Exciting Contest at CrowdANALYTIX

A new contest from a relatively new website. This one is fast and furious and has a decent chunk of money!

 

From

 

http://www.crowdanalytix.com/contests/airport-guest-sentiment-analysis-1544282253/view/

 

Submission Deadline:
Sun, 26 February 2012 05:00 AM UTC
Results Announced by:
Mon, 05 March 2012 05:00 AM UTC
Category: Text Analytics Function: Aerospace & Aviation

 

Title
Analysis of sentiment and its intensity – feedback from airport guests
Description
ABC (name intentionally obfuscated) is one of the best managed and highly profitable airports  in India. As with all well managed airports, ABC would like to understand what guests feel about their experience when traveling, using or transiting through their airport. ABC has a website in which guests can visit and leave behind a comment, agree or disagree with others’ comments, or respond to a comment confirming or negating the expressed opinion.

The goal of this contest is to create a summarization of the opinions, feelings and sentiments expressed in the comments left behind by guests on the website. This information is being provided as data for solvers. Some understanding of the intensity of the opinion, feeling or sentiment will also be useful. For example, if there is a consistent demand for more spas across guest conversations, it needs to be highlighted.  Consistent positive or negative sentiments and opinions need to be discovered and highlighted.
Data
Guest comments have been crawled and provided to you. The data consists approximately 1000 comments from guests including the timestamp of those comments.  Personal information (name, email etc) have been hidden. This data is publicly available
Solver Expectations:
Participants may submit entries before the deadline. If a participant submits multiple entries, the entry submitted last before the deadline will be considered as the participant’s submission.
The following deliverables are expected to be submitted:
  • a report expressing the results of the opinion and sentiment mining
  • documentation about how you approached the problem, what tools, technologies and languages you used, and what problems you encountered
Timeline and Prizes: 
This contest begin on 16 Feb 2012 and will last for a duration of 9 days.
Prizes:
  • One 1st Prize – $1000
  • One 2nd Prize – $500
  • Two 3rd Prizes – $250

On Software

1) All software has bugs. Sometimes this is because people have been told to code in a hurry to meet shipping deadlines. Sometimes it is due to the way metal and other software interact with it. Mostly it is karma.

2) In the 21 st Century,It is okay to insult someone over his software , but not over most other things. Sometimes I think people are passionate not just for their own software but to just diss the other guys. It is a politically convenient release.

3) Bloggers writing about software are full of bull-by products. If they were any good in writing code, they would not have time to write a blog. Mostly bloggers on code are people whose coding enthusiasm is more than their coding competence.

4) Software is easier than it looks to people who know it. To those who dont know how to code, it will always be a bit of magic.

5) Despite immense progress, initiatives and encouragement- the number of females writing code is too low . Comparatively, figuratively and literally. If you are a male and want a social life- get into marketing while the hair is still black.

Man walks into Bar. Says to Women at Bar. ” Hey,What do you do, Me- I write code”

See!

6) People who write software end up making more money not just because they create useful stuff that helps get work done faster or helps reduce boredom for people. They make more money because they are mostly passionate, logical problem thinkers, focused, hard working and better read on a variety of subjects than others. That’s your cue to how to make money even if you cannot code.

7) I would rather write much more code rather than write poetry. But I sometimes think they are related. Just manipulating words in different languages to manipulate output in different machines or people.

8) Kids should be taught software at early age , as that is a skill that helps in their education and thinking. More education for the kids!

9) Laying off talented software people because you found a cheaper , younger alternative half across the globe is sometimes evil. It is also inevitable. Learn more software as you grow older.

10) The best software is the one in your head. It was written by a better programmer too.

 

Interview Kelci Miclaus, SAS Institute Using #rstats with JMP

Here is an interview with Kelci Miclaus, a researcher working with the JMP division of the SAS Institute, in which she demonstrates examples of how the R programming language is a great hit with JMP customers who like to be flexible.

 

Ajay- How has JMP been using integration with R? What has been the feedback from customers so far? Is there a single case study you can point out where the combination of JMP and R was better than any one of them alone?

