Tag: Internet

Is Random Poetry Click Fraud

Meta-search-vi
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Is poetry when randomized

Tweaked, meta tagged , search engine optimized

Violative of unseen terms and conditional clauses

Is random poetry or aggregated prose farmed for click fraud uses

 

 

 

I dont know, you tell me, says the blog boy,

Tapping away at the keyboard like a shiny new toy,

Geeks unfortunately too often are men too many,

Forgive the generalization, but the tech world is yet to be equalized.

 

If a New York Hot Dog  is a slice of heaven at four bucks a piece

Then why is prose and poetry at five bucks an hour considered waste

Ah I see, you have grown old and cynical,

Of the numerous stupid internet capers and cyber ways

 

The clicking finger clicks on

swiftly but mostly delightfully virally moves on

While people collect its trails and

ponder its aggregated merry ways

 

All people are equal but all links are not,

Thus overturning two centuries of psychology had you been better taught,

But you chose to drop out of school, and create that search engine so big

It is now a fraud catchers head ache that millions try to search engine optimize and rig

 

Once again, people are different, in so many ways so prettier

Links are the same hyper linked code number five or earlier

People think like artificial artificial (thus natural) neural nets

Biochemically enhanced Harmonically possessed.

 

rather than  analyze forensically and quite creepily

where people have been

Gentic Algorithms need some chaos

To see what till now hasnt been seen.

 

Again this was a random poem,

inspired by a random link that someone clicked

To get here, on a carbon burning cyber machine,

Having digested poem, moves on, unheard , unseen.

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(Inspired by the Hyper Link at http://goo.gl/a8ijW )

Also-

Interview David Katz ,Dataspora /David Katz Consulting

Here is an interview with David Katz ,founder of David Katz Consulting (http://www.davidkatzconsulting.com/) and an analyst at the noted firm http://dataspora.com/. He is a featured speaker at Predictive Analytics World  http://www.predictiveanalyticsworld.com/sanfrancisco/2011/speakers.php#katz)

Ajay-  Describe your background working with analytics . How can we make analytics and science more attractive career options for young students

David- I had an interest in math from an early age, spurred by reading lots of science fiction with mathematicians and scientists in leading roles. I was fortunate to be at Harry and David (Fruit of the Month Club) when they were in the forefront of applying multivariate statistics to the challenge of targeting catalogs and other snail-mail offerings. Later I had the opportunity to expand these techniques to the retail sphere with Williams-Sonoma, who grew their retail business with the support of their catalog mailings. Since they had several catalog titles and product lines, cross-selling presented additional analytic challenges, and with the growth of the internet there was still another channel to consider, with its own dynamics.

After helping to found Abacus Direct Marketing, I became an independent consultant, which provided a lot of variety in applying statistics and data mining in a variety of settings from health care to telecom to credit marketing and education.

Students should be exposed to the many roles that analytics plays in modern life, and to the excitement of finding meaningful and useful patterns in the vast profusion of data that is now available.

Ajay-  Describe your most challenging project in 3 decades of experience in this field.

David- Hard to choose just one, but the educational field has been particularly interesting. Partnering with Olympic Behavior Labs, we’ve developed systems to help identify students who are most at-risk for dropping out of school to help target interventions that could prevent dropout and promote success.

Ajay- What do you think are the top 5 trends in analytics for 2011.

David- Big Data, Privacy concerns, quick response to consumer needs, integration of testing and analysis into business processes, social networking data.

Ajay- Do you think techniques like RFM and LTV are adequately utilized by organization. How can they be propagated further.

David- Organizations vary amazingly in how sophisticated or unsophisticated the are in analytics. A key factor in success as a consultant is to understand where each client is on this continuum and how well that serves their needs.

Ajay- What are the various software you have worked for in this field- and name your favorite per category.

David- I started out using COBOL (that dates me!) then concentrated on SAS for many years. More recently R is my favorite because of its coverage, currency and programming model, and it’s debugging capabilities.

Ajay- Independent consulting can be a strenuous job. What do you do to unwind?

David- Cycling, yoga, meditation, hiking and guitar.

Biography-

David Katz, Senior Analyst, Dataspora, and President, David Katz Consulting.

David Katz has been in the forefront of applying statistical models and database technology to marketing problems since 1980. He holds a Master’s Degree in Mathematics from the University of California, Berkeley. He is one of the founders of Abacus Direct Marketing and was previously the Director of Database Development for Williams-Sonoma.

