Google Wave has a lot of innovative features, but here are just a few:
- Real-time: In most instances, you can see what someone else is typing, character-by-character.
- Embeddability: Waves can be embedded on any blog or website.
- Applications and Extensions: Just like a Facebook() application or an iGoogle gadget, developers can build their own apps within waves. They can be anything from bots to complex real-time games.
- Wiki functionality: Anything written within a Google Wave can be edited by anyone else, because all conversations within the platform are shared. Thus, you can correct information, append information, or add your own commentary within a developing conversation.
- Open source: The Google Wave code will be open source, to foster innovation and adoption amongst developers.
- Playback: You can playback any part of the wave to see what was said.
- Natural language: Google Wave can autocorrect your spelling, even going as far as knowing the difference between similar words, like “been” and “bean.” It can also auto-translate on-the-fly.
- Drag-and-drop file sharing: No attachments; just drag your file and drop it inside Google Wave and everyone will have access.
While these are only a few of the many features of Google Wave, it’s easy to see why people are extremely excited.
Google Wave was the brainchild of a team based out of Sydney, Australia. The core team members are two brothers, Jens and Lars Rasmussen, and lead project manager Stephanie Hannon, all of whom were involved in Google Maps() previously. Google Wave was announced today at Google’s I/O Developer conference, although the product will not be available to the public for several months.
Source: http://mashable.com/2009/05/28/google-wave-guide/
Sunday, May 31, 2009
Google Wave

source: http://mashable.com/2009/05/28/google-wave-guide/
Today has been dominated by news and excitement surrounding Google Wave(), Google()’s new real-time communication platform that will launch to the public later this year. In fact, there’s been so much buzz that you might just not have enough time to read the thousands of articles being released on Google’s biggest product launch in recent memory.
To make sense of it all, we have compiled key information, definitions, and links related to the launch of Google Wave. This in-depth guide provides an overview of Google Wave, discusses the terminology associated with it, details information on Google Wave applications, (i.e. the Twitter Wave app Twave), and goes over ways to keep yourself informed. We know you’re excited about Google Wave, so here’s what we think you should know.
Google Wave actually has its own lingo - yes, you have to learn a few definitions if you’re going to really understand this new communication platform. Having knowledge of these terms will help you understand more about Google’s newest project.
- Wave: A wave, specifically, refers to a specific threaded conversation. It can include just one person, or it can include a group of users or even robots (explained below). The best comparison I can make is that it’s like your entire instant messaging (IM) history with someone. Anything you’ve ever discussed in a single chat or conversation is a wave.
- Wavelet: A wavelet is also a threaded conversation, but only a subset of a larger conversation (or a wave). It’s like a single IM conversation - a small part of a larger conversation and a larger history. Wavelets, though, can be created and managed separately from a wave.
- Blip(): Even smaller than a Wavelet, a Blip is a single, individual message. It’s like a single line of an IM conversation. Blips can have other blips attached to them, called children. In addition, blips can either be published or unpublished (once again, it’s sort of like typing out an IM message but not yet sending it).
- Document: A document actually refers to the content within a blip. This seems to refer to the actual characters, words, and files associated with a blip.
- Extension: An extension is a mini-application that works within a wave. So these are the apps you can play with while using Wave. There are two main types of extenisons: Gadgets and Robots
- Gadgets: A gadget is an application users can participate with, many of which are built on Google’s OpenSocial platform. A good comparison would be iGoogle gadgets or Facebook applications.
- Robots: Robots are an automated participant within a wave. They can talk with users and interact with waves. They can provide information from outside sources (i.e. Twitter()) or they can check content within a wave and perform actions based on them (i.e. provide you a stock quote if a stock name is mentioned).
- Embeded Wave: An embeded wave is a way to take a Google Wave and the conversation within it and place it on your website. Users could use this as a chatroom, as a way to contact you, or for something more.
Today has been dominated by news and excitement surrounding Google Wave(), Google()’s new real-time communication platform that will launch to the public later this year. In fact, there’s been so much buzz that you might just not have enough time to read the thousands of articles being released on Google’s biggest product launch in recent memory.
To make sense of it all, we have compiled key information, definitions, and links related to the launch of Google Wave. This in-depth guide provides an overview of Google Wave, discusses the terminology associated with it, details information on Google Wave applications, (i.e. the Twitter Wave app Twave), and goes over ways to keep yourself informed. We know you’re excited about Google Wave, so here’s what we think you should know.
Google Wave actually has its own lingo - yes, you have to learn a few definitions if you’re going to really understand this new communication platform. Having knowledge of these terms will help you understand more about Google’s newest project.