Kelci- Feedback from customers has been very positive. Some customers are using JMP to foster collaboration between SAS and R modelers within their organizations. Many are using JMP’s interactive visualization to complement their use of R. Many SAS and JMP users are using JMP’s integration with R to experiment with more bleeding-edge methods not yet available in commercial software. It can be used simply to smooth the transition with regard to sending data between the two tools, or used to build complete custom applications that take advantage of both JMP and R.

One customer has been using JMP and R together for Bayesian analysis. He uses R to create MCMC chains and has found that JMP is a great tool for preparing the data for analysis, as well as displaying the results of the MCMC simulation. For example, the Control Chart platform and the Bubble Plot platform in JMP can be used to quickly verify convergence of the algorithm. The use of both tools together can increase productivity since the results of an analysis can be achieved faster than through scripting and static graphics alone.

I, along with a few other JMP developers, have written applications that use JMP scripting to call out to R packages and perform analyses like multidimensional scaling, bootstrapping, support vector machines, and modern variable selection methods. These really show the benefit of interactive visual analysis of coupled with modern statistical algorithms. We’ve packaged these scripts as JMP add-ins and made them freely available on our JMP User Community file exchange. Customers can download them and now employ these methods as they would a regular JMP platform. We hope that our customers familiar with scripting will also begin to contribute their own add-ins so a wider audience can take advantage of these new tools.

(see http://www.decisionstats.com/jmp-and-r-rstats/)

Ajay- Are there plans to extend JMP integration with other languages like Python?

Kelci- We do have plans to integrate with other languages and are considering integrating with more based on customer requests. Python has certainly come up and we are looking into possibilities there.

 Ajay- How is R a complimentary fit to JMP’s technical capabilities?

Kelci- R has an incredible breadth of capabilities. JMP has extensive interactive, dynamic visualization intrinsic to its largely visual analysis paradigm, in addition to a strong core of statistical platforms. Since our brains are designed to visually process pictures and animated graphs more efficiently than numbers and text, this environment is all about supporting faster discovery. Of course, JMP also has a scripting language (JSL) allowing you to incorporate SAS code, R code, build analytical applications for others to leverage SAS, R and other applications for users who don’t code or who don’t want to code.

JSL is a powerful scripting language on its own. It can be used for dialog creation, automation of JMP statistical platforms, and custom graphic scripting. In other ways, JSL is very similar to the R language. It can also be used for data and matrix manipulation and to create new analysis functions. With the scripting capabilities of JMP, you can create custom applications that provide both a user interface and an interactive visual back-end to R functionality. Alternatively, you could create a dashboard using statistical and/or graphical platforms in JMP to explore the data and with the click of a button, send a portion of the data to R for further analysis.

Another JMP feature that complements R is the add-in architecture, which is similar to how R packages work. If you’ve written a cool script or analysis workflow, you can package it into a JMP add-in file and send it to your colleagues so they can easily use it.

Ajay- What is the official view on R from your organization? Do you think it is a threat, or a complimentary product or another statistical platform that coexists with your offerings?

Kelci- Most definitely, we view R as complimentary. R contributors are providing a tremendous service to practitioners, allowing them to try a wide variety of methods in the pursuit of more insight and better results. The R community as a whole is providing a valued role to the greater analytical community by focusing attention on newer methods that hold the most promise in so many application areas. Data analysts should be encouraged to use the tools available to them in order to drive discovery and JMP can help with that by providing an analytic hub that supports both SAS and R integration.

Ajay-  While you do use R, are there any plans to give back something to the R community in terms of your involvement and participation (say at useR events) or sponsoring contests.

 Kelci- We are certainly open to participating in useR groups. At Predictive Analytics World in NY last October, they didn’t have a local useR group, but they did have a Predictive Analytics Meet-up group comprised of many R users. We were happy to sponsor this. Some of us within the JMP division have joined local R user groups, myself included.  Given that some local R user groups have entertained topics like Excel and R, Python and R, databases and R, we would be happy to participate more fully here. I also hope to attend the useR! annual meeting later this year to gain more insight on how we can continue to provide tools to help both the JMP and R communities with their work.

