Mashed Articles

DNS (Domain Name Server) is basically a system to convert domain names into IP addresses. Domain names are easier to understand, memorize and write for humans while computers only use IP addresses to communicate.

In most of the  case, Internet Service Providers  providing the DNS servers to the customer. User can change it, the  reasons to switch to other DNS servers for performance, privacy and censorship. Most of the people using OpenDNS as the first alternative, But Now Google Public DNS is available and the performance is much better.

Now How to set up Google Public DNS in Ubuntu

Select System–>Preferences–>Network Connections


Select  the type of connection you have. For this example, we will use ‘Wired’.
Under ‘Wired’, highlight ‘Auto etho’ and click on ‘Edit’.

Now,  Inside ‘Editing Auto etho‘ window, click on ‘IPv4 Settings’ tab. and select ‘Automatic (DHCP) address only‘

Put these nameserver addresses as your ‘DNS Servers’:8.8.8.8, 8.8.4.4

Click ‘OK’ and reboot your machine.

NOTE:

For avoiding  your settings get revoked after reboots, you may need to make the following changes via the command line:

$ sudo cp /etc/resolv.conf /etc/resolv.conf.auto
$ gksudo gedit /etc/dhcp3/dhclient.conf
# append the following line to the document
prepend domain-name-servers 8.8.8.8, 8.8.4.4;
# save and exit
$ sudo ifdown eth0 && sudo ifup eth0

What are the Types of Data Mining?
Author: Maneet Puri

Web mining, an extension of data mining implies employing the techniques of data mining to documents on the Internet. Web mining is used to study various aspects of a website and recognize the relationships and patterns in user behavior in order to get an insight into crucial information. For example, if you have to improve the accessibility quotient of your website, you need to know crucial points that need to be improved. Web mining services presents you the required results. It takes into consideration the IP addresses of website visitors, browser logs, cookies and so on.

Web mining tools analyze these logs and process them accordingly to produce meaningful and understandable information. For example, various bits of information can be analyzed to track the browsing route of website visitors. This may assist you in devising ways to make your website more effective.

The whole process of web mining involves extracting information from the internet through traditional practices of data mining and applying it to specific features of the website.

Types of Web Mining
Web mining helps to discover information, find related data and documents, identify patterns and trends and make sure that the web resources remain efficient. There are three main types of web mining:

• Web Content Mining
• Web Usage Mining
• Web Structure Mining

Web Content Mining
This process seeks to discover all the links of hyperlinks within a document in order to generate a structural report on the web page. Information about various facets, for example if users are able to find information, if the website structure is too deep or too shallow, are the web page elements placed correctly, what are the most visited and least visited areas of a website and do they have anything to do with the page design, all these are evaluated and analyzed for further research.

Web Usage Mining
In this process, data mining techniques are applied to discover patterns and trends in the browsing behavior of website visitors. Navigation patters are extracted and so that browsing patters can be deciphered and website structure and designed accordingly. For instance, if there is any particular feature of the website that visitors tend to use very often, you should seek to make it more pronounced and enhanced in order to increase the usability and appeal more to the users. This process makes use of logs and accesses of the web.

By understanding visitor movement and behavior as they surf the internet, you can seek to cater to their needs and preferences better and thus make your website popular among the internet masses.

Web Structure Mining
Web structure mining involves the use of graph theory to analyze the node and connection structure of a website. And as per the nature and type of web structure data, web mining is further divided into two types.

One, extracting patterns from hyperlinks on the internet. A hyperlink is a structural web address that connects the web page to another location. Second kind of web mining is mining the document structure. A tree-like structure is used to analyze and describe the HTML or XHTML tags within the web page.

About the Author:

Maneet Puri is the managing director of LeXolution IT Services, a premier off shore outsourcing company that specializes in providing efficient KPO services. Some of the services provided by the company are Data mining, internet market research and virtual private assistance.

Article Source: ArticlesBase.com – What are the Types of Data Mining?

Holidays in beautiful Umbria (Italy) give the opportunity to do some reading. With a strong interest in clould computing, I read Cloud Application Architectures by Georges Reese this summer. Around the same time last year (2008), I read Programming Amazon Web Services by James Murty.

The book “Programming Amazon Web Services” was really good in 2008. It describes the different Amazon offerings and how to invoke the API’s using Ruby. But Amazon is extending its offering a a rapid pace, e.g. with fixed IP addresses and block storages (like NAS). So James Murty’s book is in need for a 2nd edition.

“Cloud Application Architecture” goes up the stack to a higher abstraction level and explains how to deploy (“architect”) application on the Amazon cloud. Georges Reese has gained practical experience while deploying the Valtira (Web Marketing) application on Amazon.

Reese covers some very interesting topics:

• Load balancing with software load balancer in the cloud vs. HW load balancer on premise
• Cost comparison with sample calculation; : making the comparison with operating application on own hardware or in the cloud
• (High) Availability with some sample calculations
• Use of stateless application servers
• (Virtual) Machine images: outweihing generic vs. specific machine images; the use of startup-scripts with user-data
• Privacy: example on how to separate private information and encrypt it with key generated for each customer/partner/…
• Database management: outweighing clustering vs replication, whereby replication is usually considered the better option; the slave(s) can be used for read operations and backups; solutions for primary key generation and optimistic locking
• Data Security: e.g. through file system encryption
• Network security: security groups as alternative to firewalls, the fact that network intrusion detection cannot be used in Amazon context, why network level encryption still makes sense even if machine cannot see eachother’s traffic at Amazon, system hardening (Bastille), Host intruction detection (OSSEC), anti-virus
• Disaster Recovery, backups, recovery, redundancy,
• Scaling & capacity planning, the non-sense of auto-scaling

A real joy to read, but sometimes I would have loved that the author went into some more depth. One thing definitely became clear to me: deploying application on the (Amazon) cloud requires specific approaches and skills with obviously a sound and well-thought architecture. Also specific tools will be helpful and needed: Rightscale and enStratus are mentioned in the book. That’s probably the reason why Reese is also the CTO of enStratus.

We may expect many more cloud books in the coming months but “Cloud Application Architectures” brings quality content well ahead of the pack.

PS: podcast with interview of George Reese available here, same quality and content