Goal URL), while the preceding pages make up the goal funnel.

For lead-generation goal funnels, you could assign the first page of the funnel as the URL of the contact request form and the goal page as the URL for the "Thanks for your request" page that appears after the user submits a contact request.

Next Steps

Now that you understand what goals and goal funnels are and how you might use them, read these articles for set up and configuration details:

Setting Up Goals
Goals for URLs and Ecommerce
Special-case Goals and Funnels

Once you have set up goals with values and/or ecommerce tracking, you may wish to exploreMulti-Channel Funnels.

Goals for URLs and Ecommerce

The URL Destination goal is a type of goal you use for determining visitor activity to a specific page on your site. You can also use this type of goal to determine visitor activity to key ecommerce pages (such as a shopping cart receipt page). Since you might also expect visitors to view an additional series of pages before reaching the goal page, you can also define a funnel for URL Destination goals.

This article covers the following:

Standard Goals for Fixed URLs
Ecommerce Transaction Page Goals
Dynamically generated or Variable URLs
Identical URLs Across Multiple Steps
Goals for Multiple Criteria
Funnels
Match Types: Head Match, Exact Match & Regular Expression Match
Verifying Correct URL Expressions for Goals

Standard Goals for Fixed URLs

Many websites use fixed URLs for a given webpage. The structure of these pages depends on the web technology used for the site. For example:

http://www.myownpersonaldomain.com/2008/category/name-of-blog-post/

http://www.examplepetstore.com/dogs/food.php

http://www.examplepetstore.com/cats/food.html

To configure goals for these types of URLs:

First verify that the URL for the goal is both unique to that page/goal, and consistent from view to view.

If the URL is the same across multiple steps in the goal process, see Identical URLs Across Multiple Steps (below). If the URL changes from view to view, or if it has name/value parameters, see the instructions for dynamically-generated URLs.

URL: Enter the request URI part of the goal.

The request URI is that part of the URL that comes after the domain address. Using the URL examples listed above, you would enter:

/2008/category/name-of-blog-post/

/dogs/food.php

/cats/food.html

Case Sensitive: Check this box only in the situation where you want to match only one of two identical URLs which differ only by case (e.g. /contactus.html and /CONTACTUS.html).

Match Type: Use the match type that works best for your purpose. In most situations, the default head match works well. See Match Types below for more details.

Many websites use fixed URLs for a given webpage. The structure of these pages depends on the web technology used for the site. For example:

http://www.myownpersonaldomain.com/2008/category/name-of-blog-post/

http://www.examplepetstore.com/dogs/food.php

http://www.examplepetstore.com/cats/food.html

To configure goals for these types of URLs:

First verify that the URL for the goal is both unique to that page/goal, and consistent from view to view.

URL: Enter the request URI part of the goal.

The request URI is that part of the URL that comes after the domain address. Using the URL examples listed above, you would enter:

/2008/category/name-of-blog-post/

/dogs/food.php

/cats/food.html

Case Sensitive: Check this box only in the situation where you want to match only one of two identical URLs which differ only by case (e.g. /contactus.html and /CONTACTUS.html).

Match Type: Use the match type that works best for your purpose. In most situations, the default head match works well. See Match Types below for more details.

Goal Value: If you have an imputed value for your page, enter that value in this field. For info on goal values, see About Goals and Funnels.: If you have an imputed value for your page, enter that value in this field. For info on goal values, see About Goals and Funnels.