We are also exploring options to sponsor contests and would invite participants to use their favorite tools, languages, etc. in pursuit of the best model. Statistics is about learning from data and this is how we make the world a better place.

About- Kelci Miclaus

Kelci is a research statistician developer for JMP Life Sciences at SAS Institute. She has a PhD in Statistics from North Carolina State University and has been using SAS products and R for several years. In addition to research interests in statistical genetics, clinical trials analysis, and multivariate analysis/visualization methods, Kelci works extensively with JMP, SAS, and R integration.

.

 

Interview JJ Allaire Founder, RStudio

Here is an interview with JJ Allaire, founder of RStudio. RStudio is the IDE that has overtaken other IDE within the R Community in terms of ease of usage. On the eve of their latest product launch, JJ talks to DecisionStats on RStudio and more.

Ajay-  So what is new in the latest version of RStudio and how exactly is it useful for people?

JJ- The initial release of RStudio as well as the two follow-up releases we did last year were focused on the core elements of using R: editing and running code, getting help, and managing files, history, workspaces, plots, and packages. In the meantime users have also been asking for some bigger features that would improve the overall work-flow of doing analysis with R. In this release (v0.95) we focused on three of these features:

Projects. R developers tend to have several (and often dozens) of working contexts associated with different clients, analyses, data sets, etc. RStudio projects make it easy to keep these contexts well separated (with distinct R sessions, working directories, environments, command histories, and active source documents), switch quickly between project contexts, and even work with multiple projects at once (using multiple running versions of RStudio).

Version Control. The benefits of using version control for collaboration are well known, but we also believe that solo data analysis can achieve significant productivity gains by using version control (this discussion on Stack Overflow talks about why). In this release we introduced integrated support for the two most popular open-source version control systems: Git and Subversion. This includes changelist management, file diffing, and browsing of project history, all right from within RStudio.

Code Navigation. When you look at how programmers work a surprisingly large amount of time is spent simply navigating from one context to another. Modern programming environments for general purpose languages like C++ and Java solve this problem using various forms of code navigation, and in this release we’ve brought these capabilities to R. The two main features here are the ability to type the name of any file or function in your project and go immediately to it; and the ability to navigate to the definition of any function under your cursor (including the definition of functions within packages) using a keystroke (F2) or mouse gesture (Ctrl+Click).

Ajay- What’s the product road map for RStudio? When can we expect the IDE to turn into a full fledged GUI?

JJ- Linus Torvalds has said that “Linux is evolution, not intelligent design.” RStudio tries to operate on a similar principle—the world of statistical computing is too deep, diverse, and ever-changing for any one person or vendor to map out in advance what is most important. So, our internal process is to ship a new release every few months, listen to what people are doing with the product (and hope to do with it), and then start from scratch again making the improvements that are considered most important.

Right now some of the things which seem to be top of mind for users are improved support for authoring and reproducible research, various editor enhancements including code folding, and debugging tools.

What you’ll see is us do in a given release is to work on a combination of frequently requested features, smaller improvements to usability and work-flow, bug fixes, and finally architectural changes required to support current or future feature requirements.

While we do try to base what we work on as closely as possible on direct user-feedback, we also adhere to some core principles concerning the overall philosophy and direction of the product. So for example the answer to the question about the IDE turning into a full-fledged GUI is: never. We believe that textual representations of computations provide fundamental advantages in transparency, reproducibility, collaboration, and re-usability. We believe that writing code is simply the right way to do complex technical work, so we’ll always look for ways to make coding better, faster, and easier rather than try to eliminate coding altogether.

Ajay -Describe your journey in science from a high school student to your present work in R. I noticed you have been very successful in making software products that have been mostly proprietary products or sold to companies.

Why did you get into open source products with RStudio? What are your plans for monetizing RStudio further down the line?