- Wave: A wave, specifically, refers to a specific threaded conversation. It can include just one person, or it can include a group of users or even robots (explained below). The best comparison I can make is that it’s like your entire instant messaging (IM) history with someone. Anything you’ve ever discussed in a single chat or conversation is a wave.
- Wavelet: A wavelet is also a threaded conversation, but only a subset of a larger conversation (or a wave). It’s like a single IM conversation - a small part of a larger conversation and a larger history. Wavelets, though, can be created and managed separately from a wave.
- Blip(): Even smaller than a Wavelet, a Blip is a single, individual message. It’s like a single line of an IM conversation. Blips can have other blips attached to them, called children. In addition, blips can either be published or unpublished (once again, it’s sort of like typing out an IM message but not yet sending it).
- Document: A document actually refers to the content within a blip. This seems to refer to the actual characters, words, and files associated with a blip.
- Extension: An extension is a mini-application that works within a wave. So these are the apps you can play with while using Wave. There are two main types of extenisons: Gadgets and Robots
- Gadgets: A gadget is an application users can participate with, many of which are built on Google’s OpenSocial platform. A good comparison would be iGoogle gadgets or Facebook applications.
- Robots: Robots are an automated participant within a wave. They can talk with users and interact with waves. They can provide information from outside sources (i.e. Twitter()) or they can check content within a wave and perform actions based on them (i.e. provide you a stock quote if a stock name is mentioned).
- Embeded Wave: An embeded wave is a way to take a Google Wave and the conversation within it and place it on your website. Users could use this as a chatroom, as a way to contact you, or for something more.

Twitter as anomaly (#3) -- evolutionary de-evolution?
No one would have predicted that Twitter was going to be the next big thing, because it wasn’t/isn’t a logical “next step” in the evolution of the internet. Since html-based web pages put text and graphic files together on the same screen, the world wide web has been on a march to swallow all types of media and to embed them in ever-increasing quality (thank you, bandwidth). Twitter is “de-evolutionary”—taking us back to something that is simpler and even more constrained than basic text email.
Did the internet originally simply skip over Twitter (and is now going back to correct this mistake) or has Twitter actually arisen at its proper time and place?
source: http://something-about-twitter.tumblr.com/
by Allen Bukoff, PhD.
Social Psychologist.
Business consultant.
I am NOT a social media expert. There may not be any real experts on "social media" yet. It's probably too early for that. We don't even know where this is all going. But it looks like it's going to be an interesting ride. Especially Twitter! There's something really really fascinating and different about Twitter.
@bukoff on Twitter (the writer)
@iuoma onTwitter (that is me)
Friday, May 29, 2009
BING?
A new searchengine is coming soon. See http://www.bing.com/ which will give you access as soon as it is online. The demovideo at http://www.decisionengine.com/Default.html gives you a glimps of what is coming. Microsoft tries to beat Google. We will see what the public thinks of this soon.....
Sunday, April 26, 2009
Google Analytics
Google Analytics offers a weath of possibilities when one wants to know all about a website. The only problem I see is that it is a commercial product that Google wan'ts to promote and when you use it and like it it might cause a problem of becoming dependent on the system. They made the analyses for free when your site doesn't generate too much traffic. You can monitor several sites from one console. Webdesignes and webmasters for sure will love this tool but eventually will need a subscription to have access to the data. But I must confess, the interface Google Analytics has designed is a fantastic tool for sure.
Details: http://www.google.com/analytics/
Off course I started the tracking tool from Google Analytics also on this blog. We will see what it bring and I will report on it later too.
Details: http://www.google.com/analytics/
Off course I started the tracking tool from Google Analytics also on this blog. We will see what it bring and I will report on it later too.
Friday, March 20, 2009
Stats on 20-3-2009

No changes on the BLOG for 4 months, still 2000 visitors to the blog. I must have done something right with this blog since the visitors come even without having any new information to tell you. Since a class of Mediatechnology gets a workshop on this theme, and I will use this blog as sample for some elements, I will publish a few new goodies here soon.....
Sunday, November 16, 2008
Stats on 16-11-2008
Choose HTML
There is one main benefit of search engine marketing and that is web accessibility. The more accessible your website is to search engines, the more visits your website will get. Using good search engine marketing skills, you can ensure your website a top spot on most major search engines.
First, when trying to get the most from search engine marketing, you should consider assigning ALT Descriptions on your site, which are used by visually impaired visitors, who cannot understand images. To ensure proper accessibility, ALT description should be assigned to each and every image. By doing this you will not only be assisting your visually impaired visitors, you will also help raise your search engine rating, as well as benefit more from search engine marketing.
Next, in order to get the most from search engine marketing, it is always good to avoid embedding text in images on your website. There is strong evidence to suggest search engines assign less importance to embedded text in images. So to get the best results from search engine marketing it is best to avoid embedding text in your website images. It is best to use HTML.