Ecommerce Transaction Page Goals

Defining goals for ecommerce transaction pages involves coordination with ecommerce tracking setup in your tracking code. While you manually set a URL goal for your shopping cart page, the value of the goal should be retrieved from the actual ecommerce value, not entered manually as you might with other types of goals. In this way, ROI and $Index values for that goal will be calculated from actual site revenue value. In order for this to occur, you must first configure ecommerce tracking for your website. For details on setting up ecommerce tracking for your website, see the Ecommerce Guide.
Once you have defined ecommerce tracking and can verify that the transaction data is being sent to Analytics, configure a URL Ecommerce goal as follows:

For URL: Supply the URL for your shopping cart. For example:http://www.we-sell-for-you.com/mysite/myCart.asp
Match Type: Typically, Head Match is the best choice for shopping pages, since shopping cart URLs often append a number of parameters to the end of the URL to pass data to the ecommerce server. You can test your shopping cart to determine the structure of the URL and set the match accordingly. See Match Types below for more details.
Goal Value: Leave goal value set to 0 in order to ensure that the value for the goal is retrieved from the ecommerce transaction value for the page. If you manually add a value in this field and ecommerce is also configured for the goal page, then every time this goal is converted, the goal value will be the sum of the value entered in this field plus the value of the transaction.

Dynamically generated or Variable URLs

If your URLs include query terms or have parameters at the end, use either Head Match or Regular Expression Match types when entering funnel or conversion goal URLs. Examples of dynamic or variable URLs are:

http://www.example.com/about/pageWithParameter.html?id=89
http://www.example.com/sales/JanuaryOffer.html?utm_source=NewsLetterJan&utm_medium=email
http://sports.example.com/checkout.cgi?page=1&id=002

See Match Types below for more details.

Identical URLs Across Multiple Steps

In some situations, the URL does not change across a sequence of activity. For example, a sign-up process might have the following URL path:

Step 1 (Sign Up): www.example.com/sign_up.cgi
Step 2 (Accept Agreement): www.example.com/sign_up.cgi
Step 3 (Finish): www.example.com/sign_up.cgi

To track visitors' progress through a funnel with the same URL for each step, modify the tracking code to create a virtual URL for each step in the sequence that you want to track. For details on how to use this in your tracking code, seeVirtual Pageviews in the Asynchronous Migration Examples guide, which shows how to do this in all versions of the tracking code. The following example shows how you might fabricate 3 URLs using the asynchronous tracking code:

_gaq.push(['_trackPageview', '/funnel_G1/step1.html']);
_gaq.push(['_trackPageview', '/funnel_G1/step2.html']);
_gaq.push(['_trackPageview', '/funnel_G1/step3.html']);

You would then define your funnel and goal URLs using the ones you created in the tracking code modifications.

Goals for Multiple Criteria

You can define a goal for multiple criteria, such as a visit to two specific sections of your website, or a visit to any page within a sub-directory of your website. To do this, you will use regular expression as your match type. See Match Typesbelow for more details. The following examples illustrate these scenarios:

use ^/sports/.* to match a goal when any page within the sports directory is viewed
use sports.html|music.html to match a goal when a user views wither the sports.htm or music.htm pages

Funnels

When you create a URL Destination goal, you also have the option to create funnel for that goal. A funnel is a sequence of pages that you anticipate visitors seeing before they reach the goal. Report data for the funnel appears in the Funnel Visualizations report. See About Goals for more overview information.

Before creating a funnel, keep in mind the following:

Test the sequence on your website, and make a note of all pages that make up the entire sequence of activities you want to track for the goal.
The final page of the sequence is the actual goal and its URL be entered in the Goal URL field, not the funnel section.
The match type you select for the Goal URL also applies to any URL in the Funnels section.
Omit the domain name of the URL in each funnel step (e.g.http://www.example.com/aboutUs.html is entered as/aboutUs.html)
If you make the first step of the funnel mandatory, the conversion count for the Funnel Visualization report will include only those visitors who reached the goal via that first step. Otherwise, the conversion count for the goal will be the same in all reports.

To define a funnel:

Open or create a URL Destination as goal.
Select Use funnel and enter the URL for the first page in the funnel for Step 1.
Enter a name for that step that you want to appear in the Funnel reports. For example, you might want to use Welcome as the name forwelcome.html.
To make the first step required, select the Required step checkbox.
For additional funnel steps, click Add Goal Funnel Step, and supply the URL and name for each page.
Note: Remember not to enter the final page of the process in the funnel section, but in the Goal URL field.
When you have finished adding pages, click Save Goal.