He is the founder and President of David Katz Consulting, specializing in sophisticated statistical services for a variety of applications, with a special focus on the Direct Marketing Industry. David Katz has an extensive background that includes experience in all aspects of direct marketing from data mining, to strategy, to test design and implementation. In addition, he consults on a variety of data mining and statistical applications from public health to collections analysis. He has partnered with consulting firms such as Ernst and Young, Prediction Impact, and most recently on this project with Dataspora.

For more on David’s Session in Predictive Analytics World, San Fransisco on (http://www.predictiveanalyticsworld.com/sanfrancisco/2011/agenda.php#day2-16a)

Room: Salon 5 & 6
4:45pm – 5:05pm

Track 2: Social Data and Telecom 
Case Study: Major North American Telecom
Social Networking Data for Churn Analysis

A North American Telecom found that it had a window into social contacts – who has been calling whom on its network. This data proved to be predictive of churn. Using SQL, and GAM in R, we explored how to use this data to improve the identification of likely churners. We will present many dimensions of the lessons learned on this engagement.

Speaker: David Katz, Senior Analyst, Dataspora, and President, David Katz Consulting

Exhibit Hours
Monday, March 14th:10:00am to 7:30pm

Tuesday, March 15th:9:45am to 4:30pm

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Common Analytical Tasks

WorldWarII-DeathsByCountry-Barchart
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Some common analytical tasks from the diary of the glamorous life of a business analyst-

1) removing duplicates from a dataset based on certain key values/variables
2) merging two datasets based on a common key/variable/s
3) creating a subset based on a conditional value of a variable
4) creating a subset based on a conditional value of a time-date variable
5) changing format from one date time variable to another
6) doing a means grouped or classified at a level of aggregation
7) creating a new variable based on if then condition
8) creating a macro to run same program with different parameters
9) creating a logistic regression model, scoring dataset,
10) transforming variables
11) checking roc curves of model
12) splitting a dataset for a random sample (repeatable with random seed)
13) creating a cross tab of all variables in a dataset with one response variable
14) creating bins or ranks from a certain variable value
15) graphically examine cross tabs
16) histograms
17) plot(density())
18)creating a pie chart
19) creating a line graph, creating a bar graph
20) creating a bubbles chart
21) running a goal seek kind of simulation/optimization
22) creating a tabular report for multiple metrics grouped for one time/variable
23) creating a basic time series forecast

and some case studies I could think of-

 

As the Director, Analytics you have to examine current marketing efficiency as well as help optimize sales force efficiency across various channels. In addition you have to examine multiple sales channels including inbound telephone, outgoing direct mail, internet email campaigns. The datawarehouse is an RDBMS but it has multiple data quality issues to be checked for. In addition you need to submit your budget estimates for next year’s annual marketing budget to maximize sales return on investment.

As the Director, Risk you have to examine the overdue mortgages book that your predecessor left you. You need to optimize collections and minimize fraud and write-offs, and your efforts would be measured in maximizing profits from your department.

As a social media consultant you have been asked to maximize social media analytics and social media exposure to your client. You need to create a mechanism to report particular brand keywords, as well as automated triggers between unusual web activity, and statistical analysis of the website analytics metrics. Above all it needs to be set up in an automated reporting dashboard .

As a consultant to a telecommunication company you are asked to monitor churn and review the existing churn models. Also you need to maximize advertising spend on various channels. The problem is there are a large number of promotions always going on, some of the data is either incorrectly coded or there are interaction effects between the various promotions.

As a modeller you need to do the following-
1) Check ROC and H-L curves for existing model
2) Divide dataset in random splits of 40:60
3) Create multiple aggregated variables from the basic variables

4) run regression again and again
5) evaluate statistical robustness and fit of model
6) display results graphically
All these steps can be broken down in little little pieces of code- something which i am putting down a list of.
Are there any common data analysis tasks that you think I am missing out- any common case studies ? let me know.

 

 

 

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Interview Ajay Ohri Decisionstats.com with DMR

From-

http://www.dataminingblog.com/data-mining-research-interview-ajay-ohri/

Here is the winner of the Data Mining Research People Award 2010: Ajay Ohri! Thanks to Ajay for giving some time to answer Data Mining Research questions. And all the best to his blog, Decision Stat!

Data Mining Research (DMR): Could you please introduce yourself to the readers of Data Mining Research?

Ajay Ohri (AO): I am a business consultant and writer based out of Delhi- India. I have been working in and around the field of business analytics since 2004, and have worked with some very good and big companies primarily in financial analytics and outsourced analytics. Since 2007, I have been writing my blog at http://decisionstats.com which now has almost 10,000 views monthly.

All in all, I wrote about data, and my hobby is also writing (poetry). Both my hobby and my profession stem from my education ( a masters in business, and a bachelors in mechanical engineering).