JJ- In high school and college my principal areas of study were Political Science and Economics. I also had a very strong parallel interest in both computing and quantitative analysis. My first job out of college was as a financial analyst at a government agency. The tools I used in that job were SAS and Excel. I had a dim notion that there must be a better way to marry computation and data analysis than those tools, but of course no concept of what this would look like.

From there I went more in the direction of general purpose computing, starting a couple of companies where I worked principally on programming languages and authoring tools for the Web. These companies produced proprietary software, which at the time (between 1995 and 2005) was a workable model because it allowed us to build the revenue required to fund development and to promote and distribute the software to a wider audience.

By 2005 it was however becoming clear that proprietary software would ultimately be overtaken by open source software in nearly all domains. The cost of development had shrunken dramatically thanks to both the availability of high-quality open source languages and tools as well as the scale of global collaboration possible on open source projects. The cost of promoting and distributing software had also collapsed thanks to efficiency of both distribution and information diffusion on the Web.

When I heard about R and learned more about it, I become very excited and inspired by what the project had accomplished. A group of extremely talented and dedicated users had created the software they needed for their work and then shared the fruits of that work with everyone. R was a platform that everyone could rally around because it worked so well, was extensible in all the right ways, and most importantly was free (as in speech) so users could depend upon it as a long-term foundation for their work.

So I started RStudio with the aim of making useful contributions to the R community. We started with building an IDE because it seemed like a first-rate development environment for R that was both powerful and easy to use was an unmet need. Being aware that many other companies had built successful businesses around open-source software, we were also convinced that we could make RStudio available under a free and open-source license (the AGPLv3) while still creating a viable business. At this point RStudio is exclusively focused on creating the best IDE for R that we can. As the core product gets where it needs to be over the next couple of years we’ll then also begin to sell other products and services related to R and RStudio.

About-

http://rstudio.org/docs/about

Jjallaire

JJ Allaire

JJ Allaire is a software engineer and entrepreneur who has created a wide variety of products including ColdFusion,Windows Live WriterLose It!, and RStudio.

From http://en.wikipedia.org/wiki/Joseph_J._Allaire
In 1995 Joseph J. (JJ) Allaire co-founded Allaire Corporation with his brother Jeremy Allaire, creating the web development tool ColdFusion.[1] In March 2001, Allaire was sold to Macromedia where ColdFusion was integrated into the Macromedia MX product line. Macromedia was subsequently acquired by Adobe Systems, which continues to develop and market ColdFusion.
After the sale of his company, Allaire became frustrated at the difficulty of keeping track of research he was doing using Google. To address this problem, he co-founded Onfolio in 2004 with Adam Berrey, former Allaire co-founder and VP of Marketing at Macromedia.
On March 8, 2006, Onfolio was acquired by Microsoft where many of the features of the original product are being incorporated into the Windows Live Toolbar. On August 13, 2006, Microsoft released the public beta of a new desktop blogging client called Windows Live Writer that was created by Allaire’s team at Microsoft.
Starting in 2009, Allaire has been developing a web-based interface to the widely used R technical computing environment. A beta version of RStudio was publicly released on February 28, 2011.
JJ Allaire received his B.A. from Macalester College (St. Paul, MN) in 1991.
RStudio-

RStudio is an integrated development environment (IDE) for R which works with the standard version of R available from CRAN. Like R, RStudio is available under a free software license. RStudio is designed to be as straightforward and intuitive as possible to provide a friendly environment for new and experienced R users alike. RStudio is also a company, and they plan to sell services (support, training, consulting, hosting) related to the open-source software they distribute.

Statistics on Social Media

Some official statistics on social media from the owners themselves

1) Facebook-

http://www.facebook.com/press/info.php?statistics

Date -17 Nov 2011

Statistics

People on Facebook

Preview- Google Cloud SQL

From –http://code.google.com/apis/sql/

What is Google Cloud SQL?

Google Cloud SQL is web service that allows you to create, configure, and use relational databases with your App Engine applications. It is a fully-managed service that maintains, manages, and administers your databases, allowing you to focus on your applications and services.