To verify that the funnel is working, view the Funnel Visualizations reports to see data there.

Match Types: Head Match, Exact Match & Regular Expression Match

There are three diferent match types that define how Google Analytics identifies a URL for either a goal or a funnel. The match type that you select for your goal URL also applies to the URLs in the funnel, if you create one.

Exact match—for standard, fixed URLs:An exact match is a match on every exact character in your URL—without exception—from beginning to end. Use this when your URLs for your site are easy to read and do not vary.
This option requires that the URLs you provide for your funnel or goalexactly match the URLs shown in the reports. There can be no dynamic (changing) information in the URL such as session identifiers or query parameters.

If you are using an exact match for a goal (e.g./shopping/thanks.html), leading or trailing whitespaces in the goal field will invalidate the goal.
Head Match—to eliminate trailing URL parameters:A head match matches identical characters starting from the beginning of the string up to and including the last character in the string you specify. Use this option when your page URLs are generally unvarying but when they include additional parameters at the end that you want to exclude.
If your website has dynamically generated content, use the Head Match filter and leave out the unique values.
For example, a URL visited by a particular visitor might behttp://www.example.com/checkout.cgi?page=1&id=9982251615. In this case, the id varies for every other user. You could still match this page by using /checkout.cgi?page=1as the URL and selecting Head Match as your Match Type.
Regular Expression Match—for matching on multiple criteria:A regular expression uses special characters to enable wildcard and flexible matching. This is useful when the stem, trailing parameters, or both, can vary in the URLs for the same website page.
For example, if a user could be coming from one of many subdomains, and your URLs use session identifiers, you could use a regular expression to define the constant element of your URL. For example, checkout.cgi\?page=1 will match http://sports.example.com/checkout.cgi?page=1&id=002 as well ashttp://fishing.example.com/checkout.cgi?page=1&language=fr&id=119.
As another example, you could use regular expressions to set a goal for when any page in a subdirectory is visited: ^/sports/.*.

Verifying Correct URL Expressions for Goals

You can verify that you have written a Goal URL correctly by searching for the page in the Pages report using the exact URL or regular expression you want to use in creating your goal. If you are able to successfully view the pages you expect after doing a search, you can safely assume your URL or expression will work.
Examples

Head Match
Suppose your pet store website has a number of pages in a single directory, and you want to use a head match URL to create a goal only for the fish-related pages, which all have the same structure:

/supplies/fishFood.html
/supplies/fishTanks.html
/supplies/fishTankDecorations.html

To determine whether your head match URI works, go to the Pages report for your site, click the Search button and choose "Begins with" as your search type. To match the URLs above, you would enter /supplies/fish in the search field. If your search returns those pages you expect to match, you can use that same URI string as you goal URL.
Regular Expression Match
Because the Pages report allows regular expressions in the search field, it's a great place to verify whether your regular expression will work as a goal. For example, the Analytics documentation on Google Code has a number of pages that have track as part of the file name. For example:

gaTrackingVisitors.html
eventTrackerOverview.html

While many of those files reside in the /tracking directory of the site, some of them don't. In order to set a goal that converts on all visits to pages withtrack as part of their name, a regular expression is required. A search on the Pages reports for this site using the regular expression .*track[^/]*html$verifies that this expression matches all files that contain track and no other files.

Thursday, 5 April 2012

Keyword density Formula

Many SEO experts consider the optimum keyword density to be 1 to 3 percent. Using a keyword more than that could be considered search spam. The formula to calculate your keyword density on a web page for SEO purposes is $(Nkr / Tkn) * 100$ , where Nkr is how many times you repeated a specific keyword and Tkn the total words in the analyzed text. This will result in a keyword density value. When calculating keyword density, be sure to ignore html tags and other embedded tags which will not actually appear in the text of the page once it is published.

