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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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Hybridization of Evolutionary Algorithms

Evolutionary algorithms are good general problem solver but suffer from a lack of domain specific knowledge. However, the problem specific knowledge can be added to evolutionary algorithms by hybridizing. Interestingly, all the elements of the evolutionary algorithms can be hybridized. In this chapter, the hybridization of the three elements of the evolutionary algorithms is discussed: the objective function, the survivor selection operator and the parameter settings. As an objective function, the existing heuristic function that construct the solution of the problem in traditional way is used. However, this function is embedded into the evolutionary algorithm that serves as a generator of new solutions.

 

In addition, the objective function is improved by local search heuristics. The new neutral selection operator has been developed that is capable to deal with neutral solutions, i.e. solutions that have the different representation but expose the equal values of objective function. The aim of this operator is to directs the evolutionary search into a new undiscovered regions of the search space. To avoid of wrong setting of parameters that control the behavior of the evolutionary algorithm, the self-adaptation is used. Finally, such hybrid self-adaptive evolutionary algorithm is applied to the two real-world NP-hard problems: the graph 3-coloring and the optimization of markers in the clothing industry. Extensive experiments shown that these hybridization improves the results of the evolutionary algorithms a lot. Furthermore, the impact of the particular hybridizations is analyzed in details as well.

  
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Cheating slime mold gets the upper hand

Cheating slime mold gets the upper hand | Social Foraging | Scoop.it

A  ‘cheater’ mutation (chtB) inDictyostelium discoideum, a free living slime mould able to co-operate as social organism when food is scarce, allows the cheater strain to exploit its social partner, finds a new study published in BioMed Central’s open access journal BMC Evolutionary Biology. The mutation ensures that when mixed with ‘normal’ Dictyostelium  more than the fair share of cheaters become spores, dispersing to a new environment, and avoiding dying as stalk cells. 

Dictyostelium have an unusual life style. They generally live as individual amoeboid cells, eating bacteria in leaf litter and soil. However when they run out of food they form a multi-cellular ‘slug’ capable of travelling to a new environment. However if conditions are right they behave more like a fungus, producing a stalk and a fruiting body which releases spores. During this co-operative behaviour approximately 20% become stalk cells which are doomed to starvation but, after dispersal, the spores germinate into new amoeba.

The chtB strain is able to reduce the ability of normalDictyostelium to form spores so that when mixed in equal numbers with wild type Dictyostelium 60% of the spores will be chtB. The chtB mutation appeared to be normal in all other respects and the mutation had no ‘fitness cost’ which might impede its behaviour or lifespan. In fact the mutation allowed chtB to divide faster in liquid medium.

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Biomimicry: sharkskin ships and whale flipper wind turbines

Biomimicry: sharkskin ships and whale flipper wind turbines | Social Foraging | Scoop.it
From the splendour of a peacock’s feathers to the aerodynamic body of a cheetah, natural selection has worked to engineer animals to the highest standards for survival and prosperity in their environment. Throughout history, humans have tried to emulate the wonders and beauty of the natural world in science, design and art. 

Over the past 20 years, however, this process of learning from and emulating nature has developed into a defined scientific discipline and burgeoning industry, known as “biomimicry”. 

People have always looked to nature for inspiration. In the sixteenth century, Leonardo Da Vinci made detailed sketches of birds’ anatomy to better understand the science of flight and foster ideas for his “flying machine”. The Wright brothers, over 400 years later, were still studying birds’ wings, as a potential model for the first airplane.

Yet it was only in 1997 that the term “biomimicry” was coined, and the concept really began to take off as a serious practice in the business world.

The term “biomimicry” was first used by the American biologist and authorJanine Benyus, in her book Biomimicry: Innovation Inspired by Nature. She defines biomimicry, not merely as learning “about” the natural world, but learning “from” it. Benyus calls this “the conscious emulation of life’s genius”.
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Artificial Intelligence in Motion: Introduction to Recommendations with Map-Reduce and mrjob

Artificial Intelligence in Motion: Introduction to Recommendations with Map-Reduce and mrjob | Social Foraging | Scoop.it

I will present how can we use map-reduce programming model for making recommendations.   Recommender systems are quite popular among shopping sites and social network thee days. How do they do it ?   Generally, the user interaction data available from items and products in shopping sites and social networks are enough information to build a recommendation engine using classic techniques such as Collaborative Filtering.

