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Algorithms that can help us spend, spend, spend

Algorithms that can help us spend, spend, spend | algorithms | Scoop.it

Intelligent algorithms are changing the way we do business, whether it’s in tempting us to buy designer shoes, or leading multi-million pound investments.

 

We've all heard it. That little imaginary companion, sitting on your shoulder. "Go on," it says. "You deserve a treat. Buy it."

 

That "it" could be anything. Clothes, shoes, gadgets - we all have our vices. But what if that imaginary voice - which is, willpower permitting, under your control - one day became real?

 

DBS Bank calls it a "personal concierge", and it's best understood by picturing yourself in an expensive designer clothes shop.

 

Your smartphone knows where you are - thanks to the GPS location technology found in many apps these days - and it alerts your bank through an automated system that you've signed up to. As well as knowing you've got a history of buying from similar stores, your bank also knows that you're running a bit low on cash at the moment.


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Why algorithms need humans to predict the weather

Why algorithms need humans to predict the weather | algorithms | Scoop.it

History is rich with intellectuals who have revered theories of determinism; ideas that suggest if we could only know every facet of a situation, every molecule of the landscape, we could predict and even shape future political, economic, and cultural outcomes.

 

But when it comes to the weather, forecasters long ago gave up any hope of cataloging all of the variables that could impact rainfall in Seattle, or the arrival of a cold front in New York. At least that’s what Nate Silver reports in his new book, The Signal and the Noise: Why So Many Predictions Fail — but Some Don’t, an excerpt of which was adapted for a recent article in The New York Times Magazine.

 

If you go by Silver’s account, weather forecasting is something of a dark art. Despite all of the measurements, modeling, and statistical analyses, the weather business relies as much on human insight as it does on computer programming. This is best evidenced by the National Weather Service’s own historical records. According to the agency’s data, a combination of human and computing power creates the most accurate weather forecasts. People improve accuracy levels for precipitation and temperature forecasts by about 25 percent and 10 percent respectively over forecasts done by computers alone.

 

In other words, the algorithms haven’t bested us yet.


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Scheduling tweets: Does common sense trump algorithms?

Scheduling tweets: Does common sense trump algorithms? | algorithms | Scoop.it

Several services offer to schedule your social media updates at times people are most likely to see them. This intrigues many businesses who worry their followers are missing important content.I've tried several of these services. Some social media experts praise them often. Scheduling content for the following day has its benefits when you won't have time to post in real time. But can a website actually provide precise insight on the best times to tweet?

 

People study this like a science, and you can sign up for webinars to learn the secrets. However, many of the experts explaining the benefits of scheduling social media are in the social media industry. Don't they benefit by convincing businesses that social media is not an exercise in randomness?

One service recommended that I tweet at times that most people, if they had to guess, would select anyway. The times were when most people get to work, eat lunch, and start preparing to head home. My wife and business partner, Loren, tried the same service, which provided her times similar to mine. Do our followers behave so similarly?


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How Algorithms Rule The World

How Algorithms Rule The World | algorithms | Scoop.it

In his new book, Aisle50 cofounder Christopher Steiner counts the (many, many) ways digits have come to dominate. "If you look at who has the biggest opportunity in society right now," he says, "it’s developers."

 

When Christopher Steiner, the 35-year-old cofounder of Aisle50, a Y Combinator startup offering online grocery deals, set out to write the book Automate This: How Algorithms Came to Rule Our World, (out tomorrow) he’d planned to focus solely on Wall Street. “There were a ton of good stories and then the Flash Crash happened. There was a lot to tell,” says Steiner. “But at some point I thought ‘Do people really care about the 13 different electronic training networks that were going on in the 1990’s?’” Instead the former technology journalist expanded his research to explore how the power of algorithms has spread far beyond Wall Street and now touches all of us--starting with today’s young innovators.

 

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luiy's curator insight, July 1, 2013 11:59 AM

I was intrigued by your discussion of Jon Kleinberg, a Cornell computer science professor who devised an algorithm to identify the influencers in a given organization.