My research interests in data mining are interfaces (simpler interfaces to enable better data mining), education (making data mining less complex and accessible to more people and students), and time series and regression (specifically ARIMAX)
In business my research interests software marketing strategies (open source, Software as a service, advertising supported versus traditional licensing) and creation of technology and entrepreneurial hubs (like Palo Alto and Research Triangle, or Bangalore India).

DMR: I know you have worked with both SAS and R. Could you give your opinion about these two data mining tools?

AO: As per my understanding, SAS stands for SAS language, SAS Institute and SAS software platform. The terms are interchangeably used by people in industry and academia- but there have been some branding issues on this.
I have not worked much with SAS Enterprise Miner , probably because I could not afford it as business consultant, and organizations I worked with did not have a budget for Enterprise Miner.
I have worked alone and in teams with Base SAS, SAS Stat, SAS Access, and SAS ETS- and JMP. Also I worked with SAS BI but as a user to extract information.
You could say my use of SAS platform was mostly in predictive analytics and reporting, but I have a couple of projects under my belt for knowledge discovery and data mining, and pattern analysis. Again some of my SAS experience is a bit dated for almost 1 year ago.

I really like specific parts of SAS platform – as in the interface design of JMP (which is better than Enterprise Guide or Base SAS ) -and Proc Sort in Base SAS- I guess sequential processing of data makes SAS way faster- though with computing evolving from Desktops/Servers to even cheaper time shared cloud computers- I am not sure how long Base SAS and SAS Stat can hold this unique selling proposition.

I dislike the clutter in SAS Stat output, it confuses me with too much information, and I dislike shoddy graphics in the rendering output of graphical engine of SAS. Its shoddy coding work in SAS/Graph and if JMP can give better graphics why is legacy source code preventing SAS platform from doing a better job of it.

I sometimes think the best part of SAS is actually code written by Goodnight and Sall in 1970’s , the latest procs don’t impress me much.

SAS as a company is something I admire especially for its way of treating employees globally- but it is strange to see the rest of tech industry not following it. Also I don’t like over aggression and the SAS versus Rest of the Analytics /Data Mining World mentality that I sometimes pick up when I deal with industry thought leaders.

I think making SAS Enterprise Miner, JMP, and Base SAS in a completely new web interface priced at per hour rates is my wishlist but I guess I am a bit sentimental here- most data miners I know from early 2000’s did start with SAS as their first bread earning software. Also I think SAS needs to be better priced in Business Intelligence- it seems quite cheap in BI compared to Cognos/IBM but expensive in analytical licensing.

If you are a new stats or business student, chances are – you may know much more R than SAS today. The shift in education at least has been very rapid, and I guess R is also more of a platform than a analytics or data mining software.

I like a lot of things in R- from graphics, to better data mining packages, modular design of software, but above all I like the can do kick ass spirit of R community. Lots of young people collaborating with lots of young to old professors, and the energy is infectious. Everybody is a CEO in R ’s world. Latest data mining algols will probably start in R, published in journals.

Which is better for data mining SAS or R? It depends on your data and your deadline. The golden rule of management and business is -it depends.

Also I have worked with a lot of KXEN, SQL, SPSS.

DMR: Can you tell us more about Decision Stats? You have a traffic of 120′000 for 2010. How did you reach such a success?

AO: I don’t think 120,000 is a success. Its not a failure. It just happened- the more I wrote, the more people read.In 2007-2008 I used to obsess over traffic. I tried SEO, comments, back linking, and I did some black hat experimental stuff. Some of it worked- some didn’t.

In the end, I started asking questions and interviewing people. To my surprise, senior management is almost always more candid , frank and honest about their views while middle managers, public relations, marketing folks can be defensive.

Social Media helped a bit- Twitter, Linkedin, Facebook really helped my network of friends who I suppose acted as informal ambassadors to spread the word.
Again I was constrained by necessity than choices- my middle class finances ( I also had a baby son in 2007-my current laptop still has some broken keys :) – by my inability to afford traveling to conferences, and my location Delhi isn’t really a tech hub.

The more questions I asked around the internet, the more people responded, and I wrote it all down.

I guess I just was lucky to meet a lot of nice people on the internet who took time to mentor and educate me.

I tried building other websites but didn’t succeed so i guess I really don’t know. I am not a smart coder, not very clever at writing but I do try to be honest.

Basic economics says pricing is proportional to demand and inversely proportional to supply. Honest and candid opinions have infinite demand and an uncertain supply.