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Complexity, Requirements and The Perfect Cup Of Tea

Complexity, Requirements and The Perfect Cup Of Tea | Social Foraging | Scoop.it

The words any software developer dreads hearing are “Can you just change this one thing for this one user/client/company”. The requests usually have perfectly valid reasons, but it’s sometimes hard to explain to the person asking for the feature why it’s more work than just the code. Most of the time it’s not the coding that’s terribly hard, it’s making it just so for that particular user, testing it, maintaining it and then you have the nightmare two years down the line when you have to change code that touches it.

 

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Testing Einstein's famous equation E=mc2 in outer space

Testing Einstein's famous equation E=mc<sup>2</sup> in outer space | Social Foraging | Scoop.it

University of Arizona physicist Andrei Lebed has stirred the physics community with an intriguing idea yet to be tested experimentally: The world's most iconic equation, Albert Einstein's E=mc2, may be correct or not depending on where you are in space.


With the first explosions of atomic bombs, the world became witness to one of the most important and consequential principles in physics: Energy and mass, fundamentally speaking, are the same thing and can, in fact, be converted into each other.

 

This was first demonstrated by Albert Einstein's Theory of Special Relativity and famously expressed in his iconic equation, E=mc2, where E stands for energy, m for mass and c for the speed of light (squared).

 

Although physicists have since validated Einstein's equation in countless experiments and calculations, and many technologies including mobile phones and GPS navigation depend on it, University of Arizona physics professor Andrei Lebed has stirred the physics community by suggesting that E=mc2 may not hold up in certain circumstances.

 

The key to Lebed's argument lies in the very concept of mass itself. According to accepted paradigm, there is no difference between the mass of a moving object that can be defined in terms of its inertia, and the mass bestowed on that object by a gravitational field. In simple terms, the former, also called inertial mass, is what causes a car's fender to bend upon impact of another vehicle, while the latter, called gravitational mass, is commonly referred to as "weight."


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GraphLab - Large-Scale Machine Learning on Graphs

Designing and implementing efficient, bug free parallel and distributed algorithms can be very challenging. To address this challenge high-level data-parallel abstractions like Map-Reduce expose a simple computational pattern that isolates users form the complexities of large-scale parallel and distribute system design. Unfortunately, many important computational tasks are not inherently data-parallel and cannot be efficiently or intuitively expressed in data-parallel abstractions.

 

GraphLab is a high-level graph-parallel abstraction that efficiently and intuitively expresses computational dependencies. Unlike Map-Reduce where computation is applied to independent records, computation in GraphLab is applied to dependent records which are stored as vertices in a large distributed data-graph. Computation in GraphLab is expressed as a vertex-programs which are executed in parallel on each vertex and can interact with neighboring vertices. In contrast to the more general message passing and actor models, GraphLab constrains the interaction of vertex-programs to the graph structure enabling a wide range of system optimizations. GraphLab programs interact by directly reading the state of neighboring vertices and by modifying the state of adjacent edges. In addition, vertex-programs can signal neighboring vertex-programs causing them to be rerun at some point in the future.

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Gary Bamford's comment, January 17, 2013 3:20 AM
I have no idea what this means but it sounds something like how the old mechanical integration engines used to operate!?
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Hurricane Sandy, Open Data and Social Media

From hackathons to social media, open government is transforming the way that Mayor Bloomberg’s administration and New York City government serve the public. And there has been no greater testament to open government’s potential than the strategy and innovation in action during Hurricane Sandy.

 

Learning from our experience during Hurricane Irene, in the days leading up to Hurricane Sandy’s landfall in New York City, government technologists reached out to the data science community to share recently updated hurricane evacuation zone maps based on up-to-the-minute flooding projections. To ensure wide  public access to this valuable information, the City’s IT Department immediately published the data to the City’s Open Data portal, enabling developers and designers to develop emergency maps and applications. For the second consecutive year, the City also partnered with organizations such as WNYC.org, The New York Times, and Google’s Crisis Response team, which developed a customized New York City-centric Hurricane Sandy map featuring evacuation zones, shelters, food distributions centers, warming centers, recovery centers and more resources.

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Psychologists Uncover Hidden Signals of Trust — Using a Robot

Psychologists Uncover Hidden Signals of Trust — Using a Robot | Social Foraging | Scoop.it

“In spite of the hardness and ruthlessness I thought I saw in his face, I got the impression that here was a man who could be relied upon when he had given his word."

