Is Random Poetry Click Fraud

Meta-search-vi
Image via Wikipedia

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.

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

Also-

Data Visualization: Central Banks

Iron Ore Company of Canada
Image via Wikipedia

Trying to compare the transparency of central banks via the data visualization of two very different central banks.

One is Reserve Bank of India and the other is Federal Reserve Bank of New York

Here are some points-

1) The federal bank gives you a huge clutter of charts to choose from and sometimes gives you very difficult to understand charts.

see http://www.newyorkfed.org/research/global_economy/usecon_charts.html

and http://www.newyorkfed.org/research/directors_charts/us18chart.pdf

us18chart

2) The Reserve bank of India choose Business Objects and gives you a proper drilldown kind  of  graph and tables. ( thats a lot of heavy metal and iron ore China needs from India 😉 😉

Foreign Trade – Export      Time-line: ALL

TIME LINE COUNTRY COMMODITY AMOUNT (US $ MILLION) EXPORT QUANTITY
2010:07 (JUL) – P China IRON ORE (Units: TON) 205.06 1878456
2010:06 (JUN) – P China IRON ORE (Units: TON) 427.68 6808528
2010:05 (MAY) – P China IRON ORE (Units: TON) 550.67 5290450
2010:04 (APR) – P China IRON ORE (Units: TON) 922.46 9931500
2010:03 (MAR) – P China IRON ORE (Units: TON) 829.75 13177672
2010:02 (FEB) – P China IRON ORE (Units: TON) 706.04 10141259
2010:01 (JAN) – P China IRON ORE (Units: TON) 577.13 8498784
2009:12 (DEC) – P China IRON ORE (Units: TON) 545.68 9264544
2009:11 (NOV) – P China IRON ORE (Units: TON) 508.17 9509213
2009:10 (OCT) – P China IRON ORE (Units: TON) 422.6 7691652
2009:09 (SEP) – P China IRON ORE (Units: TON) 278.04 4577943
2009:08 (AUG) – P China IRON ORE (Units: TON) 276.96 4371847
2009:07 (JUL) China IRON ORE (Units: TON) 266.11 4642237
2009:06 (JUN) China IRON ORE (Units: TON) 241.08 4584354

Source : DGCI & S, Ministry of Commerce & Industry, GoI

 

You can see the screenshots of the various visualization tools of the New York Fed Reserve Bank and Indian Reserve Bank- if the US Fed is serious about cutting the debt maybe it should start publishing better visuals

Stuxnet DeMystified

Detail of a New York Times Advertisement - 1895
Image via Wikipedia

A fascinating article in New York Times details the fascinating details of the Stuxnet virus, apparently the most successful cyber weapon in recent times.

Given that Industrial Controllers are a part of a everything from factories to missile launch configurations, I believe this is a fascinating area of study for the world’s research scientists including creating variants and defenses for this.

https://www.nytimes.com/2011/01/16/world/middleeast/16stuxnet.html

Also a 2008 presentation by Siemens that the NYT was kind enough to link to- (whither Wikileaks ??)

EU files anti trust against Google to reduce budget deficit

From the Old Lady-

http://www.nytimes.com/2010/12/01/technology/01google.html?_r=1&hpw

Google’s dominance on the Internet has been a sore point in Europe, where it controls more than 80 percent of the online search market, compared with about 66 percent in the United States, according to comScore, a research firm.

and

If Google is found in violation of European competition law, the commission has the power to fine it up to 10 percent of its annual revenue, which totaled more than $23 billion last year.

Before settling last year, Microsoft had paid fines of about $2.4 billion over the past decade in a long-running antitrust case in Brussels that focused on the Windows operating system.

In another case, the commission fined Intel about $1.45 billion for abusing its dominance in the computer chip market.


——————————————————————————————

Maybe Google should ask the European Union to buy a groupon for anti trust cases.

Related

11 Ways to Beat Google

 

 

PAW Reception and R Meetup

New DC meetup for R Users-

source- http://www.meetup.com/R-users-DC/calendar/14236478/

October’s R meet-up will be co-located with the Predictive Analytics World Conference (http://www.predictive…) taking place in Washington DC October 19-20. PAW is the premiere business-focused event for predictive analytics professionals, managers and commercial practitioners.

Agenda:

6:30 – 7:30 PAW Reception (open to meet-up attendees)
7:30 – 9:00 DC-R Meetup

Talks:
“How to speak ggplot2 like a native”
Harlan D. Harris, PhD @HarlanH

“Saving the world with R”
Michael Milton @michaelmilton

Important Registration Instructions:
You are welcome to RSVP here at meetup. The PAW organizers have requested that we register in the PAW site for the R meetup so they can provide badges to members which will give you access to the reception. There is no charge to register using the PAW site. Please click here to register.


Speaker Bios

Harlan D. Harris, PhD, is a statistical data scientist working for Kaplan Test Prep and Admissions in New York City. He has degrees from the University of Wisconsin-Madison and the University of Illinois at Urbana-Champaign. Prior to turning to the private sector, he worked as a researcher and lecturer in various areas of Artificial Intelligence and Cognitive Science at the University of Illinois, Columbia University, the University of Connecticut, and New York University.

Harlan’s talk is titled “How to speak ggplot2 like a native.”. One of the most innovative ideas in data visualization in recent years is that graphical images can be described using a grammar. Just as a fluent speaker of a language can talk more precisely and clearly than someone using a tourist phrasebook, graphics based on a grammar can yield more insights than graphics based on a limited set of templates (bar chart, pie graph, etc.). There are at least two implementations of the Grammar of Graphics idea in R, of which the most popular is the ggplot2 package written by Prof. Hadley Wickham. Just as with natural languages, ggplot2 has a surface structure made up of R vocabulary elements, as well as a deep structure that mediates the link between the vocabulary and the “semantic” representation of the data shown on a computer screen. In this introductory presentation, the links among these levels of representation are demonstrated, so that new ggplot2 users can build the mental models necessary for fluent and creative visualization of their data.

Michael Milton is a Client Manager at Blue State Digital. When he’s not saving the world by designing interactive marketing strategies that connect passionate users with causes and organizations, he writes about data and analytics. For O’Reilly Media, he wrote Head First Data Analysis and Head First Excel and has created the videos Great R: Level 1 and Getting the Most Out of Google Apps for Business.

Michael’s talk is called “How to Save the World Using R.” In this wide-ranging discussion, Michael will highlight individuals and organizations who are using R to help others as well as ways in which R can be used to promote good statistical thinking.