DMR: There is a rumor about a R book you plan to publish in 2011 :-) Can you confirm the rumor and tell us more?

AO: I just signed a contract with Springer for ” R for Business Analytics”. R is a great software, and lots of books for statistically trained people, but I felt like writing a book for the MBAs and existing analytics users- on how to easily transition to R for Analytics.

Like any language there are tricks and tweaks in R, and with a focus on code editors, IDE, GUI, web interfaces, R’s famous learning curve can be bent a bit.

Making analytics beautiful, and simpler to use is always a passion for me. With 3000 packages, R can be used for a lot more things and a lot more simply than is commonly understood.
The target audience however is business analysts- or people working in corporate environments.

Brief Bio-
Ajay Ohri has been working in the field of analytics since 2004 , when it was a still nascent emerging Industries in India. He has worked with the top two Indian outsourcers listed on NYSE,and with Citigroup on cross sell analytics where he helped sell an extra 50000 credit cards by cross sell analytics .He was one of the very first independent data mining consultants in India working on analytics products and domestic Indian market analytics .He regularly writes on analytics topics on his web site www.decisionstats.com and is currently working on open source analytical tools like R besides analytical software like SPSS and SAS.

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Top Cartoonists:Updated

Here is a list of cartoonists I follow- I sometimes think they make more sense than all the news media combined.

1) Mike Luckovich He is a Pulitzer Prize winning cartoonist for AJC at http://blogs.ajc.com/mike-luckovich/

I love his political satire-sometimes not his politics- though he is a liberal (surprisingly most people from creative arts tend to be liberal- guess because they support and need welfare more, 🙂 ) Since I am in India- I call myself a conservative (when filing taxes) or liberal (when drinking er tea)

2) Hugh Mcleod- of Gaping Void is very different from Mike above, in the way an abstract painter would be from a classical

artist. I like his satire on internet, technology and personal favorite – social media consultants. Hugh casts a critical eye on the world of tech and is an immensely successful artist- probably the Andy Warhol of this genre in a generation.

3) Doug Savage of Savage Chickens http://www.savagechickens.com/ has a great series of funny cartoons based on chickens drawn on Post it notes. While his drawing is less abstract than Hugh’s above, he sometimes touches an irreverent note more like Hugh than anyone else.

4) Professor Jorge Cham of Phd Comics http://www.phdcomics.com/comics.php is probably the most read comic in grad school  – and probably the only cartoonist with a Phd I know of.

5) Scott Adams of Dilbert http://www.dilbert.com/ is probably the first “non kid stuff” cartoonist I started reading-in fact I once wrote to him asking for advice on my poetry to his credit- he replied with a single ” Best of Luck email”

They named our email server in Lucknow, UP, India for him (in my business school at http://iiml.ac.in ) Probably the best of corporate toon humor. Maybe they should make the Dilbert movie yet.

6) Randall Munroe of xkcd.com

XKCD is geek cartooning at its best.

For catching up with the best toons in a week, the best is Time.com ‘s weekly list at http://www.time.com/time/cartoonsoftheweek

It is the best collection of political cartoons.

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2011 Forecast-ying

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I had recently asked some friends from my Twitter lists for their take on 2011, atleast 3 of them responded back with the answer, 1 said they were still on it, and 1 claimed a recent office event.

Anyways- I take note of the view of forecasting from

http://www.uiah.fi/projekti/metodi/190.htm

The most primitive method of forecasting is guessing. The result may be rated acceptable if the person making the guess is an expert in the matter.

Ajay- people will forecast in end 2010 and 2011. many of them will get forecasts wrong, some very wrong, but by Dec 2011 most of them would be writing forecasts on 2012. almost no one will get called on by irate users-readers- (hey you got 4 out of 7 wrong last years forecast!) just wont happen. people thrive on hope. so does marketing. in 2011- and before

and some forecasts from Tom Davenport’s The International Institute for Analytics (IIA) at

http://iianalytics.com/2010/12/2011-predictions-for-the-analytics-industry/

Regulatory and privacy constraints will continue to hamper growth of marketing analytics.

(I wonder how privacy and analytics can co exist in peace forever- one view is that model building can use anonymized data suppose your IP address was anonymized using a standard secret Coco-Cola formula- then whatever model does get built would not be of concern to you individually as your privacy is protected by the anonymization formula)

Anyway- back to the question I asked-

What are the top 5 events in your industry (events as in things that occured not conferences) and what are the top 3 trends in 2011.

I define my industry as being online technology writing- research (with a heavy skew on stat computing)

My top 5 events for 2010 were-

1) Consolidation- Big 5 software providers in BI and Analytics bought more, sued more, and consolidated more.  The valuations rose. and rose. leading to even more smaller players entering. Thus consolidation proved an oxy moron as total number of influential AND disruptive players grew.