 

Neville Chamberlain’s first impression of Adolf Hitler can charitably be described as an error in judgment. Rarely do our own miscalculations result in tragedy, yet popular sentiment seems to hold that when it comes to truly trusting others, you just never know. Wolves in sheep’s clothing abound, and prudence demands skepticism. Whether we are deciding on a babysitter, a doctor, or a car, we try to not base our judgments on our first impressions. We ask for references, and look up reviews and blue book values.  We know that “I’ve just got a good feeling about this” can be famous last words.

 

But this may not be a full portrayal of our capacity to judge others’ character. New research led by David DeSteno at Northeastern University suggests that when it comes to deciding whom to trust, our first impressions can be quite accurate. In fact, personality traits such as honesty and fairness are linked to specific kinds of nonverbal cues, and humans can pick up on these signals during interactions. According to these researchers we are like robots, programmed to move in particular ways if we are honest. To know who to trust, one simply needs to be able to read the patterns.

Ashish Umre's insight:

Link to the research paper: http://socialemotions.org/page5/files/Trust%20Paper_PsycSci_Final.pdf

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From the Amazon rainforest to human body cells: Quantifying stability

From the Amazon rainforest to human body cells: Quantifying stability | Social Foraging | Scoop.it

As they typically result from severe external perturbations, it is of vital interest how stable the most desirable state is. Surprisingly, this basic question has so far received little attention. Now scientists of the Potsdam Institute for Climate Impact Research (PIK), in a paper published in Nature Physics, propose a new concept for quantifying stability.


"Up to now, science was able to say if a complex system is stable or not, but it wasn't able to properly say how stable it is," says Peter J. Menck, lead author of the paper. The proposed concept is the first to fill this gap. "We conceive a system's alternative states as points in a mountainous landscape with steep rocks and deep valleys," explains Menck. "In the sinks between the peaks, a system comes to rest like a rolling ball would. Now the likelihood that the system returns to a specific sink after suffering a severe blow strongly depends on how big the surrounding valley is." In the high-dimensional systems Menck and his colleagues study, the equivalent of the valley is called the basin of attraction. The basin's volume is the measure the authors suggest to use for the quantification of stability.

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Social Network Based Search for Experts

Our system illustrates how information retrieved from social networks can be used for suggesting experts for specific tasks. The system is designed to facilitate the task of finding the appropriate person(s) for a job, as a conference committee member, an advisor, etc. This short description will demonstrate how the system works in the context of the HCIR2012 published tasks.

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Structure and Dynamics of Information Pathways in Online Media

Diffusion of information, spread of rumors and infectious diseases are all instances of stochastic processes that occur over the edges of an underlying network. Many times networks over which contagions spread are unobserved, and such networks are often dynamic and change over time. In this paper, we investigate the problem of inferring dynamic networks based on information diffusion data. We assume there is an unobserved dynamic network that changes over time, while we observe the results of a dynamic process spreading over the edges of the network. The task then is to infer the edges and the dynamics of the underlying network.


We develop an on-line algorithm that relies on stochastic convex optimization to efficiently solve the dynamic network inference problem. We apply our algorithm to information diffusion among 3.3 million mainstream media and blog sites and experiment with more than 179 million different pieces of information spreading over the network in a one year period. We study the evolution of information pathways in the online media space and find interesting insights. Information pathways for general recurrent topics are more stable across time than for on-going news events. Clusters of news media sites and blogs often emerge and vanish in matter of days for on-going news events. Major social movements and events involving civil population, such as the Libyan's civil war or Syria's uprise, lead to an increased amount of information pathways among blogs as well as in the overall increase in the network centrality of blogs and social media sites.

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Physical Limits to Leaf Size in Tall Trees

Leaf sizes in angiosperm trees vary by more than 3 orders of magnitude, from a few mm to over 1 m. This large morphological freedom is, however, only expressed in small trees, and the observed leaf size range declines with tree height, forming well-defined upper and lower boundaries. The vascular system of tall trees that distributes the products of photosynthesis connects distal parts of the plant and forms one of the largest known continuous microfluidic distribution networks. In biological systems, intrinsic properties of vascular systems are known to constrain the morphological freedom of the organism. We show that the limits to leaf size can be understood by physical constraints imposed by intrinsic properties of the carbohydrate transport network. The lower boundary is set by a minimum energy flux, and the upper boundary is set by a diminishing gain in transport efficiency.