Another good tip to getting the most from search engine marketing is to be sure to use plenty of link text in your written content. Search engines are generally known to place great importance on link text. So when at all possible, to get the most from search engine marketing, use plenty of link text on your website.
Finally, if you know anything at all about search engine marketing, or search engine optimization, it should be that your page title is among one of the most attributes on the page. If it properly describes the content of your page, more search engines will be able to more accurately interpret what your page is about, giving you more out of search engine marketing.
source: http://www.dimacc.com/search-engine-marketing.html
First, when trying to get the most from search engine marketing, you should consider assigning ALT Descriptions on your site, which are used by visually impaired visitors, who cannot understand images. To ensure proper accessibility, ALT description should be assigned to each and every image. By doing this you will not only be assisting your visually impaired visitors, you will also help raise your search engine rating, as well as benefit more from search engine marketing.
Next, in order to get the most from search engine marketing, it is always good to avoid embedding text in images on your website. There is strong evidence to suggest search engines assign less importance to embedded text in images. So to get the best results from search engine marketing it is best to avoid embedding text in your website images. It is best to use HTML.
Another good tip to getting the most from search engine marketing is to be sure to use plenty of link text in your written content. Search engines are generally known to place great importance on link text. So when at all possible, to get the most from search engine marketing, use plenty of link text on your website.
Finally, if you know anything at all about search engine marketing, or search engine optimization, it should be that your page title is among one of the most attributes on the page. If it properly describes the content of your page, more search engines will be able to more accurately interpret what your page is about, giving you more out of search engine marketing.
source: http://www.dimacc.com/search-engine-marketing.html
Friday, August 22, 2008
Motigo Counter New
The Motigo Counter has a new feature in it. Thet call it the "Heat-Map". It has been activated to test the results. It takes 48 hours to be fully operational.
Tuesday, March 4, 2008
Search engine marketing (SEM)
From Wikipedia, the free encyclopedia
Search engine marketing, or SEM, is a form of Internet marketing that seeks to promote websites by increasing their visibility in search engine result pages (SERPs). According to the Search Engine Marketing Professionals Organization, SEM methods include: search engine optimization (or SEO), paid placement, and paid inclusion. Other sources, including the New York Times, define SEM as the practice of buying paid search listings.
Market structure
In 2006, North American advertisers spent US$9.4 billion on search engine marketing, a 62% increase over the prior year and a 750% increase over the 2002 year. The largest SEM vendors are Google AdWords, Yahoo! Search Marketing and Microsoft adCenter. As of 2006, SEM was growing much faster than traditional advertising.
History
As the number of sites on the Web increased in the mid-to-late 90s, search engines started appearing to help people find information quickly. Search engines developed business models to finance their services, such as pay per click programs offered by Open Text in 1996 and then Goto.com in 1998. Goto.com later changed its name to Overture in 2001, and was purchased by Yahoo! in 2003, and now offers paid search opportunities for advertisers through Yahoo! Search Marketing. Google also began to offer advertisements on search results pages in 2000 through the Google AdWords program. By 2007 pay-per-click programs proved to be primary money-makers for search engines.
Search engine optimization consultants expanded their offerings to help businesses learn about and use the advertising opportunites offered by search engines, and new agencies focusing primarily upon marketing and advertising through search engines emerged. The term "Search Engine Marketing" was proposed by Danny Sullivan in 2001 to cover the spectrum of activities involved in performing SEO, managing paid listings at the search engines, submitting sites to directories, and developing online marketing strategies for businesses, organizations, and individuals. In 2007 Search Engine Marketing is stronger than ever with SEM Budgets up 750% as shown with stats dating back to 2002 vs 2006.[citation needed]
Ethical questions
Paid search advertising hasn't been without controversy, and issues around how many search engines present advertising on their pages of search result sets have been the target of a series of studies and reports by Consumer Reports WebWatch, from Consumers Union. The FTC also issued a letter in 2002 about the importance of disclosure of paid advertising on search engines, in response to a complaint from Commercial Alert, a consumer advocacy group with ties to Ralph Nader.
Sunday, February 24, 2008
Smile about Statistics
Statistics are for most students and researchers not very pleasible and even they hate it. For them we give on this page some food for thought (quotations) and smiling material (jokes and cartoons) on statistics. Enjoy yourself and know that statistics is not so bad as it seems.
Do you know of good quotes, jokes or cartoons on Statistics? Please don't hesitate, and send it to us. Thanks in advance.
Quotations
There are lies, darned lies, and statistical outliers.
Statistics means never having to say you're certain.