When calculating the density of a keyword phrase, the formula would be $(Nkr * Nwp / Tkn) * 100$ , where Nwp is the number of words in the phrase. So, for example, for a page about search engine optimization where that phrase is used four times and there are four hundred words on the page, the keyword phrase density is (4*3/400)*100 or 3 percent.

However, from a purely mathematical viewpoint, one cannot ignore the fact that the original concept of keyword density refers to the frequency (Nkr) of appearance of a particular keyword in a dissertation. Thus, a "keyword" consisting of multiple terms, e.g. "blue suede shoes" should be considered an entity in itself. It is the frequency of the phrase "blue suede shoes" within a dissertation that drives the key(phrase) density. Thus it is "more" mathematically correct for a "keyphrase" to be calculated just like the original calculation, but considering the word group, "blue suede shoes," as a single appearance, not three. Thus:

Density = ( Nkr / Tkn ) * 100.

Furthermore, under closer inspection, one can see that these 'keywords' (kr) that actually consist of several words, artificially inflate the total word count of the dissertation. Therefore, it could be argued that the purest mathematical representation should adjust the total word count (Tkn) lower by removing the excess key(phrase) word counts from the total. Thus:

Density = ( Nkr / ( Tkn -( Nkr * ( Nwp-1 ) ) ) ) * 100. where Nwp = the number of terms in the keyphrase.

This general formula allows that the total word count will be unaffected if the key(phrase) is indeed a single term, so it acts as the original formula.

Page Rank Algorithm

PageRank is a link analysis algorithm, named after Larry Page and used by the Google Internet search engine, that assigns a numerical weighting to each element of a hyperlinked set of documents, such as theWorld Wide Web, with the purpose of "measuring" its relative importance within the set. The algorithm may be applied to any collection of entities with reciprocal quotations and references

Simplified algorithm

Assume a small universe of four web pages: A, B, C and D. Links from a page to itself, or multiple outbound links from one single page to another single page, are ignored. PageRank is initialized to the same value for all pages. In the original form of PageRank, the sum of PageRank over all pages was the total number of pages on the web at that time, so each page in this example would have an initial PageRank of 1. However, later versions of PageRank, and the remainder of this section, assume a probability distribution between 0 and 1. Hence the initial value for each page is 0.25.

The PageRank transferred from a given page to the targets of its outbound links upon the next iteration is divided equally among all outbound links.

If the only links in the system were from pages B, C, and D to A, each link would transfer 0.25 PageRank to A upon the next iteration, for a total of 0.75.

$PR(A)= PR(B) + PR(C) + PR(D).\,$

Suppose instead that page B had a link to pages C and A, while page D had links to all three pages. Thus, upon the next iteration, page B would transfer half of its existing value, or 0.125, to page A and the other half, or 0.125, to page C. Since D had three outbound links, it would transfer one third of its existing value, or approximately 0.083, to A.

$PR(A)= \frac{PR(B)}{2}+ \frac{PR(C)}{1}+ \frac{PR(D)}{3}.\,$

In other words, the PageRank conferred by an outbound link is equal to the document's own PageRank score divided by the number of outbound links L( ).

$PR(A)= \frac{PR(B)}{L(B)}+ \frac{PR(C)}{L(C)}+ \frac{PR(D)}{L(D)}. \,$

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

$PR(u) = \sum_{v \in B_u} \frac{PR(v)}{L(v)}$ ,

i.e. the PageRank value for a page u is dependent on the PageRank values for each page v contained in the set B_u (the set containing all pages linking to page u), divided by the numberL(v) of links from page v.

[edit]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 (N) 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,

$PR(A) = {1 - d \over N} + d \left( \frac{PR(B)}{L(B)}+ \frac{PR(C)}{L(C)}+ \frac{PR(D)}{L(D)}+\,\cdots \right).$

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 original paper, however, gave the following formula, which has led to some confusion:

$PR(A)= 1 - d + d \left( \frac{PR(B)}{L(B)}+ \frac{PR(C)}{L(C)}+ \frac{PR(D)}{L(D)}+\,\cdots \right).$

The difference between them is that the PageRank values in the first formula sum to one, while in the second formula each PageRank is multiplied by N and the sum becomes N. A statement in Page and Brin's paper that "the sum of all PageRanks is one"^] and claims by other Google employees^[14] support the first variant of the formula above.