He was the guy who came up with the original method that Google eventually used to create their PageRank algorithm. His newest algorithm ranks people and their place in society by how they affect others through language. For example, if, in any given group there’s one guy who influences the others more strongly than anyone else, he tends to be the leader. This can be measured quantitatively. The schematic of how this works looks just like the schematic of how web pages are ranked. Whoever is linked and has more power over all of these trusted sites is who ends up at the top of the Google rankings. Same for people.

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Do We Need Doctors Or Algorithms?

Do We Need Doctors Or Algorithms? | algorithms | Scoop.it
I was asked about a year ago at a talk about energy what I was doing about the other large social problems, namely health care and education.

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Google Search Algorithm Shifting to On-line Public Relations Campaigns

Google Search Algorithm Shifting to On-line Public Relations Campaigns | algorithms | Scoop.it

Google Search Algorithm Shifting to On-line Public Relations CampaignsThe Herald | HeraldOnline.comIn order to make sure that they accomplish this goal they are continually researching and studying information that is released from Google in order...


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5 Google algorithm updates that affect your Web traffic | SEO Entrepreneur

5 Google algorithm updates that affect your Web traffic | SEO Entrepreneur | algorithms | Scoop.it
SEO (Search Engine Optimization) is affected on a weekly basis by Google algorithm updates.

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How Will MIT's Reverse Engineering Of Twitter's Trending Topics Algorithm Impact Twitter's Advertising Business? - Forbes

How Will MIT's Reverse Engineering Of Twitter's Trending Topics Algorithm Impact Twitter's Advertising Business? - Forbes | algorithms | Scoop.it

Why algorithms aren't the key to Twitter campaigns

 

SUMMARY: MIT researchers are reverse-engineering the algorithms used to determine personalized trending topics on Twitter -- but that won't necessarily give brands an easy way to game the system, experts say. Predicting what will trend and generating and effectively promoting trend-worthy content are very different skills, explains Eric Dykstra. "If a brand really wants everyone to see their hash tag or trending topic, they're still going to pay for a promoted trend," he writes.

 

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Google algorithms of Love

Type (or paste) this into Google search:

 

sqrt(cos(x))cos(300x)+sqrt(abs(x))-0.7)(4-x*x)^0.01, sqrt(6-x^2), -sqrt(6-x^2) from -4.5 to 4.5


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How Facebook’s algorithm works

How Facebook’s algorithm works | algorithms | Scoop.it
Ever wonder why some of your Facebook posts get more views than others? Or how certain posts are chosen to show up in individual newsfeeds? There are many questions we all have about how Facebook works and this infographic provides some insight.

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Target's customer tracking algorithms are so good, they figured out a teen was pregnant and broke the news to her father by accident

Target's customer tracking algorithms are so good, they figured out a teen was pregnant and broke the news to her father by accident | algorithms | Scoop.it

Every time you go shopping, you share intimate details about your consumption patterns with retailers. And many of those retailers are studying those details to figure out what you like, what you need, and which coupons are most likely to make you happy. Target, for example, has figured out how to data-mine its way into your womb, to figure out whether you have a baby on the way long before you need to start buying diapers.

 

Target keeps close tabs on everything its customers buy. They tag their customers with guest IDs and store all the detailed information they get from each customer. They then analyze the information and track it. They’ve become so accurate at tracking that they’ve been able to predict with extreme accuracy when women become pregnant. Target has created a system that allows them to send coupons for expecting mothers. They have an algorithm that includes 25 very specific products. When a person buys those products, they can predict a pregnancy with decent confidence. What's even scarier is that they can even guess when the person's going to be due based on what they buy!

 

What they’ve found is that they freak out their customers by congratulating them on their pregnancies before the customer has formally set up any registry or anything with Target, or even told their own family!

 

A father in Minneapolis went to a local Target demanding to speak with a manager. He was livid that his daughter had received coupons and information on maternity clothing and baby items. It was inappropriate for Target to be sending his daughter, who was still in high school, information like that promoting pregnancy.