Statistics is the art of never having to say you're wrong. Variance is what any two statisticians are at. - C.J.Bradfield
A statistician is a person who draws a mathematically precise line from an unwarranted assumption to a foregone conclusion.
A statistician is a person who stands in a bucket of ice water, sticks their head in an oven and says "on average, I feel fine!" - K.Dunnigan
A statistician drowned while crossing a stream that was, on average, 6 inches deep.
Most people use statistics the way a drunk uses a lamp post, more for support than enlightenment.
Figures don't lie, but liars figure. - Samuel Clemens (alias Mark Twain)
Are statisticians normal?
An engineer, a physicist, and a statistician were moose hunting in northern Canada. After a short walk through the marshes they spotted a HUGE moose 150 metres away. The engineer raised his gun and fired at the moose. A puff of dust showed that the bullet landed 3 metres to the right of the moose. The physicist, realizing that there was a substantial breeze that the engineer did not account for, aimed to the left of the moose and fired. The bullet landed 3 metres to the left of the moose. The statistician jumped up and down and screamed "We got him! We got him!"
The weather man is never wrong. Suppose he says that there's an 80% chance of rain. If it rains, the 80% chance came up; if it doesn't, the 20% chance came up! - Saul Barron
All measurements are subject to variation.
The minute a statistician steps into the position of the executive who must make decisions and defend them, the statistician ceases to be a statistician. - W.E.Deming
I feel that the kind of examples of statistical analysis that tend to be considered in professional discussions ... are so grossly over-simplified as to make a pretentious mockery of real-life situations and statistical consultancy. - A.Ehrenberg
There are lies, damned lies, and statistics! - B.Disraeli
It has long recognized by public men of all kinds ... that statistics come under the head of lying, and that no lie is so false or inconclusive as that which is based on statistics. - H.Belloc
Like dreams, statistics are a form of wish fulfillment. - J.Baudrillard
Where is the knowledge that is lost in information? Where is the wisdom that is lost in knowledge? - T.S.Eliot
One picture is worth more than ten thousand words.
The only useful function of a statistician is to make predictions, and thus to provide a basis for action. - W.E.Deming
The most powerful mathematical tools are sometimes less important to the engineer than some of the simpler or less powerful tools. But often, for lack of information about either, neither is used. - C.M.Ryerson
A knowledge of statistics is like a knowledge of foreign languages or of algebra; it may prove of use at any time under any circumstances. - A.L.Bowley
The long-range contribution of statistics depends not so much upon getting a lot of highly trained statisticians into industry as it does in creating a statistically minded generation of physicists, chemists, engineers, and others who will in any way have a hand in developing and directing the production processes of tomorrow. - W.A.Shewhart & W.E.Deming
The fundamental difference between engineering with and without statistics boils down to the difference between the use of a scientific method based upon the concept of laws of nature that do not allow for chance or uncertainty and a scientific method based upon the concept of laws of probability as an attribute of nature. - W.A.Shewhart
When you can measure what you are speaking about and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of the meager and unsatisfactory kind. - Lord Kelvin (British physicist)
1. If quality and productivity are to improve from current levels, changes must be made in the way things are presently being done.
2. We should like to have good data to serve as a rational basis on which to make these changes.
3. The twin question must then be addressed: what data should be collected, and, once collected, how should they be analyzed?
4. Statistics is the science that addresses this twin question. - W.G.Hunter
Do you know of good quotes, jokes or cartoons on Statistics? Please don't hesitate, and send it to us. Thanks in advance.
Quotations
There are lies, darned lies, and statistical outliers.
Statistics means never having to say you're certain.
Statistics is the art of never having to say you're wrong. Variance is what any two statisticians are at. - C.J.Bradfield
A statistician is a person who draws a mathematically precise line from an unwarranted assumption to a foregone conclusion.
A statistician is a person who stands in a bucket of ice water, sticks their head in an oven and says "on average, I feel fine!" - K.Dunnigan
A statistician drowned while crossing a stream that was, on average, 6 inches deep.
Most people use statistics the way a drunk uses a lamp post, more for support than enlightenment.
Figures don't lie, but liars figure. - Samuel Clemens (alias Mark Twain)
Are statisticians normal?
An engineer, a physicist, and a statistician were moose hunting in northern Canada. After a short walk through the marshes they spotted a HUGE moose 150 metres away. The engineer raised his gun and fired at the moose. A puff of dust showed that the bullet landed 3 metres to the right of the moose. The physicist, realizing that there was a substantial breeze that the engineer did not account for, aimed to the left of the moose and fired. The bullet landed 3 metres to the left of the moose. The statistician jumped up and down and screamed "We got him! We got him!"