Page and Brin confused the two formulas in their most popular paper "The Anatomy of a Large-Scale Hypertextual Web Search Engine", where they mistakenly claimed that the latter formula formed a probability distribution over web pages.

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, which are all equally probable, 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. 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 usually set to 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:

$PR(p_i) = \frac{1-d}{N} + d \sum_{p_j \in M(p_i)} \frac{PR (p_j)}{L(p_j)}$

where $p_1, p_2, ..., p_N$ 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

$\mathbf{R} = \begin{bmatrix} PR(p_1) \\ PR(p_2) \\ \vdots \\ PR(p_N) \end{bmatrix}$

where R is the solution of the equation

$\mathbf{R} = \begin{bmatrix} {(1-d)/ N} \\ {(1-d) / N} \\ \vdots \\ {(1-d) / N} \end{bmatrix} + d \begin{bmatrix} \ell(p_1,p_1) & \ell(p_1,p_2) & \cdots & \ell(p_1,p_N) \\ \ell(p_2,p_1) & \ddots & & \vdots \\ \vdots & & \ell(p_i,p_j) & \\ \ell(p_N,p_1) & \cdots & & \ell(p_N,p_N) \end{bmatrix} \mathbf{R}$

where the adjacency function $\ell(p_i,p_j)$ is 0 if page $p_j$ does not link to $p_i$ , and normalized such that, for each j

$\sum_{i = 1}^N \ell(p_i,p_j) = 1$ ,

i.e. the elements of each column sum up to 1, so the matrix is a stochastic matrix (for more details see the computation section below). Thus this is a variant of the eigenvector centralitymeasure used commonly in network analysis.

Because of the large eigengap of the modified adjacency matrix above,the values of the PageRank eigenvector can be approximated to within a high degree of accuracy within only a few iterations.

As a result of Markov theory, it can be shown that the PageRank of a page is the probability of arriving at that page after a large number 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.

One main disadvantage of PageRank is that it favors older pages. 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 fully determines display order.^{[citation needed]} In Google's other search services (such as its primary Web search), PageRank is only used to weight the relevance scores of pages shown in search results.

Several strategies have been proposed to accelerate the computation of PageRank.

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 purports to determine which documents are actually highly valued by the Web community.

Since December 2007, when it started actively penalizing sites selling paid text links, Google has combatted link farms and other schemes designed to artificially inflate PageRank. How Google identifies link farms and other PageRank manipulation tools is among Google's trade secrets.

Graphing on Google.com - Now in 3D

A few months ago we launched a graphing functionality right in search to help students and math lovers plot functions in an easy, simple way. In addition to calculating something simple like dividing up a restaurant bill or graphing more difficult math functions using the search box, people have also been plotting some really unique and interesting functions. You’ll be able to do even more with the graphing calculator, which now supports 3D plotting as well.

Just type any real two variable function into Google to see a dynamic, interactive, three dimensional plot. Click anywhere in the graph to rotate it to check out different angles, or scale the view by zooming in or out, or by editing the range in your equation or in the lower-right legend box. For example, if you’re a student studying advanced calculus, the ability to see a three dimensional graph will help you get a better visualization for real two variable functions.

This feature is enabled by a technology called WebGL, which we’re using for the first time in Google Search. WebGL is a new web technology that brings hardware-accelerated 3D graphics to the browser without the need to install additional software. This technology is currently supported on modern web browsers such as Chrome and Firefox.

This feature is available globally, so now millions of students can explore and interact with compound math functions right in their search results. We can’t wait to see what kind of interestingfunctions you’ll plot!