 

Later, the manager called the father to apologize again and was told that the father had spoken to his daughter. She admitted that she was pregnant and due in August, so the father apologized to the manager.


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Why do we assume economic algorithms are always right?

Why do we assume economic algorithms are always right? | algorithms | Scoop.it

I am writing this in the grips of a profound headache, largely brought on by my stumbling efforts to get a grip on where we are with our economies.

 

If our global economy were a commercial aircraft, and I one of the pilots, the entire instrument panel would be covered in flashing lights. But instead of sounding steady alarms, most would be stuttering on and off in apparently random patterns, making coherent responses very difficult. And that mental image had me racing back to the inquiry report on Air France 447, which disappeared en route from Rio de Janeiro to Charles de Gaulle on 1 June 2009.

 

Apart from routine fears of flying, those boarding the Airbus A330 would have had no reason to expect anything untoward. But, in the worst accident in French aviation history, the plane fell out of the sky into the Atlantic, killing all 228 people aboard. The causes were a mystery for air crash investigators, though early suspicions focused on the possible icing up of the critical airspeed monitoring devices called pitot tubes. It took Herculean efforts to retrieve the black boxes, but they provided a much clearer idea of what had gone so dramatically wrong.


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Seven Things Human Editors Do that Algorithms Don't (Yet)

Seven Things Human Editors Do that Algorithms Don't (Yet) | algorithms | Scoop.it

Business bloggers at Harvard Business Review discuss a variety of business topics including managing people, innovation, leadership, and more.

By - Eli Pariser - The Conversation - Harvard Business Review


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Artists and Not Algorithms Should Curate Our Music Discoveries

Artists and Not Algorithms Should Curate Our Music Discoveries | algorithms | Scoop.it

Robin Good: Maurice Boucher takes a stand for human curators in the arts, by placing string emphasis on the fact that purely alorithmic solutions cannot really discern people expressed needs and desires from unexpressed ones.

 

His central point is this: "At the heart of the online music curation role is the possible solution to the expressed need versus unexpressed desire problem that permeates the Internet and prevents us from developing internet culture beyond purely commercial interests."

 

He writes: "...I know of no algorithm that can work out the difference between what people ask for and what they actually desire.

 

That is the philosophical question that really is the core software requirement of a music recommendation engine, and music curation is an ideal testbed case to see if we can build a layer on the internet to act as verification of the search process.

 

...communicating socially and informally (with strangers) and sharing music is not enough to build a bridge between what people ask for and what they desire.

 

People have to have a sense that some agency is acting at least semi-exclusively for them and has some insight into who they are."


"At the heart of the online music curation role is the possible solution to the expressed need verses unexpressed desire problem that permeates the Internet and prevents us from developing internet culture beyond purely commercial interests."

 

"The artists have to be included in the equations that run the algorithms of curation and filtering for the internet to have a future beyond being just another compendium of useless facts and trivia."

 

 

Rightful. 8/10

 

Full article: http://north.com/thinking/guest-post-web-curation-and-filtering-defining-new-roles-for-digital-artists/




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Computer Algorithm Used To Make Movie For Sundance Film Festival | Singularity Hub

Computer Algorithm Used To Make Movie For Sundance Film Festival | Singularity Hub | algorithms | Scoop.it

Indie movie makers can be a strange bunch, pushing the envelope of their craft and often losing us along the way. In any case, if you’re going to produce something unintelligible anyway, why not let a computer do it? Eve Sussmam and the Rufus Corporation did just that. She and lead actor Jeff Wood traveled to the Kazakhstan border of the Caspian Sea for two years of filming. But instead of a movie with a beginning, middle and end, they shot 3,000 individual and unrelated clips. To the clips they added 80 voice-overs and 150 pieces of music, mixed it all together and put it in a computer. A program on her Mac G5 tower, known at Rufus as the “serendipity machine,” then splices the bits together to create a final product.


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Google Panda Algorithm Updates Dissected

Google Panda Algorithm Updates Dissected | algorithms | Scoop.it
January 2011 was still a blissful time for farmers, despite the inferior seed that they were planting and the fact that they have often just been “a...