 

2) Cloudy Computing- Computing shifted from the desktop but to the mobile and more to the tablet than to the cloud. Ipad front end with Amazon Ec2 backend- yup it happened.

3) Open Source grew louder- yes it got more clients. and more revenue. did it get more market share. depends on if you define market share by revenues or by users.

Both Open Source and Closed Source had a good year- the pie grew faster and bigger so no one minded as long their slices grew bigger.

4) We didnt see that coming –

Technology continued to surprise with events (thats what we love! the surprises)

Revolution Analytics broke through R’s Big Data Barrier, Tableau Software created a big Buzz,  Wikileaks and Chinese FireWalls gave technology an entire new dimension (though not universally popular one).

people fought wars on emails and servers and social media- unfortunately the ones fighting real wars in 2009 continued to fight them in 2010 too

5) Money-

SAP,SAS,IBM,Oracle,Google,Microsoft made more money than ever before. Only Facebook got a movie named on itself. Venture Capitalists pumped in money in promising startups- really as if in a hurry to park money before tax cuts expired in some countries.

 

2011 Top Three Forecasts

1) Surprises- Expect to get surprised atleast 10 % of the time in business events. As internet grows the communication cycle shortens, the hype cycle amplifies buzz-

more unstructured data  is created (esp for marketing analytics) leading to enhanced volatility

2) Growth- Yes we predict technology will grow faster than the automobile industry. Game changers may happen in the form of Chrome OS- really its Linux guys-and customer adaptability to new USER INTERFACES. Design will matter much more in technology on your phone, on your desktop and on your internet. Packaging sells.

False Top Trend 3) I will write a book on business analytics in 2011. yes it is true and I am working with A publisher. No it is not really going to be a top 3 event for anyone except me,publisher and lucky guys who read it.

3) Creating technology and technically enabling creativity will converge at an accelerated rate. use of widgets, guis, snippets, ide will ensure creative left brains can code easier. and right brains can design faster and better due to a global supply chain of techie and artsy professionals.

 

 

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China -United States -The Third Opium War

U.S.troops in China during the Boxer Rebellion...
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A brief glance through http://www.treasury.gov/resource-center/data-chart-center/tic/Documents/mfh.txt

shows that while US added 600 billion of debt during the past one year, the Chinese actually reduced their exposure by 50 billion Dollars.

so who has been financing the debt for the US for the past one year- It is Japan- eager to keep its currency down and United Kingdom which has pumped in an extra 300 billion of T Bills.

See the whole table at official link above or at goo.gl/qMugp

—————————————————————————————-

China still remembers the Opium Wars in which the then ruling Anglo Saxon superpower used naval superiority to enforce trade and eventual political dependency. Is China unsure of the United States brotherly nice  intentions? They certainly seem to be putting their money that way.

http://en.wikipedia.org/wiki/Opium_Wars

Britain forced the Chinese government into signing theTreaty of Nanking and the Treaty of Tianjin, also known as the Unequal Treaties, which included provisions for the opening of additional ports to unrestricted foreign trade, for fixed tariffs; for the recognition of both countries as equal in correspondence; and for the cession of Hong Kong to Britain. The British also gained extraterritorial rights. Several countries followed Britain and sought similar agreements with China. Many Chinese found these agreements humiliating and these sentiments contributed to the Taiping Rebellion (1850–1864), the Boxer Rebellion (1899–1901), and the downfall of the Qing Dynasty in 1912, putting an end to dynastic China.

———————————————————————————————-

The Koreans can always be depended on provide the first shot in any conflict- and though Anglo-US-Chinese conflict would be expensive- I guess as long as the cost of outstanding debt with China is less than cost of a brief -techno-war , we would see interesting games in this neighborhood. Note China restricts major trade with United States particularly in software, internet services (like Web Advertising, Facebook, Twitter ) and represents a lucrative market for big pharma (especially in psychiatric drugs) and big tech once it reforms its intellectual property rights. Software would be the opium of the 21st Century- if Chinese resist the Treasury Bills as their poppy flowers. The widespread Western media coverage of school kids murders by pyschopaths is also a trade tactic to encourage flow of more US made medicine in the Chinese market.

It would also help create an economic revival in the United States to exaggerate the Chinese threat (remember Sputnik) and build up its own cyber spending. Any military or cyber humiliation for the ruling party in China can help create a political vacuum for more malleable and agreeable alternatives to emerge.

(to be continued)

 

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