The weather man is never wrong. Suppose he says that there's an 80% chance of rain. If it rains, the 80% chance came up; if it doesn't, the 20% chance came up! - Saul Barron
All measurements are subject to variation.
The minute a statistician steps into the position of the executive who must make decisions and defend them, the statistician ceases to be a statistician. - W.E.Deming
I feel that the kind of examples of statistical analysis that tend to be considered in professional discussions ... are so grossly over-simplified as to make a pretentious mockery of real-life situations and statistical consultancy. - A.Ehrenberg
There are lies, damned lies, and statistics! - B.Disraeli
It has long recognized by public men of all kinds ... that statistics come under the head of lying, and that no lie is so false or inconclusive as that which is based on statistics. - H.Belloc
Like dreams, statistics are a form of wish fulfillment. - J.Baudrillard
Where is the knowledge that is lost in information? Where is the wisdom that is lost in knowledge? - T.S.Eliot
One picture is worth more than ten thousand words.
The only useful function of a statistician is to make predictions, and thus to provide a basis for action. - W.E.Deming
The most powerful mathematical tools are sometimes less important to the engineer than some of the simpler or less powerful tools. But often, for lack of information about either, neither is used. - C.M.Ryerson
A knowledge of statistics is like a knowledge of foreign languages or of algebra; it may prove of use at any time under any circumstances. - A.L.Bowley
The long-range contribution of statistics depends not so much upon getting a lot of highly trained statisticians into industry as it does in creating a statistically minded generation of physicists, chemists, engineers, and others who will in any way have a hand in developing and directing the production processes of tomorrow. - W.A.Shewhart & W.E.Deming
The fundamental difference between engineering with and without statistics boils down to the difference between the use of a scientific method based upon the concept of laws of nature that do not allow for chance or uncertainty and a scientific method based upon the concept of laws of probability as an attribute of nature. - W.A.Shewhart
When you can measure what you are speaking about and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of the meager and unsatisfactory kind. - Lord Kelvin (British physicist)
1. If quality and productivity are to improve from current levels, changes must be made in the way things are presently being done.
2. We should like to have good data to serve as a rational basis on which to make these changes.
3. The twin question must then be addressed: what data should be collected, and, once collected, how should they be analyzed?
4. Statistics is the science that addresses this twin question. - W.G.Hunter
Thursday, January 24, 2008
The Kartoo Search Engine

On http://www.kartoo.com/ there is a wonderfull search engine that works visual. The words you look for are investigated and a visual presentation of the results is given. You can easily deepen you search and visualize the sites that are offered.
Saturday, January 19, 2008
Technorati update 19-1-2008
Looking at a new update from Technorati shows that the Authority of some blogs doesn't increase that much. An exception is the Mail-Art Projects blog that has now Authority 31. Reasons: There are 60+ contributors to this blog and also lots of these contributors link to the blog. This aspect has raised the Autority to a double level in only a single month.


New Content = Visitors
It is a basic rule in websites. You can attract visitors to a website when you place new content on a regular basis. I have tested it with this blog. A silence of a few eeeks means that the amount of visitors drops. Just a single new posting means that indexing machines place you on a higher scale and that results in a better visibility of your website.
Wednesday, December 12, 2007
Data Mining - Theory
Data Mining
`We are drowning in information but starved for knowledge.'
John Naisbitt
What is data mining?
Data mining sits at the interface between statistics, computer science, artificial intelligence, pattern recognition, machine learning, database management and data visualisation (to name some of the fields).
Data mining is the non-trivial process of identifying valid, novel, potentially useful, and ultimately comprehensible patterns or models in data to make crucial decisions. Data mining is not a product that can be bought. Data mining is a discipline and process that must be mastered - a whole problem solving cycle.
The main part of data mining is concerned with the analysis of data and the use of software techniques for finding patterns and regularities in sets of data. The idea is that it is possible to strike gold in unexpected places as the data mining software extracts patterns not previously discernible or so obvious that no-one has noticed them before. The analysis process starts with a set of data, uses a methodology to develop an optimal representation of the structure of the data during which time knowledge is acquired. Once knowledge has been acquired this can be extended to larger sets of data working on the assumption that the larger data set has a structure similar to the sample data. This is analogous to a mining operation where large amounts of low grade materials are sifted through in order to find something of value.
Is data mining `statistical déjà vu'?
Whereas statistical analysis traditionally concerns itself with analysing primary data that has been collected to check specific research hypotheses (`primary data analysis'), data mining can also concern itself with secondary data collected for other reasons (`secondary data analysis'). Furthermore, data can be experimental data (perhaps the result of an experiment which randomly allocates all the statistical units to different kinds of treatment), but in data mining the data is typically observational data.