 

Panda is in the game

 

Panda was a perfect tool for the job. Well not perfect, the algorithm is, naturally, still being updated quite frequently. Since its inception it has been through a lot of changes, but its purpose remains the same, weeding out the websites that are ranked higher that they objectively deserve. As it is mostly an automated process, one can’t really expect it to be infallible, but constant updates and improvements to the algorithm are at least keeping some people on their toes, and ensuring that they will think twice before stealing someone else’s content or post a nonsensical wall of text instead of a well thought out and written article. Another advantage of the new algorithm was that it took the entire website into consideration.

 

Before Panda, pages of a website were assessed individually, allowing a terribly constructed website with just one well made page to be displayed on the first page of search results. Today, sites are judged as a whole, if you have a bunch of duplicated content, unfavorable content/ads ratio or anything else that is deemed undesirable by the algorithm, that fact will be reflected in your rankings.


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The New Algorithm of Web Marketing

The New Algorithm of Web Marketing | algorithms | Scoop.it

The future is programmatic, Web marketers say

 

SUMMARY: Programmatic buying is changing the balance of power between Web publishers and advertisers, experts say. Marketers are increasingly focused on tracking consumers across the Web rather than buying up space on specific sites, with programmatic bidding now accounting for about 10% of all online display advertising. "It's allowing advertisers to assign value to media rather than publishers," explains Ben Winkler, chief digital officer at OMD.

 

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Leap forward in brain-controlled computer cursors: New algorithm greatly improves speed and accuracy

Leap forward in brain-controlled computer cursors: New algorithm greatly improves speed and accuracy | algorithms | Scoop.it
Researchers have designed the fastest, most accurate algorithm yet for brain-implantable prosthetic systems that can help disabled people maneuver computer cursors with their thoughts.

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Searching for Cupid's algorithm

Searching for Cupid's algorithm | algorithms | Scoop.it
Is it possible for a computer to know what makes us fall in love? Online dating websites are in pursuit of the perfect algorithm.

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Algorithms Can Help Curators Pre-Filter, Discover and Learn From Like-Minded Colleagues

Algorithms Can Help Curators Pre-Filter, Discover and Learn From Like-Minded Colleagues | algorithms | Scoop.it


Robin Good: Alexis Dufresne of Faveeo, an up and coming information filtering and discovery tool not yet available to the general public, has been posting some interesting articles on topics related to news curation, filtering and discovery.

 

In particular, I found interesting his recent analysis on automated solutions and algorithms designed to help scale curation efforts, as these are generally discarded as inappropriate for any type of professional work. But, as he rightly points out, there are several tasks inside a curator workflow that can indeed help and reduce the curator's workload without limiting his ability to manually select and edit what he finds most appropriate.

Alexis pinpoints at least three different areas in which algorithms and automated operations can indeed greatly help the curator's work. These are:

 

1) Discovery of new sources and networks: ...By teaching a machine about the kind of sources and users a curator is looking for, a machine could process from the incredible mass of sources and people out there to figure out those who are likely to be trusted sources of information. By using techniques of text analysis, social reach, semantic density, popularity and more, this task could be done by a machine.

 

2) Learning the profile of a curator: A lot of engines are focusing on filtering the semantic meaning of an article in order to recommend other content. But by using advanced NLP techniques and text extraction methods, we could go further and have an idea of the tone, the lenght and other signals that can indicate the preferences of a human curator, other than simply the actual keywords used in the text.

 

3) Social recommendations: ...By detecting users that seem to click, like, share or save the same articles, we can connect them together to mutualize their search and discovery operations, in order to speed things up.

 

Rightful. Helpful. 8/10

 

Full article: http://www.faveeo.com/computer-assisted-curation-lets-figure-out-best-system-help-scale-curation-operations

 

 


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Faveeo's comment, April 18, 2013 7:20 AM
Faveeo Update : Two new features to speed up fresh discovery - http://eepurl.com/ycrBL