By offering the capabilities of a MySQL database, the service enables you to easily move your data, applications, and services into and out of the cloud. This allows for high data portability and helps in faster time-to-market because you can quickly leverage your existing database (using JDBC and/or DB-API) in your App Engine application.

Here is where you can get an invite to the beta only Google Cloud SQL

Sign up for Limited Preview

Google Cloud SQL is available to a limited number of users. To sign up for the service:

  1. Visit the Google APIs Console. The console opens the All services pane.
  2. Find the SQL Service line in the Services table and click Request access…
  3. Fill out the enrollment form.
  4. Our team will review your enrollment information and respond by email to the address associated with your Google Account.
  5. Follow the link in the email to view the Terms of Service. Please read these carefully before accepting.
  6. Sign up for the google-cloud-sql-announce group to receive important announcements and product news. (NOTE- Members: 384)
and after all that violence and double talk, a walk in the clouds with SQL.
1. There are three kinds of instances in the beta view
2. Wait for the Instance to be created note- the Design of the Interface uptil now is much better than Amazon’s.  
Note you need to have an appspot application from Google Apps and can choose between the Python and Java versions. Quite clearly there is a play for other languages too. I think GO is also supported.
3. You can import your data from your Google Storage bucket
4. I am not that hot at coding or maybe the interface was too pretty. Anyways- the log tells me that import of the text file has failed from Google Storage to Google Cloud SQL 
5. Incidentally the Google Cloud Storage interface is also much better than the Amazon GUI for transferring data- Note I was using the classical statistical dataset Boston Housing Data as the test case. 
6. The SQL prompt is the weakest part of the design process of the Interphase. There is no Query builder and the SELECT FROM WHERE prompt is slightly amusing/ insulting . I mean guys either throw in a fully fledged GUI for query builder similar to the MYSQL Workbench , than create a pretty white command prompt.
7. You can also export your data back to your Google Storage bucket 
These are early days, and I am trying to see if there is a play for some cloud kind of ODBC action between R, Prediction API , and the cloud SQL… so try it out yourself at http://code.google.com/apis/sql/ and see if there is any juice you can build  here.

LibreOffice – Extensions and Templates

Just an announcement from The Document Foundation (which has notable supporters including Google etc at http://www.documentfoundation.org/supporters/)

With both Google Docs and Libre Office – it seems like a flank attack on Office productivity software (from the cloud and from the PC/tablet ground)- however Microsoft’s Sharepoint is much better in collobration compared to the Google Docs and it has huge number of templates (more than the 38 extensions and 13 templates right now at the links below (just like WordPress has huge number of themes compared to Blogger)

Anyways, check out- it is an interesting start

http://extensions.libreoffice.org/

Extension Releases 

Extensions for all program modules
Gallery Contents for all program modules
Language Tools for all program modules
Dictionaries of different languages for all program modules
Writer-Extensions
Calc-Extensions
Impress-Extensions
Draw-Extensions
Base-Extensions
Math-Extensions 

….

and http://templates.libreoffice.org/

Template Releases

Accounting -Templates
Agenda-Templates
Arts-Templates
Book-Templates
Brochure/Pamphlet-Templates
Budget-Templates
Business-Templates
Business POS-Templates
Business Shipping-Templates
Calendar-Templates
Card-Templates
Curriculum/Resume-Templates
CD/DVD-Templates
Certificate-Templates
Checkbook-Templates
Christmas-Templates
Computer-Templates
Conference-Templates
E-book-Templates
Education-Templates
Academia-Templates
Elementary/Secondary School-Templates
Envelope-Templates
Fax-Templates
Genealogy-Templates
Grocery-Templates
Invoice-Templates
Labels-Templates
Letter-Templates
Magazine-Templates
Media-Templates
Memo-Templates
Music-Templates
Newsletter-Templates
Notes-Templates
Paper-Templates
Presentation-Templates
Recipe-Templates
Science-Templates
Sports-Templates
Timeline-Templates
Timesheet-Templates
Trades-Templates
To Do List-Templates
Writer-Templates