Data warehousing provides the enterprise with a memory
Companies are collecting data on seemingly everything. For example, a customer-focused enterprise regards every record of an interaction with a client or prospect (e.g. each call to customer support, each point-of-sale transaction, each catalogue order, each visit to a company web site) as a learning opportunity. But, learning requires more than simply gathering data. In fact, many companies gather hundreds of gigabytes of data without learning anything. For example, data are gathered because they are needed for some operational purpose, such as inventory control or billing. Once data served that purpose, data languish on tape or get discarded. The data's hidden value has largely gone untapped. For learning to take place, data from many sources (e.g. billing records, scanner data, registration forms, applications, call records, coupon redemption, surveys, manufacturing data) must first be gathered together and organised in a consistent and useful way - in a way that facilitates the retrieval of information for analytic purposes. This is called data warehousing. Data warehousing allows the enterprise to remember what it has noticed about its customers. Data warehousing provides the enterprise with a memory.
Data mining provides the enterprise with intelligence
Memory is of little use without intelligence. That is where data mining comes in. Intelligence allows us to comb through our memories noticing patterns, devising rules, coming up with new ideas to try, and making predictions about the future. The data must be analysed, understood and turned into actionable information. Using several data mining tools and techniques that add intelligence to the data warehouse, you will be able to exploit the vast mountains of data, for example, generated by interactions with your customers and prospects in order to get to know them better. Typical customer-focused business questions are:
What customers are most likely to respond to a mailing?
Are there groups (or segments) of customers with similar characteristics or behavior?
Are there interesting relationships between customer characteristics?
Who is likely to remain a loyal customer and who is likely to jump ship?
Where should the next branch be located?
What is the next product or service this customer will want?
Answers to questions like these lie buried in your corporate data, but it takes powerful data mining tools to get at them, i.e. to dig user info for gold. Data mining provides the enterprise with intelligence. Companies can use data mining findings for more profitable, proactive decision making and competitive advantage.
With data mining, companies can, for example, analyze customers' past behaviors in order to make strategic decisions for the future. Keep in mind, however, that the data mining techniques and tools are equally applicable in fields ranging from law enforcement to radio astronomy, medicine, and industrial process control.
Please contact us today in order to discuss how data mining can be applied to your field or work. Get Statooed.
Data mining myths versus realities
A great deal of what is said about data mining is incomplete, exaggerated, or wrong. Data mining has taken the business world by storm, but as with many new technologies, there seems to be a direct relationship between its potential benefits and the quantity of (often) contradictory claims, or myths, about its capabilities and weaknesses. When you undertake a data mining project, avoid a cycle of unrealistic expectations followed by disappointment. Understand the facts instead and your data mining efforts will be (hopefully) successful. A list of the most common data mining myths versus realities you will find here.
Data mining can not be ignored - the data is there, the methods are numerous, and the advantages that knowledge discovery brings are tremendous. Companies whose data mining efforts are guided by `mythology' will find themselves at a serious competitive disadvantage to those organizations taking a measured, rational approach based on facts.
source: http://www.statoo.com/en/datamining/
`We are drowning in information but starved for knowledge.'
John Naisbitt
What is data mining?
Data mining sits at the interface between statistics, computer science, artificial intelligence, pattern recognition, machine learning, database management and data visualisation (to name some of the fields).
Data mining is the non-trivial process of identifying valid, novel, potentially useful, and ultimately comprehensible patterns or models in data to make crucial decisions. Data mining is not a product that can be bought. Data mining is a discipline and process that must be mastered - a whole problem solving cycle.
The main part of data mining is concerned with the analysis of data and the use of software techniques for finding patterns and regularities in sets of data. The idea is that it is possible to strike gold in unexpected places as the data mining software extracts patterns not previously discernible or so obvious that no-one has noticed them before. The analysis process starts with a set of data, uses a methodology to develop an optimal representation of the structure of the data during which time knowledge is acquired. Once knowledge has been acquired this can be extended to larger sets of data working on the assumption that the larger data set has a structure similar to the sample data. This is analogous to a mining operation where large amounts of low grade materials are sifted through in order to find something of value.
Is data mining `statistical déjà vu'?
Whereas statistical analysis traditionally concerns itself with analysing primary data that has been collected to check specific research hypotheses (`primary data analysis'), data mining can also concern itself with secondary data collected for other reasons (`secondary data analysis'). Furthermore, data can be experimental data (perhaps the result of an experiment which randomly allocates all the statistical units to different kinds of treatment), but in data mining the data is typically observational data.