Major Search Engines Spiders / Crawler

We are sharing major Search Engines Spiders / Crawler

1.Google - Googlebot
2.Yahoo - Yahoo Slurp
3.MSN - MSNbot
4.Ask - Teoma
5.Excite - Architext spider
6.Inktomi.com - Slurp
7.Alexa - ia_archiver
8.Altavista - Scooter
9.Lycus - Lycos_Spider_(T-Rex)
10.Cuil - Twiceler (New Search Engine)
11.Looksmart - MantraAgent

Wednesday, 4 April 2012

How to Promote Our Apps

You've created your app with Caspio and deployed it to your website, but have you considered how to get more out of your efforts? Here are some ways that you can extend the reach of your Caspio apps to gain more exposure and usage:

1. Distribute Your App as a Widget on Blogs and Other Sites

Do you have web forms that could generate more leads if they had more exposure? Do you have information such as product catalogs, upcoming events, or user directories that you want to share on different pages to draw people to your site?

All Caspio forms, reports, charts, and calendars can be deployed on multiple websites, including CMS and blogging software. Our free WordPress PlugIn makes it easier if your site is on WordPress

2. Generate Free Traffic with SEO Data Publishing

Do you have data that you want to distribute as widely as possible? Do you generate revenues from your content, perhaps through advertising or subscriptions?

A key to the success of most websites is to generate free traffic. Caspio’s Search Engine Optimized deployment technology publishes your database in a search-engine friendly format, so Google and Bing can crawl it and bring organic traffic to your site.

3.Give Mobile Users a Better Experience

Caspio-powered apps are already compatible with mobile devices such as iPhone, Android and Blackberry smartphones and iPad and other tablets. However, you can go a step further and give your mobile users a better experience by creating a version of your app optimized for small devices. Caspio’s iPhone Kit is the place to start for creating mobile-friendly apps.

4. Tap into Social Media by Deploying Apps on Facebook

Businesses are realizing the power of Facebook for marketing and customer engagement, and chances are that your users are spending a great deal of time on the site. Caspio apps can be embedded in your Facebook business profile or registered as stand-alone Facebook apps. Think of generating leads, showcasing products, promoting your calendar of events, listing job openings, and soon you will see the sky is the limit on Facebook.

Google News Badges | What is Google Badges

News Badges

The U.S. Edition of Google News now lets you collect private, sharable badges for your favorite topics. The more articles you read on Google News, the more your badges level up: you can reach Bronze, Silver, Gold, Platinum, and finally Ultimate. Keep your badges to yourself, or show them off to your friends.

Earning Badges
If you’re signed-in to a Google account and have web history enabled, you will earn badges as you click on articles in Google News. Both desktop and mobile clicks earn you badges. Tips:

Badges will level up faster if you read a few relevant articles every day, rather than trying to read everything at once.
You can click on a badge to see articles that will help the badge reach its next level.
If you read a few articles a day about your favorite topics, you should earn your first badge in about a week.
At the moment, clicks only count toward News Badges if you have selected "One Column" mode. You can choose this format via the News Settings page, which you can access via the gear icon at the top right of the page.

Sharing Badges
By default, only you can see your badges. You can choose to share a specific badge in your badge collection by mousing over the badge and clicking one of the sharing icons. When you share a badge, it reveals your badge’s name and level, as well as the rough number of articles that you have read about the badge’s topic. Your friends will not see the specific articles that you have read.
Hiding Badges
To hide a specific badge from your collection, hover over the badge and click the trash can. Individual hidden badges cannot be restored, so be careful!
To hide all Google News badges, click the “X” in the top right of “Google News Badges” in the side column, or click “Turn off all news badges” when you’re notified about badges.
To restore Google News Badges, go to your News Settings page (accessible by clicking on the gear icon at the top-right of your screen) and click the checkbox, "Show Google News Badges."

Sunday, 1 April 2012

Google Maps 8-bit for NES

Have you heard about the 8-bit version of Google Maps for NES? Check it out, here

Now you can check offline map with your family ..........................