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4th International Workshop on Modeling Social Media: Mining, Modeling and Recommending 'Things' in Social Media - Workshop at Hypertext 2013

In our first workshop on Modeling Social Media (MSM 2010 in Toronto, Canada), we explored various different models of social media ranging from user modeling, hypertext models, software engineering models, sociological models and framework models. In our second workshop (MSM 2011 in Boston, USA), we addressed the user interface aspects of modeling social media. In our third workshop (MSM 2012 in Milwaukee, USA), we looked at the collective intelligence in social media, i.e. making sense of the content and context from social media websites such as Facebook, Twitter, Google+ and Foursquare by analyzing tweets, tags, blog posts, likes, posts and check-ins, in order to create a new knowledge and semantic meaning. With this year's workshop we aim to attract researchers from all over the world working in the field of social media mining, modeling and end-user applications. In particular, we would like to invite researchers working on the important field of "recommender systems" for social media which is gaining more and more in importance due to the increasing information overload problem. 


The goal of this workshop is to continue our vibrant discussion on social media mining and modelling with a special focus on recommender systems for social media applications. Hence, the workshop aims to attract and discuss various novel aspects of social media mining, modelling and doing recommendations on top of these data/models. In short the workshop invites topics such as social media mining methods/techniques, novel approaches to model users or things in social media, frameworks to harvest and/or display social media data and new social media recommender methods/techniques/algorithms or interfaces supporting users for instance in information finding, meta-data application etc. Thus, our goal is to bring together researchers and practitioners from all over the world with diverse backgrounds interested in 1) exploring different perspectives and approaches to mine (complex) and analyse social media data, 2) modelling social media users and 3) building applications such as recommender systems on top of this data/models.

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Submission deadlinesPaper Submission:Monday, February 04, 2013Acceptance Notification:Monday, February 18, 2013Paper Final Version Due: Thursday, February 28, 2013Workshop: May 01, 2013
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Biomimicry Solves Age-old Industrial Air Pollution Problem

Biomimicry Solves Age-old Industrial Air Pollution Problem | Social Foraging | Scoop.it

Enter inventor Matthew Johnson from the Department of Chemistry at theUniversity of Copenhagen. "Biomimicry" may not be the perfect term to describe what Johnson did, which mimics how Mother Nature cleans Earth's atmosphere rather than how any particular life-form works, but the concept of copying natural processes seems to fit in the category. Johnson describes his inspiration:


"I have investigated the self-cleaning mechanism of the atmosphere for years. Suddenly I realized, that the mechanism is so simple, that we could wrap it in a box and use it to clean indoor air. This makes for a better indoor climate, and in this particular case it also removes smells from this industrial process allowing the company to stay and making the neighbours happy."

 

Earth's atmosphere cleans itself when polluting gasses plus sunlight plus naturally occurring ozone cause the pollutants to clump together as particles, which can then be washed out in the next rain.

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The Materiality of Algorithms

The Materiality of Algorithms | Social Foraging | Scoop.it

One of the most exciting aspects of the new research analyzing algorithmic culture is the manner by which portions of that research are increasingly routing around the slow, painful process of traditional academic knowledge production. This is not to say that the credentialing process afforded by peer-reviewed journals or university presses is irrelevant, but it is to say that this aspect of scholarly work is only one form among the many others now emerging both on- and offline.  Overviews of stand-alone talks are now available through a variety of blogs, while a double session at this year’s 4S on “The Politics of Algorithms” was illuminating for those of us lucky enough to attend.  Journals like Limn blur the boundaries between old and new forms of scholarship. All of this is just a long way of saying that, since I first alluded to the notion of a “sociology of algorithms” in 2011, I’ve been stimulated by my contact with a much wider community doing great work on these issues, much of which I’ve encountered through this very blog.

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Cognitive benefit of lifelong bilingualism

Seniors who have spoken two languages since childhood are faster than single-language speakers at switching from one task to another, according to a study published in the January 9 issue of The Journal of Neuroscience. Compared to their monolingual peers, lifelong bilinguals also show different patterns of brain activity when making the switch, the study found.