Data warehousing provides the enterprise with a memory
Companies are collecting data on seemingly everything. For example, a customer-focused enterprise regards every record of an interaction with a client or prospect (e.g. each call to customer support, each point-of-sale transaction, each catalogue order, each visit to a company web site) as a learning opportunity. But, learning requires more than simply gathering data. In fact, many companies gather hundreds of gigabytes of data without learning anything. For example, data are gathered because they are needed for some operational purpose, such as inventory control or billing. Once data served that purpose, data languish on tape or get discarded. The data's hidden value has largely gone untapped. For learning to take place, data from many sources (e.g. billing records, scanner data, registration forms, applications, call records, coupon redemption, surveys, manufacturing data) must first be gathered together and organised in a consistent and useful way - in a way that facilitates the retrieval of information for analytic purposes. This is called data warehousing. Data warehousing allows the enterprise to remember what it has noticed about its customers. Data warehousing provides the enterprise with a memory.
Data mining provides the enterprise with intelligence
Memory is of little use without intelligence. That is where data mining comes in. Intelligence allows us to comb through our memories noticing patterns, devising rules, coming up with new ideas to try, and making predictions about the future. The data must be analysed, understood and turned into actionable information. Using several data mining tools and techniques that add intelligence to the data warehouse, you will be able to exploit the vast mountains of data, for example, generated by interactions with your customers and prospects in order to get to know them better. Typical customer-focused business questions are:
What customers are most likely to respond to a mailing?
Are there groups (or segments) of customers with similar characteristics or behavior?
Are there interesting relationships between customer characteristics?
Who is likely to remain a loyal customer and who is likely to jump ship?
Where should the next branch be located?
What is the next product or service this customer will want?
Answers to questions like these lie buried in your corporate data, but it takes powerful data mining tools to get at them, i.e. to dig user info for gold. Data mining provides the enterprise with intelligence. Companies can use data mining findings for more profitable, proactive decision making and competitive advantage.
With data mining, companies can, for example, analyze customers' past behaviors in order to make strategic decisions for the future. Keep in mind, however, that the data mining techniques and tools are equally applicable in fields ranging from law enforcement to radio astronomy, medicine, and industrial process control.
Please contact us today in order to discuss how data mining can be applied to your field or work. Get Statooed.
Data mining myths versus realities
A great deal of what is said about data mining is incomplete, exaggerated, or wrong. Data mining has taken the business world by storm, but as with many new technologies, there seems to be a direct relationship between its potential benefits and the quantity of (often) contradictory claims, or myths, about its capabilities and weaknesses. When you undertake a data mining project, avoid a cycle of unrealistic expectations followed by disappointment. Understand the facts instead and your data mining efforts will be (hopefully) successful. A list of the most common data mining myths versus realities you will find here.
Data mining can not be ignored - the data is there, the methods are numerous, and the advantages that knowledge discovery brings are tremendous. Companies whose data mining efforts are guided by `mythology' will find themselves at a serious competitive disadvantage to those organizations taking a measured, rational approach based on facts.
source: http://www.statoo.com/en/datamining/
Tuesday, December 11, 2007
ClustrMaps - December 11th 2007

The results on ClustrMaps show that visitors to this blog come from all directions. The blog still isn't that active, but it seems to attract visitors from all continents. Probably because the information is specific but not country-related.
Labels:
Clustrmap,
Results,
Returning Visitors,
Statictical Data
Saturday, December 8, 2007
Google Page Rank Update
Posted by David Peralty as Blogging News, General
Don’t get too excited it will take a while for everything to settle, but it looks like it is Google Page Rank update time again. This means your blog could shift around in search results leading to more or less traffic. For those of you getting higher page ranks you might be able to leverage it for some more money, for those of you dropping in page rank, you will probably not be able to make as much money through things like banner and text link advertising.
Good luck to everyone, and may your page ranks be high.
Source: Problogger.net
Don’t get too excited it will take a while for everything to settle, but it looks like it is Google Page Rank update time again. This means your blog could shift around in search results leading to more or less traffic. For those of you getting higher page ranks you might be able to leverage it for some more money, for those of you dropping in page rank, you will probably not be able to make as much money through things like banner and text link advertising.
Good luck to everyone, and may your page ranks be high.
Source: Problogger.net
Developments in Blogs
by David Peralty as Blog Statistics
There is a great post up on Read/WriteWeb about bloggers, the types that are currently out there, and where the blogosphere may be heading. It is a bit long, but very enjoyable, especially if you are interested in blogging for a variety of reasons.
Here is a snippet from the article:
It was a good conference and we had several interesting conversations, but I walked away with a strange feeling. Somehow it seemed that blogging just isn’t that hot anymore. The feeling has been exacerbated by the latest slow down in news. My feeds just do not update that often these days. Can it be that the digestion phase applies to blogs just as it applies to startups? In this post we’ll investigate whether the blogosphere is going through a digestion phase.
