Film Services and their recommendation feature

Besides smartphone, smart TV is also a hot trend today and in the near future. User can play game, listen to music, surf the internet, comment on their facebook and, also watch film or video.

Film service for TV is novel domain which has just started for 5 years. For any film provider, the number of film retention is target. Film recommendation is the way to improve this number. It is mentioned that Netflix and Hulu after are two honest film providers that published recommendation research for film. All of them use metadata as primary attributes to decide what film for recommending.

For evaluating a recommendation system, this post may useful.

News aggregator, more and more

A lot of news channels are the first reason for a news aggregator service being launched! Certainly, human race don't want to update from only one source. And they also want to get new information in many categories. For instance, you love football and of course, you want to track the score of Sunday matches. You love technology, keep tracking on Techcrunch, Mashable. You're in passion for software development, keep up with MindShift or Hacker News. A news aggregator, therefore,  is built to keep all sources (customisable) in one. This article tries to survey how many news aggregators was launched and how did aggregator trend develop. 

I list some news aggregators (without ranking)

1. http://www.parsely.com/
2. http://www.news.me/
3. http://www.reddit.com/
4. http://www.feedly.com/
5. http://www.huffingtonpost.com/

(to be continued...)

Resource for iOS Development

(This post will always update when I get new info)

In fact, no one can deny the mobile trend. In the below figure, it shows you the mobile market size which is made at the end 2012.

Mobile market size
(through http://www.digitallabblogasia.com/?attachment_id=901)

1.08 billion smartphones! What? 1.08 billion! And in the below infographics, it reveals the total app downloads of 4 big platforms: Android, iOS, Blackberry and Window Phone. We can recognize easily that iOS platform (was developed by Apple Inc. ) is leading in app market with 30 billions downloads.

Total app downloads. 30 billions downloads for Apple's app (Q2/2012)
( through http://www.mobilestatistics.com/mobile-statistics)

So, this post will discuss iOS development. More details, it will present the useful resources for anyone who want to begin with iOS platform. This post will attempt to  cover as much as possible necessary knowledge for making iOS app.

We should divide into 4 sections: resource for beginner, advanced resource, how to make money with iOS app, marketing strategy.
Let's start!

1. Beginner
1. Mobile tutsplus is the great site for newbie. All of tutorials are step by step clearly. It also focuses on mobile design, mobile marketing strategy.
2. Advance resource
3. How to make money
1. http://www.placeplay.com/how-to-make-money-with-apps-1/ (must review after) 
4. Design (UI & UX)
1. Mobile Usability by Jakob Nielsen. This book is very up-to-date and cover abundance of usability knowledge http://www.amazon.com/Mobile-Usability-Jakob-Nielsen/dp/0321884485
2. Human Interface Guidelines by Apple (http://developer.apple.com/library/ios/documentation/userexperience/conceptual/mobilehig/MobileHIG.pdf)
3. Smashing's Documents (http://www.smashingmagazine.com/2010/11/03/ebook-4-mobile-design-for-iphone-and-ipad/)
4. Brian Fling's slide (http://www.slideshare.net/fling/mobile-20-design-develop-for-the-iphone-and-beyond)
5. Marketing Strategy
6. 
   

Thanks for reading!

Resource for Big Data

(This post will always update when I get new info)

Recently, We were heard the phrase 'Big Data' a lots, a lots, a lots! Everywhere, 'Big Data' was appeared : Computer Science Journals , Computer Science Conferences, Technology Journals, Technology Conferences, Technology articles, Famous Blog articles, Startup Conferences, Startup Blog, so on and so on. So, I am a junior Developer in Data Mining. Therefore, Big Data is also my research domain. In this post, I show the resources for learning or working with Big Data.

We will have three types: Blog, Company site and Github repository.

1. Blog
1.1 Machine Learning Guru's Blog
1.1.1 Prof. Larry Wasserman's Blog
Prof. Larry is professor in the Department  of Statistics/Machine Learning  in Carnegie Mellon University. He shares his research, the trending  of Big Data, Machine Learning, Statistics and others. His blog was considered as the best Machine Learning Blog by Nguyen Xuan Long, the primary blogger at http://procul.org/blog .


2. Company Site
2.1 Cloudera Inc.
Cloudera's CTO is Apache Hadoop's author, Doug Cutting. Cloudera develops Hadoop-based software for business purposes. All of their softwares are open source! So great!



3. Github


In addition, you can use Quora to update Big Data news.  I usually use it to get useful information about Big Data/Data Mining and others.
Thanks for reading!