The findings suggest the value of regular stimulating mental activity across the lifetime. As people age, cognitive flexibility -- the ability to adapt to unfamiliar or unexpected circumstances -- and related "executive" functions decline. Recent studies suggest lifelong bilingualism may reduce this decline -- a boost that may stem from the experience of constantly switching between languages. However, how brain activity differs between older bilinguals and monolinguals was previously unclear.

 

In the current study, Brian T. Gold, PhD, and colleagues at the University of Kentucky College of Medicine, used functional magnetic resonance imaging (fMRI) to compare the brain activity of healthy bilingual seniors (ages 60-68) with that of healthy monolingual seniors as they completed a task that tested their cognitive flexibility. The researchers found that both groups performed the task accurately. However, bilingual seniors were faster at completing the task than their monolingual peers despite expending less energy in the frontal cortex -- an area known to be involved in task switching.


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Alexandra Strickland's curator insight, September 12, 2013 7:13 AM

Fascinating insight into bilingualism and its impact on your life!

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How To Build Your Analytics Confidence | Analytics & Optimization

How To Build Your Analytics Confidence | Analytics & Optimization | Social Foraging | Scoop.it

Do you know someone that is afraid of Analytics? Not afraid in the sense that if you open a dashboard the person will climb a chair and start screaming... I mean afraid as in the 3rd definition of Merriam-Webster: "having a dislike for something - afraid of hard work"

 

Over the years I noticed that people often ask questions without even checking their Analytics tool. The information is sometimes one click away, right after signing in. So how come they didn't find it? My assumption is that people are generally afraid of Analytics, they won't login and surf their reports looking for data and insights, like they probably do at YouTube or at Wikipedia. And this is probably a syntom of a lack of confidence.

 

A few weeks ago I watched the video below, a TED Talk by David Kelley, founder of legendary design firm IDEO and Professor at the Institue of Design at Stanford. The presentation provides interesting facts of life, psychological theories, business and life-changing experiences. And I believe it is very relevant for Analytics.

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Moving beyond Hadoop for big data needs

Hadoop and MapReduce have long been mainstays of the big data movement, but some companies now need new and faster ways to extract business value from massive -- and constantly growing -- datasets.

 

While many large organizations are still turning to the open source Hadoop big data framework, its creator, Google, and others have already moved on to newer technologies.

 

The Apache Hadoop platform is an open source version of the Google File System and Google MapReduce technology. It was developed by the search engine giant to manage and process huge volumes of data on commodity hardware.

 

It's been a core part of the processing technology used by Google to crawl and index the Web.

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BNA 2013 Festival of Neuroscience: Exploring and Celebrating Neuroscience

BNA 2013 Festival of Neuroscience: Exploring and Celebrating Neuroscience | Social Foraging | Scoop.it

The British Neuroscience Association's biennial meeting in 2013 will be a unique event. Eighteen learned societies with a neuroscience interest - both clinical and non-clinical - have contributed one or more symposia to the programme, creating a meeting with 56 scientific sessions and 8 plenary lectures involving more than 240 speakers, over 80 from outside the U.K.

The hottest topics in neuroscience research will be covered, and we expect over 1000 poster presentations representing all aspects of the subject.

As the venue for the BNA2013 meeting is the Barbican Centre - one of London's leading entertainment venues - a major public engagement programme will form part of the Festival of Neuroscience - enabling members of the public to interact with scientists, carers, charities, funders, policy-makers...and some well-known celebrities with experience of mental health issues...to learn more about the brain and the importance of a multi-disciplinary approach to research.

Ashish Umre's insight:

Dates: 7th - 10th April 2013

The Barbican Centre, London, UK.

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Swype Living Language uses crowdsourcing to add new words

Swype Living Language uses crowdsourcing to add new words | Social Foraging | Scoop.it
A new version of Swype is out and this one has a new feature which  Nuance Communications, the people behind Dragon Dictate and Swype, called Living Language. Swype Living Language uses crowdsourcing to find new trending words and adds them to the keyboard’s dictionary.

 

Crowdsourcing, in this context, means that as other users add words to their personal dictionaries the data is sent to Swype’s servers and popular and trending words are automatically pushed out to other users. You need to specifically opt into the service by going to Swype settings and tapping on Language Options. Tap Living language to activate the crowdsourcing. Nuance hope that this new feature will make the keyboard’s predictive results better allowing users to speed up their input.