Definitely worth a read though I hope we are not in a digestion phase. I still like the crazy unbridled growth we’ve seen over the past two or three years.
There is a great post up on Read/WriteWeb about bloggers, the types that are currently out there, and where the blogosphere may be heading. It is a bit long, but very enjoyable, especially if you are interested in blogging for a variety of reasons.
Here is a snippet from the article:
It was a good conference and we had several interesting conversations, but I walked away with a strange feeling. Somehow it seemed that blogging just isn’t that hot anymore. The feeling has been exacerbated by the latest slow down in news. My feeds just do not update that often these days. Can it be that the digestion phase applies to blogs just as it applies to startups? In this post we’ll investigate whether the blogosphere is going through a digestion phase.
Definitely worth a read though I hope we are not in a digestion phase. I still like the crazy unbridled growth we’ve seen over the past two or three years.
Tuesday, November 20, 2007
Nedstats - search engines
Search Engines - Theory
Search engines provide an interface to a group of items that enables users to specify criteria about an item of interest and have the engine find the matching items. The criteria are referred to as a search query. In the case of text search engines, the search query is typically expressed as a set of words that identify the desired concept that one or more documents may contain.[1]
There are several styles of search query syntax that vary in strictness. Where as some text search engines require users to enter two or three words separated by white space, other search engines may enable users to specify entire documents, pictures, sounds, and various forms of natural language. Some search engines apply improvements to search queries to increase the likelihood of providing a quality set of items through a process known as query expansion.
index-based search engineThe list of items that meet the criteria specified by the query is typically sorted, or ranked, in some regard so as to place the most relevant items first. Ranking items by relevance (from highest to lowest) reduces the time required to find the desired information. Probabilistic search engines rank items based on measures of similarity and sometimes popularity or authority. Boolean search engines typically only return items which match exactly without regard to order.
To provide a set of matching items quickly, a search engine will typically collect metadata about the group of items under consideration beforehand through a process referred to as indexing. The index typically requires a smaller amount of computer storage, and provides a basis for the search engine to calculate item relevance. The search engine may store of copy of each item in a cache so that users can see the state of the item at the time it was indexed or for archive purposes or to make repetitive processes work more efficiently and quickly.
Notably, some search engines do not store an index. Crawler, or spider type search engines may collect and assess items at the time of the search query. Meta search engines simply reuse the index or results of one or more other search engines.
source: http://en.wikipedia.org/wiki/Search_engines
There are several styles of search query syntax that vary in strictness. Where as some text search engines require users to enter two or three words separated by white space, other search engines may enable users to specify entire documents, pictures, sounds, and various forms of natural language. Some search engines apply improvements to search queries to increase the likelihood of providing a quality set of items through a process known as query expansion.
index-based search engineThe list of items that meet the criteria specified by the query is typically sorted, or ranked, in some regard so as to place the most relevant items first. Ranking items by relevance (from highest to lowest) reduces the time required to find the desired information. Probabilistic search engines rank items based on measures of similarity and sometimes popularity or authority. Boolean search engines typically only return items which match exactly without regard to order.
To provide a set of matching items quickly, a search engine will typically collect metadata about the group of items under consideration beforehand through a process referred to as indexing. The index typically requires a smaller amount of computer storage, and provides a basis for the search engine to calculate item relevance. The search engine may store of copy of each item in a cache so that users can see the state of the item at the time it was indexed or for archive purposes or to make repetitive processes work more efficiently and quickly.
Notably, some search engines do not store an index. Crawler, or spider type search engines may collect and assess items at the time of the search query. Meta search engines simply reuse the index or results of one or more other search engines.
source: http://en.wikipedia.org/wiki/Search_engines
Sunday, November 4, 2007
Technorati Blog Info update 4-11-2007

It is always interesting to see the Authorities of Blogs. This one has now Authority 4. Two more blogs have a much higher Authority. They are much longer active of have several members that publish on the blog. I have 11 blogs lister at technorati. That way I can see how the interact and how things work....
Labels:
Authority,
Blogs,
IUOMA,
Netherlands,
Ruud Janssen,
Technorati
Wednesday, October 31, 2007
Motigo - Overview visitors 31-10-2007

While Statcounter only registers the last 500 hits, the Motigo counter saves all hits and therefore becomes interesting when one is searchibf for historical information. The longer a site is in the air, the more interesting the statistical data gets because one can make prognoses. Here is an overview of the countries visitors come from. Seems like they come also from abroad now. Even some dozens of hits from www.google.com themselves (in California, USA), so they are reading this too.....
Labels:
Countries,
Google,
Motigo,
Search Engine Marketing,
Statictical Data
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