 

Also new in this version is a feature called Smart Editor. It analyzes the last entered sentence and highlights any potential errors, along with suggestions, to enable you to fix the text quickly. I tapped “Gong home now” into a text message and Swype correctly underlined Gong and suggested Going. Neat!

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UPS Drivers Vs. The UPS Algorithm and the Travelling Salesman Problem

UPS Drivers Vs. The UPS Algorithm and the Travelling Salesman Problem | Social Foraging | Scoop.it

A lot of times, I feel like an explorer,” says Jack Levis, UPS’s director of process management. “Often I’m telling the company: Just because we’ve done it this way for the past 50 years doesn’t mean it’s right.”

 

Levis, who manages a team of mathematicians who build the algorithms that help UPS shave millions of miles off delivery routes, is paid to tell the company things it may not want to hear. One of his major projects in the last decade has been rolling out a system called ORION (On-Road Integrated Optimization and Navigation), a kind of algorithmic overmind that knows better than any human how drivers ought to plan their routes.

 

ORION was first conceived in 2000, but wasn’t tested till 2008. Over the past four years, the system has rolled out to some 50 UPS buildings; it will take another half-decade or so to roll out the system throughout UPS. “It’s one driver at a time, one building at a time,” says Levis.

 

Developing a system of this magnitude--and making a 105-year-old company comfortable with it--was no easy feat. Fast Company caught up with Levis to glean a few lessons.

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OK, Stupid: IAC to Bring Dating Algorithms to Tutor.com After Acquisition

OK, Stupid: IAC to Bring Dating Algorithms to Tutor.com After Acquisition | Social Foraging | Scoop.it

Oh, algorithms: So good for trading stocks,handicapping elections and finding Mrs. Right—and now, perhaps, finding the right online tutor.

 

IAC, the parent company to Match.com and OKCupid, acquired Tutor.com, according to a press release, noting an opportunity to apply its expertise in marketing and distribution to the online education service.

 

Founded in 1998, Tutor.com touts itself as the world’s largest online tutoring service, claiming a network of 2,500 experts who provide homework help and professional development over a proprietary online platform. According to The New York Times, which reported on the deal last night, 90 percent of the company’s business comes from partnerships with institutions such as the U.S. military, schools and libraries.

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Multi-layered Social Networks

It is quite obvious that in the real world, more than one kind of relationship can exist between two actors and that those ties can be so intertwined that it is impossible to analyse them separately [Fienberg 85], [Minor 83], [Szell 10]. Social networks with more than one type of relation are not a completely new concept [Wasserman 94] but they were analysed mainly at the small scale, e.g. in [McPherson 01], [Padgett 93], and [Entwisle 07]. Just like in the case of regular single-layered social network there is no widely accepted definition or even common name. At the beginning such networks have been called multiplex network [Haythornthwaite 99], [Monge 03].

 

The term is derived from communications theory which defines multiplex as combining multiple signals into one in such way that it is possible to separate them if needed [Hamill 06]. Recently, the area of multi-layered social network has started attracting more and more attention in research conducted within different domains [Kazienko 11a], [Szell 10], [Rodriguez 07], [Rodriguez 09], and the meaning of multiplex network has expanded and covers not only social relationships but any kind of connection, e.g. based on geography, occupation, kinship, hobbies, etc. [Abraham 12]. This essay aims to summarize existing knowledge about one concept which has many different names i.e. the concept of Multi-layered Social Network also known as Layered social network, Multi-relational social network, Multidimensional social network, Multiplex social network

  
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Bandit Algorithms for Website Optimization

Bandit Algorithms for Website Optimization | Social Foraging | Scoop.it

When looking for ways to improve your website, how do you decide which changes to make? And which changes to keep? This concise book shows you how to use Multiarmed Bandit algorithms to measure the real-world value of any modifications you make to your site. Author John Myles White shows you how this powerful class of algorithms can help you boost website traffic, convert visitors to customers, and increase many other measures of success.

This is the first developer-focused book on bandit algorithms, which were previously described only in research papers. You’ll quickly learn the benefits of several simple algorithms—including the epsilon-Greedy, Softmax, and Upper Confidence Bound (UCB) algorithms—by working through code examples written in Python, which you can easily adapt for deployment on your own website.

 

Learn the basics of A/B testing—and recognize when it’s better to use bandit algorithms

 

Develop a unit testing framework for debugging bandit algorithms
Get additional code examples written in Julia, Ruby, and JavaScript with supplemental online materials

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